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Planning: CRISES: Reskilling and Upskilling for an Age of Technological Disruption

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

Decades of research show that significant changes in the returns to workers’ skills, driven primarily by rapid technological change, have dramatically affected U.S. income, employment, physical health, and psychological well-being. The resulting rise in economic and social inequality has already torn the nation’s social fabric, and rapid advances in AI, machine learning, and related technologies will likely bring additional disruptive changes to the skills the American labor market will demand. How can this challenge be met? Drawing upon the best research by labor economists, management scholars, and technology experts, our team will explore what future technological changes might come and what skills are likely to provide strong returns even given technological uncertainty. Drawing upon the best research by learning scientists, we will also explore how we can design effective and affordable educational institutions, instructional approaches, and technologies that will enable workers – especially those without college degrees – to reskill and upskill when hit by current or future technological shocks. We will take a rigorous, data-driven approach to targeting the skills and skill combinations with the highest expected future payoffs for workers in a range of occupational categories. Then, we will leverage the best research in learning sciences and educational technology to teach these skills effectively, with a strong emphasis on vocational education and training opportunities for those not attending a four-year college.<br/><br/>The ability of labor economists and management scholars to measure the returns to specific skills over the short run and the long run has been significantly expanded by the availability of new data. These advances hold out the possibility of using labor market outcomes to target more effectively the kinds of skills contemporary workers should acquire in an age of rapid technological change. Some of the same technologies shifting demand for skills also create new opportunities for AI-enhanced personalized instruction, acceleration of learning, and effective upskilling/reskilling, especially for lower-income and historically marginalized communities who may face significant threats from the next wave of technology-led disruption. As the capabilities of AI-driven adaptive learning software have advanced, researchers have demonstrated that the personalization of learning achieved by these systems can yield large learning gains. Embedding generative AI in established learning technologies systems offers exciting new opportunities to amplify and extend these gains, while dramatically reducing development costs. The PIs will work together with community college instructors to develop and deploy these cutting-edge technologies in community college STEM programs. By providing a blueprint for AI-augmented learning that could be used in community college and vocational programs across the country, the research plans we will work toward in this planning grant could help address shortages of workers with key skills, while creating cost-effective, accessible pathways to living wage jobs for workers who previously lacked those opportunities. Over a longer time horizon, these efforts could potentially impact the lives of millions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437451

[{'FirstName': 'David', 'LastName': 'Deming', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Deming', 'EmailAddress': 'david_deming@harvard.edu', 'NSF_ID': '000853088', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Carolyn', 'LastName': 'Rose', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carolyn P Rose', 'EmailAddress': 'cp3a@andrew.cmu.edu', 'NSF_ID': '000441071', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'James', 'LastName': 'Winyard', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James H Winyard', 'EmailAddress': 'jwinyard@ccac.edu', 'NSF_ID': '0000A0F2D', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lee', 'LastName': 'Branstetter', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lee G Branstetter', 'EmailAddress': 'branstet@cmu.edu', 'NSF_ID': '000342657', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'National Bureau of Economic Research Inc', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385359', 'PhoneNumber': '6178683900', 'StreetAddress': '1050 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'GT28BRBA2Q49', 'ORG_LGL_BUS_NAME': 'NATIONAL BUREAU OF ECONOMIC RESEARCH INC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'National Bureau of Economic Research Inc', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385359', 'StreetAddress': '1050 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437451.xml'}

Planning: CRISES: A Center on Clean Energy and Society

NSF

09/15/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

This project supports planning for a new Center on Clean Energy and Society (CES). The goal of the project is to investigate the social, political, and behavioral processes relevant to scaling up clean energy infrastructure in the United States and around the world. The planning grant supports organizational activities over a two-year period including interdisciplinary meetings to identify key research on the societal aspects of clean energy development; a synthesis of existing research on clean energy and society; and an outreach meeting with relevant stakeholders. The approval of solar and wind energy projects is a complicated process involving numerous actors and stakeholders at a range of spatial scales. Institutional factors play an especially key role in energy infrastructure development. This planning project supports the development of a human-centered approach to the reliable, affordable, equitable, and effective solutions needed for clean energy development. <br/><br/>This project investigates the social and institutional processes of clean energy development. The research project particularly investigates under what conditions does support for a clean energy economy materialize, and whether clean energy development boosts community resilience, energy reliability, and national security. The benefits and the costs of rolling out clean energy fall unequally to different people along lines of income and racial diversity. The proposed CES Center addresses these challenges, and the organizational activities supported by this planning grant lay the groundwork for a broader research program tackling these questions. Ultimately, the goal of this work is to generate knowledge to understand the complex mechanisms grounding the societal dimensions of clean energy development. This involves identifying various social, political, and institutional barriers to clean energy and assessing the effectiveness of various strategies to surmount those barriers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437479

[{'FirstName': 'Jennifer', 'LastName': 'Hadden', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer Hadden', 'EmailAddress': 'jen_hadden@brown.edu', 'NSF_ID': '000744400', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jeff', 'LastName': 'Colgan', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeff D Colgan', 'EmailAddress': 'jeff_colgan@brown.edu', 'NSF_ID': '000990997', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Christopher', 'LastName': 'Rea', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher M Rea', 'EmailAddress': 'christopher_rea@brown.edu', 'NSF_ID': '000871734', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'ZipCode': '029129100', 'PhoneNumber': '4018632777', 'StreetAddress': '1 PROSPECT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'RI01', 'ORG_UEI_NUM': 'E3FDXZ6TBHW3', 'ORG_LGL_BUS_NAME': 'BROWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'E3FDXZ6TBHW3'}

{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'StateCode': 'RI', 'ZipCode': '029129127', 'StreetAddress': '1 PROSPECT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'RI01'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437479.xml'}

Collaborative Research: Conference: NSF Computer and Information Science and Engineering Research Expansion Program (CISE MSI) 2024-2026 Aspiring Principal Investigators Workshop

NSF

08/01/2024

07/31/2026

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'James Fowler', 'PO_EMAI': 'jafowler@nsf.gov', 'PO_PHON': '7032928910'}

Many minority-serving institutions (MSIs) encounter challenges to establishing and maintaining a robust research enterprise, including a lack of training in proposal writing, difficulties in starting research partnerships, and limited involvement of MSI students in research endeavors. To address these obstacles, this project will organize four workshops to aimed at training aspiring principal investigators (PIs) from MSIs in the southern and southeastern US states, preparing participants for submitting proposals to the CISE MSI program in the 2025 and 2026 competitions. The events will provide a platform for participants to meet at large, share research insights, identify challenges and opportunities, and initiate potential research collaborations. Broader-impact aspects of the project comprise the broadening participation of over 60 MSI scholars as well as the fostering of MSI collaborations across nine US states.<br/><br/>The workshops will pursue four major objectives: 1) Community building - the strengthening of relationships among data science (DS), artificial intelligence (AI), and extended reality (XR) to boost broader data-intensive research communities at MSIs; 2) Cross-learning: the facilitating of knowledge sharing, the exchanging of best practices, and the training of aspiring PIs from MSIs to leverage success and enhance proposal development skills; 3) Mentoring - the providing of each research team with experienced coaching; 4) Collaboration development - the fostering of new collaborations, the exploring of future opportunities to advance research initiatives, and the preparing of collaborative proposals towards CISE MSI-focused programs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/31/2024

07/31/2024

None

Grant

47.070

1

4900

4900

2437481

[{'FirstName': 'Kewei', 'LastName': 'Sha', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kewei Sha', 'EmailAddress': 'kewei.sha@unt.edu', 'NSF_ID': '000699250', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Sharad', 'LastName': 'Sharma', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sharad Sharma', 'EmailAddress': 'sharad.sharma@unt.edu', 'NSF_ID': '000326939', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of North Texas', 'CityName': 'DENTON', 'ZipCode': '762051132', 'PhoneNumber': '9405653940', 'StreetAddress': '1112 DALLAS DR STE 4000', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'TX13', 'ORG_UEI_NUM': 'G47WN1XZNWX9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH TEXAS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of North Texas', 'CityName': 'DENTON', 'StateCode': 'TX', 'ZipCode': '762051132', 'StreetAddress': '1112 DALLAS DR STE 4000', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'TX13'}

{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437481.xml'}

Collaborative Research: Conference: NSF Computer and Information Science and Engineering Research Expansion Program (CISE MSI) 2024-2026 Aspiring Principal Investigators Workshop

NSF

08/01/2024

07/31/2026

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'James Fowler', 'PO_EMAI': 'jafowler@nsf.gov', 'PO_PHON': '7032928910'}

Many minority-serving institutions (MSIs) encounter challenges to establishing and maintaining a robust research enterprise, including a lack of training in proposal writing, difficulties in starting research partnerships, and limited involvement of MSI students in research endeavors. To address these obstacles, this project will organize four workshops to aimed at training aspiring principal investigators (PIs) from MSIs in the southern and southeastern US states, preparing participants for submitting proposals to the CISE MSI program in the 2025 and 2026 competitions. The events will provide a platform for participants to meet at large, share research insights, identify challenges and opportunities, and initiate potential research collaborations. Broader-impact aspects of the project comprise the broadening participation of over 60 MSI scholars as well as the fostering of MSI collaborations across nine US states.<br/><br/>The workshops will pursue four major objectives: 1) Community building - the strengthening of relationships among data science (DS), artificial intelligence (AI), and extended reality (XR) to boost broader data-intensive research communities at MSIs; 2) Cross-learning: the facilitating of knowledge sharing, the exchanging of best practices, and the training of aspiring PIs from MSIs to leverage success and enhance proposal development skills; 3) Mentoring - the providing of each research team with experienced coaching; 4) Collaboration development - the fostering of new collaborations, the exploring of future opportunities to advance research initiatives, and the preparing of collaborative proposals towards CISE MSI-focused programs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/31/2024

07/31/2024

None

Grant

47.070

1

4900

4900

2437482

{'FirstName': 'Peter', 'LastName': 'Clarke', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Peter J Clarke', 'EmailAddress': 'clarkep@cis.fiu.edu', 'NSF_ID': '000095234', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Florida International University', 'CityName': 'MIAMI', 'ZipCode': '331992516', 'PhoneNumber': '3053482494', 'StreetAddress': '11200 SW 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'FL26', 'ORG_UEI_NUM': 'Q3KCVK5S9CP1', 'ORG_LGL_BUS_NAME': 'FLORIDA INTERNATIONAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'Q3KCVK5S9CP1'}

{'Name': 'Florida International University', 'CityName': 'MIAMI', 'StateCode': 'FL', 'ZipCode': '331992516', 'StreetAddress': '11200 SW 8TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'FL26'}

{'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}

2024~99994

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437482.xml'}

EAGER: RDSV: Visioning Design Evolution for Human-Robot Interaction

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Mitra Basu', 'PO_EMAI': 'mbasu@nsf.gov', 'PO_PHON': '7032928649'}

The field of Human-Robot Interaction covers the design, hardware fabrication, and algorithm development of robots that interact with people in personal and public spaces. Examples of these interactions are robot tutors in schools and robots that support older adults aging in their homes. This type of technology requires careful design of robot embodiment (i.e., the ‘look’ and ‘feel’ of a robot), their behaviors (e.g., what the robot says and does), and their interaction with people (e.g., the role it is created to embody). This is a highly complex problem that only recently has received attention in the field of Human-Robot Interaction. This project aims to create the future vision for the field of Design applied to Human-Robot Interaction with four different activities, organized within a series of design visioning meetings ("Design Retreat") that will be attended by academic and industry experts in Design Research and Human-Robot Interaction. The first activity will use metaphors to create new ideas of robot design that go beyond existing roles that robots have in today’s society; the second activity will create storyboards that describe in more detail ideas of robot interactions in society, such as their role, how they should interact with humans, and what humans should expect from robots; the third activity will identify existing resources in the scientific community that can support the consolidation of the ideas generated in the previous activities; the fourth and final activity will map out milestones about specific steps to turn the ideas derived from the activities into reality. The research team will disseminate the educational knowledge about this topic by making a documentary of the Design Retreat, giving lectures in traditionally underrepresented schools and populations, and sharing a website that supports communities in engaging in design visioning around novel and emergent technologies.<br/> <br/>“Design for Human-Robot Interaction” is the area of work within Human-Robot Interaction (HRI) that embodies design work. This area has the potential for high impact in robotics and HRI fields as it incorporates diverse methods to build robots, with most methods being human-centric and accounting for human values. However, the potential of Design for HRI has not been fully realized and outlined in the field. There are several reasons behind this challenge, such as the lack of consensus on what Design for HRI means, what methods should be used, and how design work should be evaluated. The research team believes that envisioning a future for Design in HRI can further scope promising new directions that not only provide a consensus on the meaning of Design for HRI, but also develop engagement with societal impact in the field. The research team will lead a Design Retreat to gather the HRI Design community, including academia and industry experts in design, and map out the future of Design for HRI through visioning activities. The Design Retreat will have the four Visioning Workshops to support participants in imagining and building the future of Design for HRI. The main outcomes of this project are scientific community building, the generation of the “Interdisciplinary Technology Visioning Toolkit” that will be released in open-access, a documentary with the highlights of the Design Retreat to proliferate education on this topic, and scientific publications in relevant areas including HRI and Human-Computer Interaction.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.070

1

4900

4900

2437503

{'FirstName': 'Patricia', 'LastName': 'Alves-Oliveira', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia Alves-Oliveira', 'EmailAddress': 'robopati@umich.edu', 'NSF_ID': '000861944', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}

{'Code': '164000', 'Text': 'Information Technology Researc'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437503.xml'}

CAREER: Determining how flow of polluted water impacts antibiotic resistance in soils

NSF

06/01/2024

05/31/2029

{'Value': 'Continuing Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Karl Rockne', 'PO_EMAI': 'krockne@nsf.gov', 'PO_PHON': '7032927293'}

Antibiotics provide a textbook example of biologically active chemicals that can impact human, animal, and ecosystem health. In soils, many bacterial strains carry genes that encode for antibiotic resistance (AR). The use of treated wastewater for irrigation has emerged as an important source of antibiotics in soils. In agriculture fields irrigated with treated wastewater, previous studies have found that antibiotics are frequently detected in soils. In addition, some studies have reported that irrigation intensity and the occurrence of AR markers in irrigation water are correlated to the abundance of those markers in soils. However, a fundamental understanding of the fate, transport, and reactivity of antibiotics in agricultural soils during irrigation with treated/polluted wastewater has remained elusive. The overarching goal of this CAREER project is to advance the fundamental understanding of the reactive transport processes that occur during the infiltration of antibiotic-polluted water and their impact on the levels of AR bacteria in agricultural soils. To advance this goal, the Principal Investigator proposes to test the hypothesis that changes in the abundance and persistence of AR bacteria in agricultural soils are directly linked to the physicochemical interactions between soils and antibiotics during the infiltration of treated/polluted irrigation wastewater. The successful completion of this project will benefit society through the generation of new fundamental knowledge on how soils function as natural filters that accumulate and/or degrade antibiotic pollutants and control their availability to soil micro-organisms. Additional benefits to society will be achieved through student education and training including the mentoring of two graduate students and one undergraduate student at Texas A&M University.<br/><br/>Antibiotic pollutants are a group of chemicals that infiltrate through soils during irrigation when treated wastewater is used as alternative to address water scarcity in agriculture. Despite the importance of soils in assimilating antibiotic pollution, little is known about how the flow of antibiotic-polluted water impacts the spread and persistence of antibiotic resistance (AR) in soils during irrigation. This CAREER project will address these critical knowledge gaps through the integration of field investigations, bench scale lab experiments, and process-based modeling. The specific objectives of the research are to (1) identify the factors that control the persistence of antibiotics and the amplification of AR markers in soils irrigated with treated wastewater, (2) identify and quantify the soil-antibiotic interactions that induce persistence and horizontal transfer of AR genes among soil bacteria, and (3) elucidate key reactive processes controlling the amplification of AR in soils that receive a mix of antibiotics and AR bacteria in polluted water. The successful completion of this project has the potential for transformative impact through the generation of new data and fundamental knowledge about the AR attenuation capacity of soil ecosystems under the continuous infiltration of antibiotic polluted wastewater. To implement the educational and mentoring goals of this CAREER project, the Principal Investigator proposes (PI) to leverage existing programs and resources at Texas A&M University to (i) engage students in the design, implementation, and deployment of a human-like dynamic conversation interface (educational chatbot), and (ii) use the educational chatbot to promote interactive communication between virtual STEM scholars and K-12 student audiences. The PI plans to build upon these educational activities to design and implement new pedagogical frameworks that foster equal participation and a sense of belonging among all students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/15/2024

07/15/2024

None

Grant

47.041

1

4900

4900

2437540

{'FirstName': 'Itza', 'LastName': 'Mendoza-Sanchez', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Itza Mendoza-Sanchez', 'EmailAddress': 'itzamendoza@tamu.edu', 'NSF_ID': '000733996', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'ZipCode': '778433124', 'PhoneNumber': '9798626777', 'StreetAddress': '3124 TAMU', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'QD1MX6N5YTN4', 'ORG_LGL_BUS_NAME': 'TEXAS A&M ENGINEERING EXPERIMENT STATION', 'ORG_PRNT_UEI_NUM': 'QD1MX6N5YTN4'}

{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'StateCode': 'TX', 'ZipCode': '778433124', 'StreetAddress': '3124 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}

{'Code': '144000', 'Text': 'EnvE-Environmental Engineering'}

2024~439974

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437540.xml'}

Planning: CRISES: Catastrophic Risks and System-Level Governance

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Floods, fires, pandemics and other catastrophic risks are a major worldwide concern in the light of climate change, urbanization, and an increasingly complex and interconnected world. These risks are challenging to prevent and manage because they tend to have impacts that cascade in surprising and unexpected ways across communities, political jurisdictions and economic sectors. To address this challenge in a sustainable and equitable way, risk-prone regions must take account of the complex interdependence of infrastructures, organizations and communities operating at different levels and scales of governance. This project develops a strategy of collaborative catastrophic risk modeling to help risk-prone regions collectively recognize, understand, and hopefully act upon their interdependence. A range of approaches have been used to model catastrophic risk. This project is distinctive in that it aims to demonstrate how these models can be developed in collaboration with regional stakeholders. A collaborative approach is expected to both increase the practical relevance of risk models and enhance regional efforts to address catastrophic risks. <br/><br/>Catastrophic risk management poses a fundamental challenge: the difficulty of dampening down escalating events or spillover effects from one part of a system to another. This challenge has been referred to as the problem of “cascading risks,” which have been observed to occur in electrical blackouts, infectious disease outbreaks, extreme weather events, natural hazard spillovers into industrial failures, landslides, and floods. Although this challenge is gaining increasing recognition, there is still limited understanding of how risk-prone regions can be encouraged to work together to prevent and manage these cascading interactions. This project develops a methodology of collaborative risk modeling to bring regional stakeholders together to identify and analyze catastrophic risks. While already a recognized tool for analyzing the dynamic nature of cascading risks, catastrophic risk modeling has not previously been used as framework to advance system-scale governance, a concept that acknowledges that risk reduction for large-scale hazard events necessarily occurs at micro-, meso- and macro-scales and includes public, private and nonprofit stakeholders working together A methodology of collaborative risk modeling not only provides valuable input into the development of useful models, but also creates an opportunity for regional stakeholders--particularly vulnerable communities–to collectively perceive and address regional risks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437579

[{'FirstName': 'Louise', 'LastName': 'Comfort', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Louise K Comfort', 'EmailAddress': 'lkc@pitt.edu', 'NSF_ID': '000200087', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Christopher', 'LastName': 'Ansell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher Ansell', 'EmailAddress': 'cansell@berkeley.edu', 'NSF_ID': '000501352', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~99721

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437579.xml'}

EAGER: RDSV: Enhancing Visioning Impacts on Computing Research

NSF

10/01/2024

12/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Mitra Basu', 'PO_EMAI': 'mbasu@nsf.gov', 'PO_PHON': '7032928649'}

Visioning is used by the research communities to identify and shape high-impact research directions, opportunities, and initiatives. This project brings together scientific and technical thought leaders and experienced research program managers to examine and discuss effective strategic planning and visioning in long-range research. A mix of invited talks, panel conversations, and breakout discussions will be used to explore these questions. A workshop summary report will be prepared to capture key points and make them available widely in the computing research community. An online event will be used to present workshop results and discuss them with the audience.<br/><br/>This project explores research visioning, i.e., processes for identifying and shaping future high-impact research directions, opportunities, and initiatives. The workshop addresses such topics as which types of activities are best suited to achieve particular goals, effective charters for visioning participants, how to select appropriate participants, balancing feasibility with high-risk, high-reward initiatives, and evaluating the success of visioning activities. Outcomes include documenting a range of visioning activities, identifying factors leading to successful and impactful visioning efforts, capturing best practices for different types of visioning activities, suggesting potential new visioning models, identifying further work that could help advance community visioning efforts, and identifying which approaches and processes best address technology and societal factors that affect the realization of a vision. Workshop sessions are in the form of invited talks, panel conversations, and breakout discussions. Session topics cover high level assessment and analysis of different visioning mechanisms as well as deep diving into specific programs and outcomes. The virtual report launch event includes a presentation of the workshop summary by planning committee members and discussion with the audience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.070

1

4900

4900

2437581

{'FirstName': 'Jon', 'LastName': 'Eisenberg', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jon K Eisenberg', 'EmailAddress': 'jeisenbe@nas.edu', 'NSF_ID': '000064760', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'National Academy of Sciences', 'CityName': 'WASHINGTON', 'ZipCode': '204180007', 'PhoneNumber': '2023342254', 'StreetAddress': '2101 CONSTITUTION AVE NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'PKFJZHG2MLG9', 'ORG_LGL_BUS_NAME': 'NATIONAL ACADEMY OF SCIENCES', 'ORG_PRNT_UEI_NUM': 'PKFJZHG2MLG9'}

{'Name': 'National Academy of Sciences', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '204180007', 'StreetAddress': '2101 CONSTITUTION AVE NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '164000', 'Text': 'Information Technology Researc'}

2024~297574

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437581.xml'}

OPP-PRF: A Well-Constrained Hosing Experiment for Interrogating Arctic Precipitation Changes in the Younger Dryas

NSF

08/15/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '06090100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OPP', 'LongName': 'Office of Polar Programs (OPP)'}}

{'SignBlockName': 'Lauren Culler', 'PO_EMAI': 'lculler@nsf.gov', 'PO_PHON': '7032928057'}

In the next century, changes to precipitation will be among the most significant impacts of anthropogenic climate change. An important tool for predicting future climate change is understanding how climate has changed in the past. About 12,000 years ago, a significant volume of cold, fresh water was added to the North Atlantic. This fresh water is believed to have slowed the Atlantic Meridional Overturning Circulation, an ocean current that is important to the stability of the planet’s climate. Using the results of high-resolution computer simulations of iceberg paths through the ocean, this research will test the hypothesis that icebergs were the primary contributor of fresh water to the Atlantic during the Younger Dryas. This hypothesis will be tested against the idea that the fresh water was sourced from a catastrophic outburst flood on land, as well as against a more traditional, low-resolution model of fresh water forcing. These simulations will be compared to each other and to records of Arctic precipitation change during the Younger Dryas, advancing understanding of both past and present climate change in the Arctic. <br/><br/>This research investigates the Younger Dryas, an interval of abrupt global climate change that occurred about 12,000 years ago. The Younger Dryas is believed to have been caused by the addition of cold, fresh water to the North Atlantic, which slowed Atlantic Meridional Overturning Circulation, though the exact nature of this forcing is not well understood. This work involves sensitivity experiments using an isotope-enabled global climate model, iCESM, with new constraints on the location of fresh water. The PI hypothesizes these more realistic constraints will produce a climate response more comparable to the geologic record than past works. These experiments will investigate the initiation and duration of these events in order to generate a more complete narrative of abrupt climate change in the Younger Dryas. The results of this modeling will then be compared to proxy records from Arctic lakes, interpreted through forward-modeling of the systems recording the proxies, or proxy system modeling. This approach, involving global climate modeling, proxy records, and proxy system modeling of the same event will produce a narrative of Younger Dryas climate dynamics and link those events to sediments from Arctic lakes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/14/2024

08/14/2024

None

Grant

47.078

1

4900

4900

2437583

{'FirstName': 'Michaela', 'LastName': 'Fendrock', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michaela Fendrock', 'EmailAddress': 'michaela.fendrock@gmail.com', 'NSF_ID': '000874563', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Alfred University', 'CityName': 'ALFRED', 'ZipCode': '148021205', 'PhoneNumber': '6078712026', 'StreetAddress': '1 SAXON DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '23', 'CONGRESS_DISTRICT_ORG': 'NY23', 'ORG_UEI_NUM': 'J1B5PBG573T1', 'ORG_LGL_BUS_NAME': 'ALFRED UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Alfred University', 'CityName': 'ALFRED', 'StateCode': 'NY', 'ZipCode': '148021205', 'StreetAddress': '1 SAXON DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '23', 'CONGRESS_DISTRICT_PERF': 'NY23'}

{'Code': '524700', 'Text': 'POST DOC/TRAVEL'}

2022~177641

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437583.xml'}

Conference: 2024 International Conference on CRISPR Technologies

NSF

08/01/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Anthony Garza', 'PO_EMAI': 'aggarza@nsf.gov', 'PO_PHON': '7032922489'}

The 2024 International Conference on CRISPR Technologies (ICCT) will focus on the latest advances in CRISPR technologies and applications, bringing together key stakeholders from academia and industry who have aligned interests. The conference program features talks on a variety CRISPR-related subjects, including AI, genomics and gene editing tools, beyond double stranded breaks, CRISPR in the dark genome, and natural biology of CRISPR systems. The conference covers a broad range of research areas and applications of CRISPR technology, which creates a unique environment for people with diverse expertise to gather and exchange information. Additionally, the conference aims to give students and early career professionals opportunities to share their work, to network with the foremost leaders in the field, and to develop their careers. <br/><br/>The field of genome editing with CRISPR technologies is one of the fastest growing and highest impact areas of modern research, with applications in agriculture, ecology and medicine. The 2024 International Conference on CRISPR Technologies (ICCT) will bring together biologists, chemists, and engineers to discuss CRISPR’s ability to address fundamental and applied problems. The sessions feature a broad range of emerging technologies and a diverse set of topics that will impact the next decade of research. ICCT is designed to bring together researchers and experts from academia, government and industry in a highly interactive and engaging meeting. Early career and established researchers will have opportunities to interact during organized talks, poster sessions, panels, and many informal gatherings. This platform will allow established and early career scientists to discuss challenges in the field and to establish collaborations to address these challenges.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.074

1

4900

4900

2437587

{'FirstName': 'Evan', 'LastName': 'Flach', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan Flach', 'EmailAddress': 'evanf@aiche.org', 'NSF_ID': '000662136', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'ZipCode': '100055991', 'PhoneNumber': '6464951350', 'StreetAddress': '120 WALL ST', 'StreetAddress2': '23 FLO', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'KLPNCLPDAS45', 'ORG_LGL_BUS_NAME': 'AMERICAN INSTITUTE OF CHEMICAL ENGINEERS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100055991', 'StreetAddress': '120 WALL ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

{'Code': '801100', 'Text': 'Systems and Synthetic Biology'}

2024~19900

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437587.xml'}

Conference: US-Southeast Asia Regional Workshop on Responsible Artificial Intelligence

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Vladimir Pavlovic', 'PO_EMAI': 'vpavlovi@nsf.gov', 'PO_PHON': '7032928318'}

This workshop, set to take place in the spring 2025, at the National University of Singapore, aims to bring together approximately 50 artificial intelligence (AI) experts from the United States (US) and Southeast Asian nations (including Singapore, Malaysia, India, Vietnam, Indonesia, and Thailand). The objective is to facilitate discussions on enhancing collaboration in responsible AI research between Southeast Asia and the US. This interactive workshop will focus on: (1) identifying research gaps and opportunities in responsible AI research across countries to promote potential collaboration between Southeast Asia and the US; and, (2) discussing responsible, use-inspired foundational AI development that can serve in providing crucial elements of future economic development and societal well-being. <br/><br/>The multinational workshop will be held at the National University of Singapore (NUS), a globally recognized institution with a strong commitment to fostering advancements in AI. Key members of the workshop steering committee include leadership and faculty from NUS and Nanyang Institute of Technology, as well as members of industry and government. Insights from the workshop discussions will be captured in a white paper which will include the essential takeaways from the event, providing: (i) a snapshot of the collective knowledge and (ii) recommendations for future directions of research collaboration between US and the Southeast Asian countries in the field of responsible AI. <br/><br/>The workshop project is co-funded by the Division of Information and Intelligent Systems (IIS) within the Directorate for Computer and Information Science and Engineering (CISE) and the Office of International Science and Engineering at NSF.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/30/2024

07/30/2024

None

Grant

47.070, 47.079

1

4900

4900

2437592

{'FirstName': 'Junsong', 'LastName': 'Yuan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Junsong Yuan', 'EmailAddress': 'jsyuan@buffalo.edu', 'NSF_ID': '000791552', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'ZipCode': '142282577', 'PhoneNumber': '7166452634', 'StreetAddress': '520 LEE ENTRANCE STE 211', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'NY26', 'ORG_UEI_NUM': 'LMCJKRFW5R81', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}

{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'StateCode': 'NY', 'ZipCode': '142602500', 'StreetAddress': '338H Davis Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'NY26'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '748400', 'Text': 'IIS Special Projects'}]

2024~99941

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437592.xml'}

Conference: 23rd Annual Symposium of the NSF Astronomy and Astrophysics Postdoctoral Fellows

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '03020000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'AST', 'LongName': 'Division Of Astronomical Sciences'}}

{'SignBlockName': 'Hans Krimm', 'PO_EMAI': 'hkrimm@nsf.gov', 'PO_PHON': '7032922761'}

The 23rd Annual Symposium of the NSF Astronomy and Astrophysics Postdoctoral Fellows (AAPF) will be held on 11–12 January 2025 alongside the 245th meeting of the American Astronomical Society (AAS) in National Harbor, MD, near Washington, DC. The NSF AAPF program aims to prepare postdoctoral fellows for their future scientific careers by integrating research and teaching/outreach. The annual symposium provides: (1) a platform for fellows to discuss their research and broader impacts projects, (2) exposure for the fellows and the fellowship program within the astronomical community, and (3) an open discussion of issues that are important to astronomers as they begin their careers. The symposium will achieve broader impacts by facilitating collaborations between NSF AAPF fellows on both research and education, and by increasing the exposure of the fellows and the fellowship program within the astronomical community.<br/><br/>The AAPF symposium will consist of (1) talks by current NSF AAPF fellows on their research and education projects, (2) a keynote science talk focused on the efforts to deal with the influx of big data from modern large surveys in astronomy, (3) a keynote outreach talk on starting and building a successful outreach program. (4) a workshop on navigating the academic job market, (5) a workshop on crafting an engaging story that communicates scientific results, and (6) opportunities for open discussion between current NSF AAPF fellows and the broader astronomical community to foster opportunities for mentoring and new collaborations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/01/2024

08/01/2024

None

Grant

47.049

1

4900

4900

2437597

[{'FirstName': 'Jorge', 'LastName': 'Moreno', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jorge Moreno', 'EmailAddress': 'jorge.morenosoto@pomona.edu', 'NSF_ID': '000681370', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Francisco', 'LastName': 'Mercado', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Francisco J Mercado', 'EmailAddress': 'mercadojfrancisco1@gmail.com', 'NSF_ID': '000882449', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Pomona College', 'CityName': 'CLAREMONT', 'ZipCode': '917114434', 'PhoneNumber': '9096218328', 'StreetAddress': '550 N COLLEGE AVE # 244', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_ORG': 'CA28', 'ORG_UEI_NUM': 'Q9VBQSV2CBY5', 'ORG_LGL_BUS_NAME': 'POMONA COLLEGE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Pomona College', 'CityName': 'CLAREMONT', 'StateCode': 'CA', 'ZipCode': '917114434', 'StreetAddress': '550 N COLLEGE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_PERF': 'CA28'}

{'Code': '121900', 'Text': 'SPECIAL PROGRAMS IN ASTRONOMY'}

2024~49990

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437597.xml'}

Planning: CRISES: A Community-Centered Laboratory for the Research and Design of Socially Astute Epidemic Readiness and Response

NSF

01/01/2025

12/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

Hard-to-manage outbreaks of infectious disease are emerging more frequently, and the U.S. requires public health systems that protect populations against the adverse social, economic, political, psychological and physical impacts. This project involves planning for a future academic research center that blends the social and biological sciences with community knowledge to understand and to promote epidemic control strategies that affected communities consider appropriate in terms of core values, feasibility, fairness, and health benefits. Public health experts, a range of social scientists, and community stakeholders will together explore the organizing question, “What infrastructure – including financing, organizations, personnel, processes, and practices – supports epidemic interventions that address the social norms, cultural values, language needs, economic realities, local knowledge, and active participation of socially vulnerable populations?”<br/><br/>With hard-to-manage outbreaks of infectious disease emerging more frequently, the U.S. requires systems that protect populations against adverse social, economic, political, psychological and physical impacts. This project constitutes planning for an academic research center that partners with community stakeholders to advance the understanding, design, and implementation of human-centered infrastructure at the community/public health interface which supports “socially astute” epidemic management. Socially astute describes those epidemic controls that affected communities consider appropriate in terms of core values, feasibility, evenhandedness, and health benefits. The planning activities posit a synthesis between the social and the biological, between problem-solving experts and those who experience the problem in the contexts of their everyday lives. Combining human-centered systems thinking with a community-based participatory research approach, the project asks, “What infrastructure – including social milieu, financing, organizations, personnel, processes, and practices – underpins epidemic interventions that adequately address the social norms, cultural values, language needs, economic realities, local knowledge, and active participation of socially vulnerable populations?” Objectives for a series of planning workshops and community stakeholder consultations are: (1) develop a systems map for socially astute epidemic management infrastructure, including an over-arching narrative and visual depiction; (2) build a “living document” research agenda to propel the research center; and (3) draft an organizational management plan that addresses the center’s human capital needs, trajectory of fundamental and use-inspired research, operationalization of community collaboration, and the translation of research into curricula, internships, trainings, and briefings.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.075

1

4900

4900

2437610

[{'FirstName': 'Monica', 'LastName': 'Schoch-Spana', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Monica Schoch-Spana', 'EmailAddress': 'mschoch@jhu.edu', 'NSF_ID': '000368744', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Stephanie', 'LastName': 'McClure', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephanie M McClure', 'EmailAddress': 'smcclur1@ua.edu', 'NSF_ID': '000346915', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Stephen', 'LastName': 'Thomas', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephen B Thomas', 'EmailAddress': 'sbt@umd.edu', 'NSF_ID': '0000A0GR5', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Noe', 'LastName': 'Crespo', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Noe C Crespo', 'EmailAddress': 'ncrespo@sdsu.edu', 'NSF_ID': '0000A0GYG', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'ZipCode': '212182608', 'PhoneNumber': '4439971898', 'StreetAddress': '3400 N CHARLES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMTDMBR29C7', 'ORG_LGL_BUS_NAME': 'THE JOHNS HOPKINS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212182608', 'StreetAddress': '3400 N CHARLES ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437610.xml'}

Planning: CRISES: Human-Centered Action Research to Disrupt Trafficking (HART)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

Human trafficking is a human rights abuse that negatively affects individuals, families and communities worldwide, including within the United States. Yet, despite continued efforts by researchers and practitioners in the field, there remain substantial gaps in knowledge on how to effectively prevent, disrupt, and dismantle human trafficking and remediate the harms human trafficking causes. What the field needs is large-scale and nuanced research on the interconnections between individuals, trafficking operations, the wide range of commercial sex market segments, community contexts, and root causes. This planning grant brings together a diverse group, including researchers from multiple disciplines, human trafficking survivor-leaders, and other stakeholders (e.g., service providers and law enforcement), to develop a national-level action research center and build a transdisciplinary team capable of carrying out this long-term research agenda. Participants will co-create a plan for building, organizing, and sustaining a new research center called “Human-Centered Action Research to Disrupt Trafficking (HART).”<br/><br/>The planning approach for the HART Center uses a novel scientific approach to design a research agenda by converging social sciences, health sciences, and computational modeling with lived expertise from survivors of trafficking and other key stakeholders. The transdisciplinary team has a national scope with expertise to capture the realities and nuances of a broad range of trafficking contexts ethically and accurately and to translate that research to practice. This deep collaboration provides a realistic ground-truth for the direction and scale of research questions. It also enables identification and avoidance of unintended negative consequences that too often arise from human trafficking research and prevention and intervention efforts. Harms to avoid include, among other things, re-traumatizing survivors through invasive research surveys and interviews, over-focusing on some contexts leading to skewed results, inadvertently arresting victims in law enforcement interventions, and wasting resources on well-meaning, but ultimately ineffective strategies. The planning approach equalizes the playing field among participants with a carefully managed process that attends to power differentials, builds trust, and fosters shared understanding among people with diverse experience and perspectives. Methods for planning use cutting-edge strategies for team building, appreciative inquiry, and participatory collaboration through a series of interactive remote meetings culminating in an in-person convening. The results of the planning process are threefold: 1) develop shared values and research philosophy for the HART center; 2) identify key human trafficking research thrusts; and 3) build a team and project plan to address these thrusts that focus on the complex social, legal, economic, and human rights challenges of human trafficking.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437620

[{'FirstName': 'Kayse', 'LastName': 'Maass', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kayse L Maass', 'EmailAddress': 'k.maass@northeastern.edu', 'NSF_ID': '000779223', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lauren', 'LastName': 'Martin', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lauren E Martin', 'EmailAddress': 'Mart2114@umn.edu', 'NSF_ID': '000779583', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Kelle', 'LastName': 'Barrick', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kelle Barrick', 'EmailAddress': 'kbarrick@rti.org', 'NSF_ID': '000595724', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Thomas', 'LastName': 'Sharkey', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas Sharkey', 'EmailAddress': 'tcshark@clemson.edu', 'NSF_ID': '000526318', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Regents of the University of Minnesota', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554550353', 'StreetAddress': '5-140 Weaver-Densford Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437620.xml'}

EAGER: A Domain-Informed Generative Framework for Joint Learning of Public Medical Knowledge and Individual Health Records

NSF

10/01/2024

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Christopher Yang', 'PO_EMAI': 'ccyang@nsf.gov', 'PO_PHON': '7032928111'}

Access to comprehensive knowledge about diseases, conditions, and medications is not only empowering but also essential for the public to understand complex medical information, leading to better personal well-being. However, current medical information sources, such as Google Knowledge Graph, often have limited scope, primarily covering a small subset of well-known diseases. Public data sources like academic papers on uncommon diseases are not well-structured or easily understood by the general public. This project aims to create a flexible and open-resource medical knowledge base called FORMED, providing multi-faceted information on a wide range of diseases and conditions for public access. This knowledge base will include well-structured sections on symptoms, causes, and treatments, enabling efficient disease classification and indexing. By integrating medical knowledge with individual health records, the project will also evaluate its effectiveness in predicting individual health risks for uncommon diseases. Additionally, this project will involve educational initiatives such as developing new courses on large language models; conducting interdisciplinary research activities to train graduate, undergraduate, and high-school students in data science and bioinformatics; and increasing participation of women and minority groups in academic research. All core outcomes of this project, including software, datasets, and publications, will be made available to the general public.<br/><br/><br/>The goal of this project is twofold: (1) to create a public-oriented medical knowledge base called FORMED, covering a wide range of diseases, conditions, and medications in the current disease classification system with descriptive attributes including symptoms, causes, and treatments; and (2) to develop a temporal health outcome prediction and generation framework to evaluate the generated knowledge base with individual health records. This project creates a set of technologies for semi-structured text generation, knowledge graph construction, and mixed-structure temporal data prediction as well as generation. Specifically, the research activities include: (1) Developing hyperbolic embedding-enhanced domain-specific large language models for building FORMED; (2) Constructing a knowledge graph from FORMED to represent the logical concepts of disease characteristics and causes; (3) Designing novel learning and prompting strategies to augment the reasoning capability of large language models with knowledge graphs; and (4) Building a robust testing platform to evaluate the effectiveness of the generated knowledge graph for forecasting individual health risks. The establishment of comprehensive medical knowledge bases will significantly enhance public understanding of uncommon diseases and improve the inference capabilities of generative models, enabling searching-based services. Research outcomes of this project will be disseminated in peer-reviewed publications, tutorials, seminars, and workshops.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.070

1

4900

4900

2437621

{'FirstName': 'Yue', 'LastName': 'Ning', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yue Ning', 'EmailAddress': 'yue.ning@stevens.edu', 'NSF_ID': '000791052', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Stevens Institute of Technology', 'CityName': 'HOBOKEN', 'ZipCode': '07030', 'PhoneNumber': '2012168762', 'StreetAddress': '1 CASTLEPOINT ON HUDSON', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'NJ08', 'ORG_UEI_NUM': 'JJ6CN5Y5A2R5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF THE STEVENS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Stevens Institute of Technology', 'CityName': 'HOBOKEN', 'StateCode': 'NJ', 'ZipCode': '070305906', 'StreetAddress': '1 CASTLEPOINT ON HUDSON', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'NJ08'}

{'Code': '736400', 'Text': 'Info Integration & Informatics'}

2024~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437621.xml'}

NSF-SNSF: Revealing the mechanisms of thylakoid biogenesis at the base of the green lineage

NSF

08/01/2024

07/31/2028

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Richard Cyr', 'PO_EMAI': 'rcyr@nsf.gov', 'PO_PHON': '7032928440'}

Most life on Earth depends on biomass and oxygen derived from photosynthetic organisms. Photosynthesis in plants and algae is performed by an organelle called the chloroplast. Inside the chloroplast, thylakoid membranes embed the photosynthetic protein complexes, which drive the light-dependent reactions of photosynthesis. Thylakoids are one of the most complex and organized membrane networks in nature. However, it is poorly understood how thylakoid membranes form and organize into their intricate architecture. In this project, the investigators have assembled an international team with a unique combination of innovative biological systems and revolutionary imaging technology to gain new insights into the fundamentals of thylakoid biogenesis in green algae. Because green algae are at the base of the green lineage on the Tree of Life, and photosynthesis and thylakoids are generally conserved, the research has broad implications for both algae and land plants. Broader impacts of this research include the intrinsic merit of understanding the fundamental biology that supports life on Earth, and the knowledge gained is likely to benefit applied projects such as improving production of crops, biofuels and bioproducts. This project provides opportunities for academic learning, including interdisciplinary training bridging cell biology, biochemistry, molecular genetics, bioinformatics, quantitative imaging, and advanced microscopy. Additional activities involve public engagement and open access of data, methods, and publications.<br/><br/>While thylakoid membranes are central to photosynthesis, it remains unknown not only how thylakoid membranes form and organize, but also how, when, and where they are populated with photosynthetic complexes. Recently, the Roth group (Berkeley, USA) has established a rapid, controllable switch that enables cells to turn on/off photosynthesis and induce thylakoid biogenesis (a process called “greening”) in evolutionarily distant green algae. The Engel group (Basel, Switzerland) has established a cutting-edge cryo-electron tomography (cryo-ET) workflow to visualize native thylakoid membranes inside cells with the resolution to localize individual photosynthetic complexes. Combining the inducible algal systems with cryo-ET will provide an unprecedented time-resolved molecular view into the events of thylakoid biogenesis. In this project, the investigators will 1) map the stepwise events that establish thylakoid architecture and molecular organization, 2) use molecular genetics to determine and dissect roles of known thylakoid membrane remodeling proteins during thylakoid biogenesis, and 3) discover and define roles of novel candidate genes involved in thylakoid biogenesis by combining multi-omics, bioinformatics, molecular genetics, and a multidisciplinary set of analyses. The overarching goal of the collaborative research is to develop a mechanistic model of how thylakoid membranes are built, shaped into complex architecture, and precisely organized with newly assembled photosynthetic machinery.<br/><br/>This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland. Funds for the US side come from the Office of International Science and Engineering, the Biological Directorate, and the Division of Molecular and Cellular Biosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/06/2024

08/06/2024

None

Grant

47.074, 47.079

1

4900

4900

2437623

{'FirstName': 'Melissa', 'LastName': 'Roth', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Melissa S Roth', 'EmailAddress': 'mroth@berkeley.edu', 'NSF_ID': '0000A0G6V', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'The Regents of the University of California', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '111400', 'Text': 'Cellular Dynamics and Function'}, {'Code': '727500', 'Text': 'Cross-BIO Activities'}]

2024~1154987

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437623.xml'}

Conference: 2024 International Conference on Microbiome Engineering

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Anthony Garza', 'PO_EMAI': 'aggarza@nsf.gov', 'PO_PHON': '7032922489'}

The 2024 International Conference on Microbiome Engineering will focus on the latest advances in microbiome research tools, microbiome biology and microbiome engineering applications, bringing together key stakeholders from academia and industry who have aligned interests. The conference program features talks on a variety microbiome engineering-related subjects, including the latest tools for engineering individual and groups of microbes, engineering animal microbiome systems, engineering plant and soil microbiome systems, and the underlying science of microbial dynamics in microbiomes. The conference covers a broad range of research areas and applications of microbiome engineering, which creates a unique environment for people with diverse expertise to gather and exchange information. Additionally, the conference aims to give students and early career professionals opportunities to share their work, to network with the foremost leaders in the field, and to develop their careers. <br/><br/>The field of microbiome engineering is one of the fastest growing and highest impact areas of modern research, with applications in agriculture, ecology and medicine. The 2024 International Conference on Microbiome Engineering will bring together biologists, chemists, and engineers to discuss the ability of microbiome research to address fundamental and applied problems. The sessions feature a broad range of emerging technologies and a diverse set of topics that will impact the next decade of research. The conference is designed to bring together researchers and experts from academia, government and industry in a highly interactive and engaging meeting. Early career and established researchers will have opportunities to interact during organized talks, poster sessions, panels, and many informal gatherings. This platform will allow established and early career scientists to discuss challenges in the field and to establish collaborations to address these challenges.<br/><br/>This conference has been co-funded by the Cellular and Biochemical Engineering Program in the Division of Chemical, Bioengineering, Environmental and Transport Systems, and the Systems and Synthetic Biology Program in the Division of Molecular and Cellular Biosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/26/2024

07/26/2024

None

Grant

47.041, 47.074

1

4900

4900

2437626

{'FirstName': 'Evan', 'LastName': 'Flach', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan Flach', 'EmailAddress': 'evanf@aiche.org', 'NSF_ID': '000662136', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'ZipCode': '100055991', 'PhoneNumber': '6464951350', 'StreetAddress': '120 WALL ST', 'StreetAddress2': '23 FLO', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'KLPNCLPDAS45', 'ORG_LGL_BUS_NAME': 'AMERICAN INSTITUTE OF CHEMICAL ENGINEERS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'American Institute of Chemical Engineers', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100055991', 'StreetAddress': '120 WALL ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

[{'Code': '149100', 'Text': 'Cellular & Biochem Engineering'}, {'Code': '801100', 'Text': 'Systems and Synthetic Biology'}]

2024~47525

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437626.xml'}

Planning: CRISES: CLAIM: The Center for Climate Leadership and AI-driven Integrity and Mitigation

NSF

01/01/2025

12/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

This planning project aims to develop CLAIM: The Center for Climate Leadership and AI-driven Integrity and Mitigation, which seeks to investigate the societal, regulatory and governance implications of private sector climate commitments in the realm of generative Artificial Intelligence (genAI). The PI and team will lead efforts to demystify genAI’s role in climate information to enhance the credibility and integrity of climate actions by researching how it affects trust, policy support and individual behavior. The center will generate education and training opportunities through pilot projects, represent underserved communities, and equip future leaders to navigate AI’s societal implications. More broadly, this project will support climate regulation by providing credible information, distinguishing reliable sources, unlocking new data to assess various actors’ climate impacts, and creating open-source datasets to address data gaps and benefit broader research.<br/><br/>Through an interdisciplinary collaboration that includes social scientists, computer scientists, law and policy experts, and practitioners from various sectors, the project activities will create safeguards, metrics, and institutions to effectively leverage AI for transparency and tracking of climate actions. The planning project focuses on three primary aims: (1) rigorously interrogating genAI models to address information; (2) designing new metrics and benchmarks to evaluate the accuracy and credibility of genAI information regarding climate commitments; and (3) convening specific projects to examine the societal impacts of genAI on corporate climate behavior and governance. During the planning phase, this project will identify and convene stakeholders to conduct a comprehensive gap analysis, address key challenges, assess vulnerabilities, gather insights on real-world impacts, develop robust metrics for evaluating AI-generated content, review policy frameworks, and establish the center’s aims and flagship pilot projects.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437655

{'FirstName': 'Angel', 'LastName': 'Hsu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Angel Hsu', 'EmailAddress': 'angel.hsu@unc.edu', 'NSF_ID': '000769646', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of North Carolina at Chapel Hill', 'CityName': 'CHAPEL HILL', 'ZipCode': '275995023', 'PhoneNumber': '9199663411', 'StreetAddress': '104 AIRPORT DR STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'D3LHU66KBLD5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL', 'ORG_PRNT_UEI_NUM': 'D3LHU66KBLD5'}

{'Name': 'University of North Carolina at Chapel Hill', 'CityName': 'CHAPEL HILL', 'StateCode': 'NC', 'ZipCode': '275995023', 'StreetAddress': '104 AIRPORT DR STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437655.xml'}

SitS: Collaborative Research: Understand and Forecast Long-term Variations of in-situ Geophysical and Geomechanical Characteristics of Degrading Permafrost in the Arctic

NSF

07/01/2024

12/31/2024

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Giovanna Biscontin', 'PO_EMAI': 'gibiscon@nsf.gov', 'PO_PHON': '7032922339'}

Climate change is resulting in warming of the permafrost across the Arctic and sub-Arctic, which results in changes in the geological and mechanical properties of soils. Quantifying the changes in soil properties are critical for both understanding the natural environment and assessing the effects of these changes on the existing and future built infrastructure, both of which have long-lasting societal impacts. This project will embed fiber optic sensing cables into the ground in an Alaskan coastal community. Fiber-optic-sensed signals will be converted into the geological and geomechanical properties of the ground material and then used to quantitatively forecast future impacts on permafrost properties. The project outcomes will enable realistic evaluation of the performances of infrastructure in Arctic Alaska and improve the design of more robust infrastructure in the Arctic. The research team will actively recruit and train women scientists and engineers through convergent research, and the research team will be involved in educational and outreach activities in Utqiaġvik, Alaska’s indigenous community.<br/><br/>The goal of this project is to understand and forecast long-term variations of in-situ geophysical and geomechanical characteristics of the active layer and permafrost in Arctic Alaska using an innovative sensing technology, data transmission and analysis, and modeling. Through advances in sensor systems and modeling, the project will transform existing capabilities for understanding dynamic, near-surface soil processes in the active layer and permafrost in an Arctic coastal community, thus generating quantitative knowledge of long-term and in-situ permafrost degradation in the Arctic due to climate change. Five tasks will be conducted: (1) develop and deploy a 1.5-kilometer-long fiber-optic distributed acoustic sensing (DAS) array in Utqiaġvik, Alaska for long-term in-situ permafrost monitoring; (2) develop innovative data transmission and analysis of DAS signals in permafrost and derive temperature-dependent S-wave and P-wave velocity profiles of changing permafrost in spatial and temporal scales; (3) obtain ground-truth measurements of geophysical and geomechanical properties through in-situ and laboratory characterizations; (4) develop correlations between geophysical and geomechanical properties of permafrost and S- and P-wave velocities as well as between permafrost temperature and S- and P-wave velocities; and (5) forecast future changes of geophysical and geomechanical properties of degrading permafrost. Research outcomes will directly inform current infrastructure evaluation and future infrastructure development in the North Slope Borough, Alaska. Methodology developed in this project will provide transformative and cost-effective geophysical and geotechnical monitoring in the Arctic and sub-Arctic regions.<br/><br/>This award was made through the "Signals in the Soil (SitS)" solicitation, a collaborative partnership between the National Science Foundation and the United States Department of Agriculture National Institute of Food and Agriculture (USDA NIFA).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/30/2024

07/30/2024

None

Grant

47.041

1

4900

4900

2437668

{'FirstName': 'Eileen', 'LastName': 'Martin', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eileen R Martin', 'EmailAddress': 'eileenrmartin@mines.edu', 'NSF_ID': '000793187', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'ZipCode': '804011887', 'PhoneNumber': '3032733000', 'StreetAddress': '1500 ILLINOIS ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'CO07', 'ORG_UEI_NUM': 'JW2NGMP4NMA3', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF THE COLORADO SCHOOL OF MINES', 'ORG_PRNT_UEI_NUM': 'JW2NGMP4NMA3'}

{'Name': 'Colorado School of Mines', 'CityName': 'GOLDEN', 'StateCode': 'CO', 'ZipCode': '804011887', 'StreetAddress': '1500 ILLINOIS ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'CO07'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2020~121069

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437668.xml'}

Conference: 38th Annual Gibbs Conference on Biothermodynamics

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Wilson Francisco', 'PO_EMAI': 'wfrancis@nsf.gov', 'PO_PHON': '7032927856'}

The 38th Annual Gibbs Conference on Biothermodynamics will be held at the Touch of Nature Outdoor Education Center in Carbondale, Illinois on September 28-October 1, 2024. The Gibbs Conference brings together researchers with similar interests in understanding how changes in structure and energetics manifest in biological function. This conference provides a unique opportunity for scientific exchange and collegial interactions among researchers, while fostering the professional growth of early career trainees and promoting an equitable, accessible, and inclusive biothermodynamics community. The 2024 conference will bring together scientists from across the country as invited speakers and create numerous opportunities for trainees and early-career scientists to connect with peers and mentors.<br/><br/>Biological thermodynamics aims to understand the energetics of chemical processes that lead to biological function. Modern biothermodynamics has evolved new ideas with the use of technological advancements to probe the basic tenets of allostery. More broadly, biothermodynamics now includes structural biology to help link the gap between structure, energetics, and function. To move the field forward, there is a need to bring together various disciplines. The field is now at the intersection of computational methodologies, detailed kinetic investigations, structural biology, molecular biology, high- throughput approaches, and classical thermodynamics. Combining these diverse disciplines will lead to new developments in all areas of biology. Developments in modern biothermodynamics will continue to lead to the development of new approaches and methodologies to study protein-protein and protein-ligand interactions, enzymes, and their cellular pathways. This meeting is supported by the Molecular Biophysics Cluster of the Division of Molecular and Cellular Biosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/19/2024

07/19/2024

None

Grant

47.074

1

4900

4900

2437673

[{'FirstName': 'Ernesto', 'LastName': 'Fuentes', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ernesto J Fuentes', 'EmailAddress': 'ernesto-fuentes@uiowa.edu', 'NSF_ID': '000281382', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Tonya', 'LastName': 'Zeczycki', 'PI_MID_INIT': 'N', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tonya N Zeczycki', 'EmailAddress': 'zeczyckit@ecu.edu', 'NSF_ID': '000736183', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'ZipCode': '522421316', 'PhoneNumber': '3193352123', 'StreetAddress': '105 JESSUP HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IA01', 'ORG_UEI_NUM': 'Z1H9VJS8NG16', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF IOWA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'StateCode': 'IA', 'ZipCode': '522421316', 'StreetAddress': '105 JESSUP HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Iowa', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IA01'}

{'Code': '114400', 'Text': 'Molecular Biophysics'}

2024~7000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437673.xml'}

I-Corps: Transformation Potential of a Clinical Decision Support System for the Early Detection of Endometriosis

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Molly Wasko', 'PO_EMAI': 'mwasko@nsf.gov', 'PO_PHON': '7032924749'}

The broader impact of this I-Corps project is based on the development of an artificial intelligence-driven clinical decision support system to detect endometriosis. Endometriosis is a chronic medical condition in which tissue similar to the lining inside the uterus, called the endometrium, begins to grow outside the uterus. This condition can cause pain, irregular bleeding, and may lead to infertility. Early diagnosis of endometriosis can improve patient outcomes, increase access to care, and lead to more treatment options. This technology combines patient screening with image analysis to provide a comprehensive clinical decision support system for physicians and radiologists caring for patients at risk of this condition. This innovative approach to early-stage endometriosis detection has the potential to reduce diagnostic disparities and democratize access to high-quality care for all women. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a clinical decision support system that offers a non-invasive, objective, and accessible solution for early-stage detection of the superficial peritoneal lesions found in endometriosis. The technology combines a patient screening tool and an imaging analysis tool to identify key health indicators and risk factors to help primary care physicians and gynecologists detect early-stage endometriosis. The technology also analyzes magnetic resonance imaging (MRI) images based on a deep learning model with more than 5 years of high-quality patient data, offering radiologists a more transparent, reliable, and repeatable scoring mechanism for potential endometriosis.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.084

1

4900

4900

2437697

{'FirstName': 'Susan', 'LastName': 'Khalil', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Susan Khalil', 'EmailAddress': 'susan.khalil@mountsinai.org', 'NSF_ID': '0000A0D8D', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Icahn School of Medicine at Mount Sinai', 'CityName': 'NEW YORK', 'ZipCode': '100296504', 'PhoneNumber': '2128248300', 'StreetAddress': '1 GUSTAVE L LEVY PL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'C8H9CNG1VBD9', 'ORG_LGL_BUS_NAME': 'ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI', 'ORG_PRNT_UEI_NUM': 'C8H9CNG1VBD9'}

{'Name': 'Icahn School of Medicine at Mount Sinai', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100296504', 'StreetAddress': '1 GUSTAVE L LEVY PL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437697.xml'}

EAGER: III: Visualizing and Tracking Progress in Multimodal CR (Cardiac Rehabilitation) Data

NSF

10/01/2024

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Christopher Yang', 'PO_EMAI': 'ccyang@nsf.gov', 'PO_PHON': '7032928111'}

While integration of multimodal information has been widely researched, the difficulty in carrying out this integration in a domain-agnostic, generic manner has been problematic. Past results have emphasized the need for addressing multimodal integration in a domain-specific manner. For instance, cardiac rehabilitation is a diverse range of practices for restoring individual's functioning. Unfortunately, only 30% - 40% of patients report regular exercise at six months after discharge and 39%-45% of these patients suffer from at least one readmission within one year. These poor outcomes motivate the need for using technology for remote monitoring in this multi-modal system. The overarching goal of this proposal is to understand how multiple cardiac experts view multimodal data, decide on the progress, and the variations/biases among the experts' views and decisions. This understanding would help us design and build a multimodal visualization and progress-tracking system that can provide meaningful information to stakeholders. Though the proposed algorithms for multimodal data analysis are tightly tied to the biomedical domain, the derived knowledge and understanding would be useful to other domains using multimodal sensing. Results, metrics, and algorithms from this research will be published widely in high-quality academic journals and conference proceedings.<br/><br/>Integrating, visualizing and tracking progress using multimodal data is highly domain dependent. In this project, cardiac tele-rehabilitation deployed in-home is the target domain, generating multimodal data, with their diverse data characteristics and varied timeframes. Research challenges in domain-specific multimodal integration typically include the characteristics of the multimodal data as well as the domain-specific needs. For multimodal integration for cardiac rehabilitation, the challenges include: (i) Integrating the multimodal data with diverse types of data with varying temporal characteristics to find relationships among potential adverse events; and, (ii) Possibilities for using mobile and wearable sensors to provide opportunities for personalization both in the rehabilitation and in the multimodal data integration. The proposed system, in the form of a mobile app, will democratize data acquisition. This, in turn, could lead to a better understanding of bias among experts and possible strategies for mitigating the bias and provide appropriate feedback and nudges to patients.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/28/2024

07/28/2024

None

Grant

47.070

1

4900

4900

2437698

{'FirstName': 'Balakrishnan', 'LastName': 'Prabhakaran', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Balakrishnan Prabhakaran', 'EmailAddress': 'praba@utdallas.edu', 'NSF_ID': '000230020', 'StartDate': '07/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Texas at Dallas', 'CityName': 'RICHARDSON', 'ZipCode': '750803021', 'PhoneNumber': '9728832313', 'StreetAddress': '800 WEST CAMPBELL RD.', 'StreetAddress2': 'SP2.25', 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'EJCVPNN1WFS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT DALLAS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Dallas', 'CityName': 'RICHARDSON', 'StateCode': 'TX', 'ZipCode': '750803021', 'StreetAddress': '800 WEST CAMPBELL RD.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'TX24'}

{'Code': '736400', 'Text': 'Info Integration & Informatics'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437698.xml'}

Planning: CRISES: Building Collective Action for Sustainable Habitats

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

This project applies behavior science research approaches to investigate how people self-organize to manage the use of natural resources. There is a pressing need for understanding and improving collective action participation in native habitat conservation and restoration in grassland ecosystems. This planning project is for a research center that will use knowledge from psychology research to build communities and networks that help maintain vital natural resources for the common good. The project focuses on native watershed habitat rehabilitation and maintenance in urban/rural settings as a test topic. The research team investigates the social, environmental, and information infrastructure that tend to lead to sustained natural resource governance arrangements. This work is developed in partnership with local stakeholders to build sustainable community-involved research opportunities (social infrastructure).<br/><br/>The deterioration of collective action for maintaining natural resources as common goods is an ongoing, complex, and global problem. Collective action can under some conditions sustain these natural resource governance arrangements. However, lack of participation and free-rider problems are two of just many challenges that pose barriers to sustained common-pool resource management. Previous work has identified the conditions that tend to support sustained governance of common pool resources. This project specifically investigates how to build and maintain those characteristics. The research project focuses on the context of urban/rural native watershed habitat rehabilitation and maintenance. A key challenge in these systems is how to translate existing insights about the features of existing systems that successfully maintain common goods into ways to effectively change social, political, economic, and environmental contexts that will bring common and public goods situations into full collective action participation. This project addresses this need by developing multi-site, community engaged research labs that a) test the application of techniques from cognitive and social psychology to guide changes to people’s experienced environment, and b) build the infrastructure of people, resources, and equipment needed to support common goods in at-risk grasslands ecosystems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437719

[{'FirstName': 'Gary', 'LastName': 'Brase', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gary L Brase', 'EmailAddress': 'gbrase@ksu.edu', 'NSF_ID': '000446551', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Jason', 'LastName': 'Vogel', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason R Vogel', 'EmailAddress': 'jason.vogel@ou.edu', 'NSF_ID': '000582763', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Aaron', 'LastName': 'Mittelstet', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aaron R Mittelstet', 'EmailAddress': 'amittelstet2@unl.edu', 'NSF_ID': '000749815', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Katherine', 'LastName': 'Nelson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine Nelson', 'EmailAddress': 'katherinenelson@missouri.edu', 'NSF_ID': '000785964', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'ZipCode': '665062504', 'PhoneNumber': '7855326804', 'StreetAddress': '1601 VATTIER STREET', 'StreetAddress2': '103 FAIRCHILD HALL', 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'CFMMM5JM7HJ9', 'ORG_LGL_BUS_NAME': 'KANSAS STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'StateCode': 'KS', 'ZipCode': '665062504', 'StreetAddress': '1601 VATTIER STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437719.xml'}

Collaborative Research: Planning: CRISES: Human-Centered Early Warning Systems for Weather Hazards

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Hazardous weather early warning systems disseminate timely and meaningful information about flash floods, tornadoes, and other weather hazards so that individuals, communities and organizations can prepare for and protect themselves against harm or loss. Early warning systems involve sensors, model forecasts, federal and local public safety organizations, private companies, and communications technologies that disseminate warnings to the public. Hazardous weather warning messages are general rather than tailored to the risks faced by the people who receive them. The same warning message goes out to everyone in an affected region, regardless of individual circumstances. Each person is responsible for ensuring they receive and understand the warning, figuring out if they or loved ones are at risk, and then deciding if they have the capability or interest in taking protective actions. While warning systems have been effective for segments of the population, there is great potential to improve individual-level decision-making and community/societal outcomes, especially in the face of rapidly intensifying weather events. This planning grant takes a human-centered approach to hazardous weather warning to: 1) develop a deeper understanding of how individuals assess their risk and take action as weather hazards evolve, and 2) apply this expanded knowledge to new ways of tailoring warnings to individual or group circumstances.<br/><br/>In this planning grant, a multidisciplinary group of researchers and practitioners address how multiple factors – rain intensity, quality of the stormwater infrastructure, individual daily routines of travel, advanced preparation, risk perception, warnings, social and environmental cues, and socioeconomic vulnerability – interact to influence people’s perception and response to floods. The team establish a common knowledge base and language through sharing research, methods, and datasets. A focus group is held with residents of vulnerable communities in collaboration with a local nonprofit to investigate how different individuals process information from early warning systems. The planning project includes exploratory projects that contribute to an innovative plan for convergent human-centered research. This work identifies new relationships among risk perception, mobility, weather, and built infrastructure that can point to new directions for convergent warning research. In addition, the planning grant allows early work on developing the concept of personalized warnings. Broader impacts include outreach to vulnerable populations to learn about this group’s perceptions and actions during floods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437723

[{'FirstName': 'Brenda', 'LastName': 'Philips', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brenda J Philips', 'EmailAddress': 'bphilips@ecs.umass.edu', 'NSF_ID': '000497276', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Curtis', 'LastName': 'Walker', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Curtis L Walker', 'EmailAddress': 'walker@ucar.edu', 'NSF_ID': '000878384', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'ZipCode': '010039252', 'PhoneNumber': '4135450698', 'StreetAddress': '101 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'VGJHK59NMPK9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'StateCode': 'MA', 'ZipCode': '010039252', 'StreetAddress': '101 COMMONWEALTH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~59772

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437723.xml'}

Collaborative Research: Planning: CRISES: Human-Centered Early Warning Systems for Weather Hazards

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Hazardous weather early warning systems disseminate timely and meaningful information about flash floods, tornadoes, and other weather hazards so that individuals, communities and organizations can prepare for and protect themselves against harm or loss. Early warning systems involve sensors, model forecasts, federal and local public safety organizations, private companies, and communications technologies that disseminate warnings to the public. Hazardous weather warning messages are general rather than tailored to the risks faced by the people who receive them. The same warning message goes out to everyone in an affected region, regardless of individual circumstances. Each person is responsible for ensuring they receive and understand the warning, figuring out if they or loved ones are at risk, and then deciding if they have the capability or interest in taking protective actions. While warning systems have been effective for segments of the population, there is great potential to improve individual-level decision-making and community/societal outcomes, especially in the face of rapidly intensifying weather events. This planning grant takes a human-centered approach to hazardous weather warning to: 1) develop a deeper understanding of how individuals assess their risk and take action as weather hazards evolve, and 2) apply this expanded knowledge to new ways of tailoring warnings to individual or group circumstances.<br/><br/>In this planning grant, a multidisciplinary group of researchers and practitioners address how multiple factors – rain intensity, quality of the stormwater infrastructure, individual daily routines of travel, advanced preparation, risk perception, warnings, social and environmental cues, and socioeconomic vulnerability – interact to influence people’s perception and response to floods. The team establish a common knowledge base and language through sharing research, methods, and datasets. A focus group is held with residents of vulnerable communities in collaboration with a local nonprofit to investigate how different individuals process information from early warning systems. The planning project includes exploratory projects that contribute to an innovative plan for convergent human-centered research. This work identifies new relationships among risk perception, mobility, weather, and built infrastructure that can point to new directions for convergent warning research. In addition, the planning grant allows early work on developing the concept of personalized warnings. Broader impacts include outreach to vulnerable populations to learn about this group’s perceptions and actions during floods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437724

{'FirstName': 'Jessica', 'LastName': 'Eisma', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica A Eisma', 'EmailAddress': 'jessica.eisma@uta.edu', 'NSF_ID': '000847319', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~7000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437724.xml'}

Collaborative Research: Planning: CRISES: Human-Centered Early Warning Systems for Weather Hazards

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Hazardous weather early warning systems disseminate timely and meaningful information about flash floods, tornadoes, and other weather hazards so that individuals, communities and organizations can prepare for and protect themselves against harm or loss. Early warning systems involve sensors, model forecasts, federal and local public safety organizations, private companies, and communications technologies that disseminate warnings to the public. Hazardous weather warning messages are general rather than tailored to the risks faced by the people who receive them. The same warning message goes out to everyone in an affected region, regardless of individual circumstances. Each person is responsible for ensuring they receive and understand the warning, figuring out if they or loved ones are at risk, and then deciding if they have the capability or interest in taking protective actions. While warning systems have been effective for segments of the population, there is great potential to improve individual-level decision-making and community/societal outcomes, especially in the face of rapidly intensifying weather events. This planning grant takes a human-centered approach to hazardous weather warning to: 1) develop a deeper understanding of how individuals assess their risk and take action as weather hazards evolve, and 2) apply this expanded knowledge to new ways of tailoring warnings to individual or group circumstances.<br/><br/>In this planning grant, a multidisciplinary group of researchers and practitioners address how multiple factors – rain intensity, quality of the stormwater infrastructure, individual daily routines of travel, advanced preparation, risk perception, warnings, social and environmental cues, and socioeconomic vulnerability – interact to influence people’s perception and response to floods. The team establish a common knowledge base and language through sharing research, methods, and datasets. A focus group is held with residents of vulnerable communities in collaboration with a local nonprofit to investigate how different individuals process information from early warning systems. The planning project includes exploratory projects that contribute to an innovative plan for convergent human-centered research. This work identifies new relationships among risk perception, mobility, weather, and built infrastructure that can point to new directions for convergent warning research. In addition, the planning grant allows early work on developing the concept of personalized warnings. Broader impacts include outreach to vulnerable populations to learn about this group’s perceptions and actions during floods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437725

{'FirstName': 'Jennifer', 'LastName': 'Henderson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer Henderson', 'EmailAddress': 'jen.henderson@ttu.edu', 'NSF_ID': '000845959', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Texas Tech University', 'CityName': 'LUBBOCK', 'ZipCode': '79409', 'PhoneNumber': '8067423884', 'StreetAddress': '2500 BROADWAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'TX19', 'ORG_UEI_NUM': 'EGLKRQ5JBCZ7', 'ORG_LGL_BUS_NAME': 'TEXAS TECH UNIVERSITY SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Texas Tech University', 'CityName': 'LUBBOCK', 'StateCode': 'TX', 'ZipCode': '79409', 'StreetAddress': '2500 BROADWAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'TX19'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~17000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437725.xml'}

Collaborative Research: Planning: CRISES: Human-Centered Early Warning Systems for Weather Hazards

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Hazardous weather early warning systems disseminate timely and meaningful information about flash floods, tornadoes, and other weather hazards so that individuals, communities and organizations can prepare for and protect themselves against harm or loss. Early warning systems involve sensors, model forecasts, federal and local public safety organizations, private companies, and communications technologies that disseminate warnings to the public. Hazardous weather warning messages are general rather than tailored to the risks faced by the people who receive them. The same warning message goes out to everyone in an affected region, regardless of individual circumstances. Each person is responsible for ensuring they receive and understand the warning, figuring out if they or loved ones are at risk, and then deciding if they have the capability or interest in taking protective actions. While warning systems have been effective for segments of the population, there is great potential to improve individual-level decision-making and community/societal outcomes, especially in the face of rapidly intensifying weather events. This planning grant takes a human-centered approach to hazardous weather warning to: 1) develop a deeper understanding of how individuals assess their risk and take action as weather hazards evolve, and 2) apply this expanded knowledge to new ways of tailoring warnings to individual or group circumstances.<br/><br/>In this planning grant, a multidisciplinary group of researchers and practitioners address how multiple factors – rain intensity, quality of the stormwater infrastructure, individual daily routines of travel, advanced preparation, risk perception, warnings, social and environmental cues, and socioeconomic vulnerability – interact to influence people’s perception and response to floods. The team establish a common knowledge base and language through sharing research, methods, and datasets. A focus group is held with residents of vulnerable communities in collaboration with a local nonprofit to investigate how different individuals process information from early warning systems. The planning project includes exploratory projects that contribute to an innovative plan for convergent human-centered research. This work identifies new relationships among risk perception, mobility, weather, and built infrastructure that can point to new directions for convergent warning research. In addition, the planning grant allows early work on developing the concept of personalized warnings. Broader impacts include outreach to vulnerable populations to learn about this group’s perceptions and actions during floods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437726

{'FirstName': 'Barbara', 'LastName': 'Minsker', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Barbara Minsker', 'EmailAddress': 'minsker@smu.edu', 'NSF_ID': '000202149', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'ZipCode': '752051902', 'PhoneNumber': '2147684708', 'StreetAddress': '6425 BOAZ ST RM 130', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'D33QGS3Q3DJ3', 'ORG_LGL_BUS_NAME': 'SOUTHERN METHODIST UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'S88YPE3BLV66'}

{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'StateCode': 'TX', 'ZipCode': '752051902', 'StreetAddress': '6425 BOAZ ST RM 130', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'TX24'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~10000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437726.xml'}

Collaborative Research: Planning: CRISES: Human-Centered Early Warning Systems for Weather Hazards

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Hazardous weather early warning systems disseminate timely and meaningful information about flash floods, tornadoes, and other weather hazards so that individuals, communities and organizations can prepare for and protect themselves against harm or loss. Early warning systems involve sensors, model forecasts, federal and local public safety organizations, private companies, and communications technologies that disseminate warnings to the public. Hazardous weather warning messages are general rather than tailored to the risks faced by the people who receive them. The same warning message goes out to everyone in an affected region, regardless of individual circumstances. Each person is responsible for ensuring they receive and understand the warning, figuring out if they or loved ones are at risk, and then deciding if they have the capability or interest in taking protective actions. While warning systems have been effective for segments of the population, there is great potential to improve individual-level decision-making and community/societal outcomes, especially in the face of rapidly intensifying weather events. This planning grant takes a human-centered approach to hazardous weather warning to: 1) develop a deeper understanding of how individuals assess their risk and take action as weather hazards evolve, and 2) apply this expanded knowledge to new ways of tailoring warnings to individual or group circumstances.<br/><br/>In this planning grant, a multidisciplinary group of researchers and practitioners address how multiple factors – rain intensity, quality of the stormwater infrastructure, individual daily routines of travel, advanced preparation, risk perception, warnings, social and environmental cues, and socioeconomic vulnerability – interact to influence people’s perception and response to floods. The team establish a common knowledge base and language through sharing research, methods, and datasets. A focus group is held with residents of vulnerable communities in collaboration with a local nonprofit to investigate how different individuals process information from early warning systems. The planning project includes exploratory projects that contribute to an innovative plan for convergent human-centered research. This work identifies new relationships among risk perception, mobility, weather, and built infrastructure that can point to new directions for convergent warning research. In addition, the planning grant allows early work on developing the concept of personalized warnings. Broader impacts include outreach to vulnerable populations to learn about this group’s perceptions and actions during floods.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.075

1

4900

4900

2437727

{'FirstName': 'Steven', 'LastName': 'Martinaitis', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Steven M Martinaitis', 'EmailAddress': 'steven.martinaitis@noaa.gov', 'NSF_ID': '0000A0F00', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'ZipCode': '730193003', 'PhoneNumber': '4053254757', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OK04', 'ORG_UEI_NUM': 'EVTSTTLCEWS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'StateCode': 'OK', 'ZipCode': '730193003', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OK04'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~6228

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437727.xml'}

Planning: CRISES: Center for Socio-Technological Transformation

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

Today’s societies face multiple, often overlapping and reinforcing social, economic, and environmental challenges. Technology and technological systems unfortunately contribute to many of these challenges, including risk, inequality, and insecurity. Energy is an important example. Energy technologies and systems provide essential human services (e.g., mobility, electric power, security, heating and cooling). At the same time, they are increasingly at risk due to extreme weather and cybersecurity risks. They contribute to climate change and air pollution. And they pose costly financial burdens for low-income households and communities that have the potential to perpetuate and exacerbate poverty. It is important, therefore, to find new ways to design and orchestrate human relationships with technology and infrastructure that support and strengthen, rather than undermine, families and communities.<br/><br/>This study investigates how to advance innovation in technology and technological systems that supports and enhances human wellbeing and security. The goal is to significantly improve understanding of socio-technological systems, defined as how technology is integrated into society, in the present and in the future. The project carries out planning of research to analyze how current socio-technological systems contribute to risk, inequality, and insecurity. It develops approaches to envisioning and designing future socio-technological systems that strengthen families and communities. And it explores how to bring about change from today’s existing socio-technological systems to better future alternatives. The project uses research methods that foster interdisciplinary synthesis and convergence to create use-inspired and useful knowledge for societal partners. These methods draw together researchers from the social and economic sciences and engineering, as well as community, government, and industry leaders, in a process of collaborative research design. The project also carries out planning of associated educational, training, community engagement, and other initiatives to accompany the research as part of a comprehensive research center design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437739

{'FirstName': 'Clark', 'LastName': 'Miller', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Clark A Miller', 'EmailAddress': 'clark.miller@asu.edu', 'NSF_ID': '000414676', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437739.xml'}

EAGER: RDSV: Envisioning Sociotechnical Ecosystems Research

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Mitra Basu', 'PO_EMAI': 'mbasu@nsf.gov', 'PO_PHON': '7032928649'}

Computer and Information Science and Engineering (CISE) research produces many innovations. The impact of these innovations depends on their adoption in the greater sociotechnical ecosystem – the set of technical components and actors, the economic transactions between these entities, the legal system governing them, and the human end users. Thus, anticipating the impact of new research directions requires a broad range of expertise. This award will go towards the development of a new organizational structure for envisioning new research directions for CISE that is informed by representatives of the social sciences, legal studies, and civil society, as well as scientific, industry, and government leaders. Through a systematic process of interviews and workshops, the investigators will elicit these experts’ best ideas about new research directions, as well as the theories of change that motivate these ideas. Computational models of sociotechnical ecosystems based on these ideas will then serve as tools in visioning workshops where assumptions are revealed and challenged. The goal is to develop a process for strategic visioning of CISE research that is both sensitive to complex sociotechnical and ecosystemic change and consistent with computational thinking.<br/><br/>The investigators will iteratively perform a visioning process, improving each cycle. The process involves five steps. First, the investigators will identify seed participants. In addition to scientific, industry, and government experts, the team will seed their study with non-technical scholars of technology policy and ethics, as well as computational social scientists. Second, the investigators will conduct semi-structured interviews, starting with the initial seed participants and expanding through snowball sampling, to elicit their views of promising research directions and potential social impacts, as well as the theories of change that motivate their recommendations. Third, the investigators will compile these results into structured data and build composite models of sociotechnical ecosystems and the hypothesized dynamics of research impact. Fourth, the investigators will hold workshops in which the interview process and the resulting composite models are reviewed, critiqued, and “red-teamed”. Lastly, the investigators will disseminate the results on-line, back to participants, and to NSF program officers. This work will culminate in a written report published to the profession, and a tutorial on running such processes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.070

1

4900

4900

2437745

[{'FirstName': 'Scott', 'LastName': 'Shenker', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Scott Shenker', 'EmailAddress': 'shenker@icsi.berkeley.edu', 'NSF_ID': '000241246', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sebastian', 'LastName': 'Benthall', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sebastian Benthall', 'EmailAddress': 'sbenthall@gmail.com', 'NSF_ID': '000840443', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'International Computer Science Institute', 'CityName': 'BERKELEY', 'ZipCode': '947041345', 'PhoneNumber': '5106662900', 'StreetAddress': '2150 SHATTUCK AVE', 'StreetAddress2': 'SUITE 250', 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GSRMP1QCXU74', 'ORG_LGL_BUS_NAME': 'INTERNATIONAL COMPUTER SCIENCE INSTITUTE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'International Computer Science Institute', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947041345', 'StreetAddress': '2150 SHATTUCK AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

{'Code': '164000', 'Text': 'Information Technology Researc'}

2024~292844

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437745.xml'}

Planning: CRISES: Center for Social Science and Artificial Intelligence Technology

NSF

09/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Artificial intelligence (AI)—and particularly deep learning—is progressing rapidly from a technical perspective, but, in a number of domains, adoption is still pending over the resolution of important issues. Methods of data analysis and interpretation based on AI are becoming common among law enforcement agencies (LEAs). Typical applications include suspect profiling (e.g., on social media), traffic control (automated license plate detection and vehicle identification), analyzing dark web money flows, child pornography detection, and anomaly detection. Noteworthy and concerning, is the literature on the various ethical and legal concerns surrounding several issues, namely, AI bias. A culturally competent and social science focused approach to AI and Machine Learning approaches in law enforcement is needed at the forefront of this enhanced predictive application of policing. Specifically, artificial intelligence (AI) can be used to enhance justice in order to eradicate the biases that deny targeted people access to resources or freedom through the judicial system. Additionally, AI law enforcement should be used, if and where possible, to overcome discriminatory traits in human policing that have been a problem for law enforcement for decades. This proposal advances a center to keep pace with strategic and technological advancement, particularly, as these endeavors relate to AI, Machine Learning and predictive policing. <br/><br/>This planning project’s main objective is to bring together a multidisciplinary group of experts to guide various sheriff departments to navigate challenges and opportunities they encounter as artificial intelligence becomes more embedded and an integral part of law enforcement. The development of AI technology to better society must be approached with a more social scientific focus and include constituents most affected by biases in law enforcement. With most constituents struggling to develop convincing and clear-cut guidelines to direct legislative and administrative considerations, this planning proposal explores the need and capacity of a specific focused center. This center offers guidance on how to implement AI in law enforcement by collaborating with local sheriff departments and expanding to other law enforcement agencies across various states. Trainings in the use of AI must be responsive to the needs of the communities law enforcement agencies are serving. The project develops plans for sustained research and training engagement amongst law enforcement departments, multidisciplinary academic teams, government agencies, policy makers, community group members and other constituents to focus and navigate the paradigm shift that law enforcement experiences with the continued progression of machine learning and specifically artificial intelligence.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.075

1

4900

4900

2437763

{'FirstName': 'Denise', 'LastName': 'Nation', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Denise Nation', 'EmailAddress': 'nationde@wssu.edu', 'NSF_ID': '000857747', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Winston-Salem State University', 'CityName': 'WINSTON SALEM', 'ZipCode': '271100003', 'PhoneNumber': '3367503019', 'StreetAddress': '601 S MARTIN LUTHER KING JR DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'NC05', 'ORG_UEI_NUM': 'K54FKGWN2EN5', 'ORG_LGL_BUS_NAME': 'WINSTON-SALEM STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Winston-Salem State University', 'CityName': 'WINSTON SALEM', 'StateCode': 'NC', 'ZipCode': '271100003', 'StreetAddress': '601 S MARTIN LUTHER KING JR DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'NC05'}

{'Code': '146Y00', 'Text': 'Build and Broaden'}

2024~99989

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437763.xml'}

I-Corps: Translation Potential of a Seismic Monitoring System Empowered by Machine Learning Automation

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': 'jcamelio@nsf.gov', 'PO_PHON': '7032922061'}

The broader impact of this I-Corps project is the development of a fully automated seismic monitoring system. The new seismic monitoring system will contribute to safer energy production and storage which may have significant, positive environmental and societal implications. The need for this solution is partially due to new technologies like hydraulic fracturing in oil, gas and geothermal reservoirs which cause earthquakes but also due to the need to safely store energy and carbon dioxide (CO2) in the sub-surface. Better seismic monitoring systems provide early alerts enabling reservoir operations to be adjusted to mitigate this hazard. The new technology will contribute to a safer and more efficient transition to new energy sources. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of an automated seismic monitoring system. The need for seismic monitoring is rapidly accelerating both in plate boundary and energy producing areas. The increasingly widespread usage of geothermal energy and CO2 capture and sequestration is expected to be associated with significant seismic hazards which need to be effectively monitored. Seismic monitoring is complex, expensive, and time consuming, and many companies struggle with the right approach. The new technology will provide a comprehensive new seismic monitoring package, including instrumentation, software applications and visualization tools to facilitate a completely automated approach. The product builds on state-of-the-art machine learning processing pipelines and large amounts of labeled data from previous experiments. The new system is easy to deploy and maintain, which significantly cuts installation and personnel costs. The ultimate goal is to facilitate swift and safe energy storage and production through cutting-edge seismic monitoring.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.084

1

4900

4900

2437766

{'FirstName': 'Thomas', 'LastName': 'Goebel', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas H Goebel', 'EmailAddress': 'thgoebel@memphis.edu', 'NSF_ID': '000829207', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'ZipCode': '381520001', 'PhoneNumber': '9016783251', 'StreetAddress': '115 JOHN WILDER TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TN09', 'ORG_UEI_NUM': 'F2VSMAKDH8Z7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MEMPHIS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'StateCode': 'TN', 'ZipCode': '381523370', 'StreetAddress': '115 JOHN WILDER TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TN09'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437766.xml'}

Planning: CRISES: Center for Indigenous Knowledge and Stewardship (CIKS)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04010000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SMA', 'LongName': 'SBE Off Of Multidisciplinary Activities'}}

{'SignBlockName': 'Naomi Hall-Byers', 'PO_EMAI': 'nhallbye@nsf.gov', 'PO_PHON': '7032922672'}

Addressing national and global crises taking place at the intersection of society and environmental relations requires innovation and transformative approaches. Current approaches from US research have focused exclusively on western scientific disciplines – what is missing is the breadth and depth of Indigenous knowledge systems. This planning grant convenes a group of university researchers (Indigenous and non-Indigenous scientists) and Tribal leaders and partners to generate a new vision of how universities and Tribal Nations can work together to develop new research protocols and projects to address the social and environmental crises facing not just Tribes, but all communities all across our nation. This Indigenous-led convening uplifts Tribal leadership together with western science expertise to collaboratively vision and co-develop a proposal for the Center for Indigenous Knowledge and Stewardship (CIKS). <br/><br/>As Indigenous scholars, social scientists, natural scientists, and Tribal leaders, our team has worked across cultural and disciplinary boundaries over years of collaboration to build relationships and trust necessary to advance the goals of this work in effective and culturally appropriate ways. Our evidence-based approach to transforming research processes includes an elevation of Indigenous epistemologies and ontologies, Indigenous rights and values, Indigenous knowledge, language, stories, protocols, and practices. The Center for Indigenous Knowledge and Stewardship generates a new vision of how universities and Tribes can work together to address the social and environmental crises of our time. There is a growing need for scientists trained in knowledge co-production and for inclusive science to correct the systematic exclusion of Indigenous peoples and knowledge systems from conventional western science research approaches. Our convening and collaboration to co-develop a full proposal for CIKS will itself generate and advance scholarship on knowledge co-production and expand environmental sciences and governance processes to better include western social sciences, Indigenous knowledge systems, and One Health frameworks. CIKS would be a national model for training and research that bridges Indigenous and western sciences to address seemingly intractable social-environmental crises. CIKS’s focus on addressing critical crises facing Indigenous and all communities across the nation will improve health and wellbeing of people and environments.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.075

1

4900

4900

2437775

[{'FirstName': 'Courtney', 'LastName': 'Carothers', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Courtney L Carothers', 'EmailAddress': 'clcarothers@alaska.edu', 'NSF_ID': '000511409', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Peter', 'LastName': 'Westley', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Peter A Westley', 'EmailAddress': 'pwestley@alaska.edu', 'NSF_ID': '000690589', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Charlene', 'LastName': 'Stern', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charlene B Stern', 'EmailAddress': 'cbstern@alaska.edu', 'NSF_ID': '000741971', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jessica', 'LastName': 'Black', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica C Black', 'EmailAddress': 'jcblack@alaska.edu', 'NSF_ID': '000746014', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alisa', 'LastName': 'Alexander', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alisa J Alexander', 'EmailAddress': 'ajalexander5@alaska.edu', 'NSF_ID': '0000A077Z', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Alaska Fairbanks Campus', 'CityName': 'FAIRBANKS', 'ZipCode': '997750001', 'PhoneNumber': '9074747301', 'StreetAddress': '2145 N TANANA LOOP', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alaska', 'StateCode': 'AK', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'AK00', 'ORG_UEI_NUM': 'FDLEQSJ8FF63', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ALASKA FAIRBANKS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Alaska Fairbanks Campus', 'CityName': 'FAIRBANKS', 'StateCode': 'AK', 'ZipCode': '997750001', 'StreetAddress': '2145 N TANANA LOOP', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alaska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'AK00'}

{'Code': '265Y00', 'Text': 'CRISES-R&I in Sci, Env&Society'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437775.xml'}

EAGER: How Well Does Traffic Control Theory and Optimization Research Work on Public Roads?

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Siqian Shen', 'PO_EMAI': 'siqshen@nsf.gov', 'PO_PHON': '7032927048'}

This EArly-Concept Grant for Exploratory Research (EAGER) project will identify gaps in translating traffic control theoretical research into practical traffic controls (such as traffic signals, ramp meters, and congestion pricing) in real-world settings and will attempt to discover scientific reasons for these gaps. Although academics have developed complex new controls built on models that are supposed to be more accurate, the traffic controls used in practice rely on theories and models that are at least two decades out of date, with no plans to implement the new methods that already exist from research. This issue leads to a fundamental research question: can controls based on more advanced theories perform better than legacy theories in practice? A positive answer will provide a tighter connection between research and practitioners to justify use of new research, and a negative answer will identify causes for performance differences that will inform future research and prepare for next-generation design of transportation and traffic control systems. The societal benefits could include reduced traffic congestion and lower travel times, which improves the well-being of travelers. This project also advances the field by improving the likelihood that traffic control research in general will become useful to practice. Results will be disseminated through conferences, curriculum redesign and development, as well as collaborations with industry and community partners through various educational and outreach activities. <br/><br/>The technical approach to the research is based on studying differences between widely accepted traffic flow models and real traffic from public vehicle trajectory data in the new transportation era. Kinematic wave theory is the most common macroscopic flow model, but how useful is the continuous partial differential equation for describing discrete vehicle traffic? How does heterogeneity in vehicle types and driver behaviors affect model accuracy, which is well-known as the variance in the congested side of the flow-density relationship? How does stochasticity in travel demand and route choices affect controls built for the average value? By modifying traffic flow models to include specific characteristics (such as time- and space-varying flow-density relationships caused by heterogeneous vehicles), researchers will test the importance of such characteristics on predicting reality. What are the important traffic characteristics to consider for different types of traffic controls? Answering this question might validate that specific existing traffic controls are likely effective in practice, or lead to new traffic flow models that incorporate important traffic behaviors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.041

1

4900

4900

2437781

[{'FirstName': 'Michael', 'LastName': 'Levin', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael W Levin', 'EmailAddress': 'mlevin@umn.edu', 'NSF_ID': '000771690', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Raphael', 'LastName': 'Stern', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Raphael Stern', 'EmailAddress': 'rstern@umn.edu', 'NSF_ID': '000821501', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '200 OAK ST SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437781.xml'}

Collaborative Research: Hominoid origins in a unique paleocommunity

NSF

06/15/2024

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Rebecca Ferrell', 'PO_EMAI': 'rferrell@nsf.gov', 'PO_PHON': '7032927850'}

This project advances knowledge about a crucial time in primate evolution when the ancestors of apes and humans are thought to have first diverged from other primate lines. A team of experts in paleoanthropology, paleontology and geology are conducting excavations and analyzing fossils and paleoenvironmental data from a fossil-bearing site in order to better understand the environmental context for primate adaptations and ecological diversity. The project offers invaluable research and training opportunities to scientists and students, including individuals from groups underrepresented in STEM, and provides opportunities for science outreach about human origins and climate change with local communities and the general public. <br/><br/>An extraordinary new fossil primate site provides an opportunity to obtain new data related to the origins of the hominoids during the Oligocene. The primary objective of the project is to characterize the species diversity and paleoenvironmental context for the site. The central hypothesis is that the earliest stem hominoids arose within unique ecological communities that were very unlike those of the later Miocene hominoid radiations. The team of paleoanthropologists, geologists, and paleontologists carry out this work through additional fieldwork and analysis of the hundreds of fossils and geological samples already obtained. The goals are three-fold: (1) characterize the paleobiological disparity between hominoids and cercopithecoids in the mid-Oligocene by analyzing functional disparity; (2) build out a robust geologic framework that integrates current and future fossil localities into a well constrained chronology; and (3) characterize the mammalian community diversity by contextualizing its taxonomic, functional, and phylogenetic composition.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.075

1

4900

4900

2437782

{'FirstName': 'Patricia', 'LastName': 'Princehouse', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia Princehouse', 'EmailAddress': 'patricia.princehouse@oswego.edu', 'NSF_ID': '000846086', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY College at Oswego', 'CityName': 'OSWEGO', 'ZipCode': '131263501', 'PhoneNumber': '3153122884', 'StreetAddress': '7060 STATE RTE 104', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'NY24', 'ORG_UEI_NUM': 'DLV5DEVHGF38', 'ORG_LGL_BUS_NAME': 'THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'SUNY College at Oswego', 'CityName': 'OSWEGO', 'StateCode': 'NY', 'ZipCode': '131263501', 'StreetAddress': '7060 STATE RTE 104', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'NY24'}

{'Code': '139200', 'Text': 'Biological Anthropology'}

2021~194926

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437782.xml'}

CRII:SCH: Interactive Explainable Deep Survival Analysis

NSF

10/01/2023

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Christopher Yang', 'PO_EMAI': 'ccyang@nsf.gov', 'PO_PHON': '7032928111'}

Annually, the United States spends almost 20% of gross domestic product (GDP) in healthcare with growth continued to be boosted by a greying population aging into Medicare. Although the cost is huge, numerous patients fail to get timely and effective medication cure. Accurate diagnosis is critical in clinical decision making. However, “prevention is better than cure” as prevention and early intervention will prevent the aging people from suffering more diseases and/or more extensive treatments. Also, it is too late to build the prediction model when a lot of patients have been observed in the late stage of a progressive disease, which severely damages their health. Meanwhile, in order to be usable by healthcare providers, the prediction model needs to be interpretable and trustable. Also, efficient interaction between human stakeholders (e.g., developers, domain experts and/or end-users) and clear model interpretation not only improve the model performance but also enhance human trust. The proposed research project aims at developing algorithms and methods that support implementation of trustworthy and time-efficient data-driven decision making for prevention and early intervention.<br/><br/>The main approach proposed in this project is interactive explainable deep survival analysis. Survival analysis aims at predicting the time to event of interest, which is extremely beneficial in healthcare for modeling disease progression, identifying prognostic factors, assessing risk of health. This project will build deep survival analysis models in healthy aging and precision medicine to support clinical decision making, especially in the early stage of a progressive disease before a lot of patients have been suffered from that disease. Deep survival analysis is a kind of “black box” model that stakeholders cannot tell how the model operates and how it comes to its decisions and hence limits its usage in practice. This project will develop methods to achieve both transparency and trustworthiness in deep survival analysis models with encoding of domain knowledge and expert feedback to achieve better prediction performance. More specifically, this project will propose a time-dependent counterfactual gradient integration to interpret what makes the model output differentiate from the counterfactual survival status at each time interval. This project will also incorporate feature attribution priors into the training process of deep survival analysis model to improve consistency of the explanation as well as the performance and trustworthiness of the model. Inspired by human-in-the-loop, this project will further investigate efficient schemes to mathematically formulate physicians' qualitative feedback, and interactively incorporate them in the learning process of the model with powerful perceptual user interface to efficiently encode diverse types of feedback from physicians.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.070

1

4900

4900

2437784

{'FirstName': 'Lu', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lu Wang', 'EmailAddress': 'lwang71@central.uh.edu', 'NSF_ID': '000895299', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'ZipCode': '772043067', 'PhoneNumber': '7137435773', 'StreetAddress': '4300 MARTIN LUTHER KING BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_ORG': 'TX18', 'ORG_UEI_NUM': 'QKWEF8XLMTT3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HOUSTON SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'StateCode': 'TX', 'ZipCode': '772043067', 'StreetAddress': 'HOUSTON, TX 772043067', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_PERF': 'TX18'}

{'Code': '801800', 'Text': 'Smart and Connected Health'}

2023~155163

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437784.xml'}

NSF-DFG MISSION: Operando Surface X-ray Scattering Studies of Quasi-epitaxial Growth and Electrocatalysis at Liquid Gallium Electrodes

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': "Francis D'Souza", 'PO_EMAI': 'frdsouza@nsf.gov', 'PO_PHON': '7032924559'}

Liquid metals are fertile platforms for inorganic materials synthesis and design. Recently, room temperature liquid metals have proven uniquely suited for the electrochemical syntheses of novel nanomaterials, new compositions of matter, and potent (electro)catalysts. A critical factor in expanding the palette of materials chemistry possible with liquid metals is a clearer understanding of the structure of the interface with molecular solutions. With support from the Division of Chemistry at NSF and DFG, Dr. Maldonado at U Michigan, Dr. Ocko at Brookhaven National Lab in US and Dr. Magnussen at Kiel University in Germany will work together to define the microscopic details of the evolution of the liquid/liquid interface between metallic gallium (Ga) and water during electrochemical reactions. The successful completion of the proposed work will lead to the development of supported electrode platforms that enable smooth, thin liquid metal films that are amenable for more precise operando and electrocatalytic studies and that are applicable to any liquid metal composition. The students involved in the research project will have the opportunity to enhance students exposure to global research and practices.<br/><br/>This work will advance the fundamental understanding of liquid metal/liquid electrolyte behaviors on two distinct fronts. First, the electrodeposition of various metals cations onto liquid Ga electrodes will be performed to examine the physicochemical and electrochemical factors at the interface relevant to observing quasi-epitaxial crystal growth. The atomistic details of quasi-epitaxy will be unraveled by operando X-ray reflectivity and grazing incidence X-ray diffraction. As an important prerequisite for these studies, the team will investigate the interface structure of liquid Ga in metal-free aqueous base electrolyte as a function of potential and pH, focusing in particular on the presence and structure of Ga surface oxide layers. Second, the formation and activity of supported catalytically active liquid metal platforms based on Ga will be studied. The interplay of the interface structure of the liquid metal interfacial structure and the distribution and dynamics of isolated catalytic solute atoms will be determined for the case of hydrogen evolution and electrochemical CO2 reduction.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.049

1

4900

4900

2437806

{'FirstName': 'Stephen', 'LastName': 'Maldonado', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephen Maldonado', 'EmailAddress': 'smald@umich.edu', 'NSF_ID': '000521349', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}

{'Code': '688400', 'Text': 'Chemical Catalysis'}

2024~490521

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437806.xml'}

EAGER: Development of Multifunctional Molecular Electronics Devices with Tunnel Junctions

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Usha Varshney', 'PO_EMAI': 'uvarshne@nsf.gov', 'PO_PHON': '7032925385'}

Molecular electronics is based on the quantum properties of nanoscale materials and offers unique potential for high density electronic circuitry. This project seeks to advance the science and technology of a basic building block of molecular electronics - the molecular tunnel junction. Tunnel junction devices have a wide range of applications, including detectors, high frequency circuits, and quantum computing, among many others. This project will develop advanced molecular tunnel junction devices with novel functionalities that employ the plasticity and dynamical qualities associated to their molecular nature. These include in-operando reconfigurable molecular switches and optically active molecular devices at the single molecule level for future use in molecular electronic applications. The project encompasses fundamental studies in physics and chemistry as well as device engineering in a broad range of experimental conditions. The broader potential impact of the project resides on complementarity of the expected functionalities of the proposed molecular-based devices with respect to silicon-based technologies. The planned research activities will advance knowledge of fundamental aspects of charge transport in molecular junctions in a variety of experimental conditions, paving the way towards developing operative multifunctional molecular electronic devices. The PI will concentrate efforts to integrate the proposed research with a few educational activities designed to train a diverse next generation of quantum and semiconducting technology workforce. Among these include, high school students participating in summer research internships at UCF and graduate students involved in the collaborative physical science capstone research program who will benefit from the research performed in this project, aiding their training and facilitating their transition to the next career stages and the profession. Graduate student will be trained at the interface between inorganic chemistry and fundamental and applied physics.<br/><br/>This EAGER project focuses on the development of molecular devices with multiple integrated functionalities. The project encompasses theory and experiment in chemistry, physics, device fabrication and technique development. The proposed studies will lead to a better understanding of molecular transport in molecular tunnel junctions, in view of advancing knowledge enabling future technological applications in molecular electronics. The broad goal of this proposal is to investigate charge transport in molecular junctions in a wide range of experimental conditions, in view of designing novel advanced multifunctional molecular devices that employ the plasticity and dynamical qualities of molecular junctions governed by pro-ton-coupled electron transfer processes as well as advance the development of optically active molecular devices for future use in molecular electronic applications. For the first approach, the PI will employ molecules where concerted proton and electron transfer reactions govern the electrical conduction through the tunnel junction, providing the source for the plasticity degree of freedom necessary to obtain devices that integrate hysteretic memory, negative differential conductance, and dynamical on-off states that enable neuromorphic computation solutions, among others. For the second approach, tunnel junctions at the single-molecule level will be fabricated to obtain optically active molecular switches that respond to external illumination stimuli and both bias and gate electrostatic potentials, expanding the accessible electrical and optical energy landscape of current molecular devices. The expected functionalities of the pro-posed molecular-based devices will be complementary to silicon-based technologies, offering a new avenue to significantly advance emerging technologies based on quantum low-dimensional systems. The pro-posed novel multifunctional device solutions uniquely associated to the molecular dynamical/quantum nature of molecular tunnel junctions present disruptive potential in emerging molecular electronics and semiconducting technologies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.041

1

4900

4900

2437811

{'FirstName': 'Enrique', 'LastName': 'del Barco', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Enrique del Barco', 'EmailAddress': 'delbarco@ucf.edu', 'NSF_ID': '000125617', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'ZipCode': '328168005', 'PhoneNumber': '4078230387', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'FL10', 'ORG_UEI_NUM': 'RD7MXJV7DKT9', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF CENTRAL FLORIDA BOARD OF TRUSTEES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'StateCode': 'FL', 'ZipCode': '328168005', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'FL10'}

{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}

2024~273615

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437811.xml'}

CAREER: Elucidating the Interplay Between Exciton Dynamics and Symmetry-Breaking Charge Transfer Through Multidimensional Visible and Mid-Infrared Spectroscopies

NSF

08/15/2024

07/31/2026

{'Value': 'Continuing Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': 'Samy El-Shall', 'PO_EMAI': 'selshall@nsf.gov', 'PO_PHON': '7032927416'}

With support from the Chemical Structure, Dynamics, and Mechanisms-A (CSDM-A) Program in the Division of Chemistry, Dr. Jessica Anna and her group at the University of Pennsylvania are investigating some of the earliest, and most important steps involved in the conversion of sunlight into energy. Solar energy conversion often begins with the transfer of energy or charge between two or more identical molecules that are packed together tightly. The close proximity and identical structures of the molecules make it very difficult to directly observe the first stages of the conversion process. In order to better understand these early events and how they affect solar energy conversion efficiency, Dr. Anna and her research team use sophisticated laser techniques to study pairs of molecules that represent more complicated systems. The team varies the relative distance and orientation of the two molecules in a well-defined way that allows them to distinguish changes caused by subtle differences in the way the two molecules interact with each other. The cutting-edge measurements they make provide new insight to aid in the design and development of new materials for solar energy conversion, including artificial photosynthetic complexes, photocatalysts, and organic photovoltaic materials. The project also involves educational and public outreach activities related to the research, including the development of new teaching modules for integration into graduate, undergraduate, and pre-college classrooms, as well as research opportunities and paid internships for undergraduates, pre-college students, and local area high school teachers. The teaching modules, research opportunities, and paid internships are designed to increase the participation of students in science, technology, engineering, and mathematics (STEM) fields, including underrepresented groups and first-generation college students. <br/><br/>This project focuses on elucidating the interplay between exciton dynamics and charge transfer in a new family of pi-extended metallo-dipyrrin complexes. These systems have the potential to form excitonic states that undergo symmetry-breaking charge transfer, and therefore allow a systematic investigation of the interplay between energy- and charge-transfer processes. Dr. Anna and her students use pump-probe and coherent multidimensional spectroscopy in the visible and mid-IR spectral regions to study the different dipyrrin complexes and obtain a full characterization of the excited-state dynamics, structural rearrangement, and solvent reorganization involved in the symmetry-breaking charge transfer process. The research team uses a mixed spectral approach to probe the evolution of molecules in electronically excited states having charge-transfer character, harnessing the sensitivity of vibrational modes to the local electrostatic field. The team uses pump-probe spectroscopy to characterize population transfer and determine the branching ratios among different excited states in the dipyrrin complexes. The coherent multidimensional spectroscopy measurements provide more detailed information on the dynamics by alleviating spectral congestion, resolving vibrational modes in the excited state, and elucidating solvation dynamics and other relaxation processes. The comprehensive spectroscopic approach yields a deeper understanding of the combined role of intramolecular structural rearrangement and solvation dynamics in symmetry-breaking charge transfer processes that are important for solar energy conversion and other applications.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.049

1

4900

4900

2437814

{'FirstName': 'Jessica', 'LastName': 'Anna', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica M Anna', 'EmailAddress': 'jmanna@pitt.edu', 'NSF_ID': '000753700', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Pittsburgh', 'CityName': 'PITTSBURGH', 'ZipCode': '152600001', 'PhoneNumber': '4126247400', 'StreetAddress': '4200 FIFTH AVENUE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'MKAGLD59JRL1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF PITTSBURGH - OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Pittsburgh', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152600001', 'StreetAddress': '4200 FIFTH AVENUE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}

{'Code': '910100', 'Text': 'CSD-Chem Strcture and Dynamics'}

['2021~47749', '2022~420000']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437814.xml'}

NSF-DFG MISSION: Comprehensive Operando Analysis of Electrolyte-Solid Interface Dynamics for Enhanced Electrocatalytic CO2 Conversion

NSF

01/01/2025

12/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Robert McCabe', 'PO_EMAI': 'rmccabe@nsf.gov', 'PO_PHON': '7032924826'}

Global initiatives aim to significantly reduce carbon dioxide (CO2) emissions by 2030 and achieve net-zero emissions by 2050. Electrocatalytic CO2 reduction (e-CO2RR) has emerged as a promising approach to convert CO2 into valuable chemicals and fuels using renewable electricity. However, current e-CO2RR systems face efficiency and stability limitations that hinder their practical implementation. Copper-based catalysts, while selective towards hydrocarbon production, suffer from performance degradation over extended operation. Leveraging a collaboration between Northwestern University in the US and the Fritz Haber Institute of the Max Planck Society in Germany, this project focuses on developing techniques for studying novel catalysts under realistic operating conditions and integrating advanced synthesis, characterization, and modeling methods to unravel the dynamic changes during reaction. Fundamental understandings gained from this project will provide essential guidance for developing catalysts that can be scaled up for real-world applications and enabling large-scale CO2 utilization for chemical manufacturing and carbon management. Beyond the technical aspects, the investigators are deeply invested in educational and outreach initiatives ranging from elementary school children to post-doctoral researchers. Those efforts will continue under the project, with specific efforts focused on training graduate students in the most advanced microscopy techniques relevant to catalyst design and performance under realistic electrochemical reaction conditions. <br/><br/>The scientific underpinning of this project is to elucidate the dynamics occurring at the catalyst-electrolyte interface for intermetallic nanomaterial (iNM) electrocatalysts during CO2 reduction and to correlate these changes with catalyst performance. This project leverages the synergy between four key components: (1) machine learning-guided design and synthesis of iNM catalysts; (2) operando electron and X-ray microscopy techniques for nanoscale visualization of catalyst evolution, including electrochemical cell transmission electron microscopy (EC-TEM) and transmission X-ray microscopy (TXM); (3) development of in situ liquid cells with ultra-thin membrane windows to enhance spatial resolution and chemical sensitivity, aiming to achieve roughly 1-nm resolution in liquid environments; and (4) integration of real-time product analysis, adapting differential electrochemical mass spectrometry (DEMS) concepts for CO2 reduction. By bridging the gap between atomic-scale structural investigations and practical catalyst performance in CO2 electrolyzers, this research aims to accelerate the development of high-performing iNM-based e-CO2RR systems, potentially transforming the approach to carbon dioxide utilization and sustainable energy production.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2437819

[{'FirstName': 'Vinayak', 'LastName': 'Dravid', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Vinayak P Dravid', 'EmailAddress': 'v-dravid@northwestern.edu', 'NSF_ID': '000206463', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Edward', 'LastName': 'Sargent', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward Sargent', 'EmailAddress': 'ted.sargent@northwestern.edu', 'NSF_ID': '000700481', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'StateCode': 'IL', 'ZipCode': '602083100', 'StreetAddress': '2200 Campus Drive', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2024~599926

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437819.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/14/2024

08/14/2024

None

Grant

47.076

1

4900

4900

2437827

{'FirstName': 'Maria', 'LastName': 'Witte', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria M Witte', 'EmailAddress': 'wittemm@auburn.edu', 'NSF_ID': '000265895', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Auburn University', 'CityName': 'AUBURN', 'ZipCode': '368490001', 'PhoneNumber': '3348444438', 'StreetAddress': '321-A INGRAM HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'AL03', 'ORG_UEI_NUM': 'DMQNDJDHTDG4', 'ORG_LGL_BUS_NAME': 'AUBURN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'DMQNDJDHTDG4'}

{'Name': 'Auburn University', 'CityName': 'Auburn', 'StateCode': 'AL', 'ZipCode': '368490001', 'StreetAddress': '321-A INGRAM HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alabama', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'AL03'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~612000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437827.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437829

{'FirstName': 'William', 'LastName': 'Hockaday', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William C Hockaday', 'EmailAddress': 'william_hockaday@baylor.edu', 'NSF_ID': '000282487', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Baylor University', 'CityName': 'WACO', 'ZipCode': '767061003', 'PhoneNumber': '2547103817', 'StreetAddress': '700 S UNIVERSITY PARKS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '17', 'CONGRESS_DISTRICT_ORG': 'TX17', 'ORG_UEI_NUM': 'C6T9BYG5EYX5', 'ORG_LGL_BUS_NAME': 'BAYLOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Baylor University', 'CityName': 'Waco', 'StateCode': 'TX', 'ZipCode': '767061003', 'StreetAddress': '700 S UNIVERSITY PARKS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '17', 'CONGRESS_DISTRICT_PERF': 'TX17'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~159000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437829.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution<br/>.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/14/2024

08/14/2024

None

Grant

47.076

1

4900

4900

2437833

{'FirstName': 'Charles', 'LastName': 'Rozek', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charles E Rozek', 'EmailAddress': 'cer2@po.cwru.edu', 'NSF_ID': '000326614', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Case Western Reserve University', 'CityName': 'CLEVELAND', 'ZipCode': '441061712', 'PhoneNumber': '2163684510', 'StreetAddress': '10900 EUCLID AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'OH11', 'ORG_UEI_NUM': 'HJMKEF7EJW69', 'ORG_LGL_BUS_NAME': 'CASE WESTERN RESERVE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Case Western Reserve University', 'CityName': 'Cleveland', 'StateCode': 'OH', 'ZipCode': '441061712', 'StreetAddress': '10900 EUCLID AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'OH11'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~422000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437833.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/14/2024

08/26/2024

None

Grant

47.076

1

4900

4900

2437834

[{'FirstName': 'Deborah', 'LastName': 'Martin', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Deborah G Martin', 'EmailAddress': 'demartin@clarku.edu', 'NSF_ID': '000328553', 'StartDate': '08/14/2024', 'EndDate': '08/26/2024', 'RoleCode': 'Former Principal Investigator'}, {'FirstName': 'Lisa', 'LastName': 'Gaudette', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lisa Gaudette', 'EmailAddress': 'lgaudette@clarku.edu', 'NSF_ID': '000629310', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Clark University', 'CityName': 'WORCESTER', 'ZipCode': '016101400', 'PhoneNumber': '5084213835', 'StreetAddress': '950 MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'LD3WUVEUK2N5', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF CLARK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clark University', 'CityName': 'Worchester', 'StateCode': 'MA', 'ZipCode': '016101400', 'StreetAddress': '950 MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~53000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437834.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/14/2024

08/14/2024

None

Grant

47.076

1

4900

4900

2437839

{'FirstName': 'Carlos', 'LastName': 'Alonso', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carlos Alonso', 'EmailAddress': 'calonso@columbia.edu', 'NSF_ID': '000582098', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'ZipCode': '100277922', 'PhoneNumber': '2128546851', 'StreetAddress': '615 W 131ST ST', 'StreetAddress2': 'MC 8741', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'F4N1QNPB95M4', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Columbia University', 'CityName': 'New York', 'StateCode': 'NY', 'ZipCode': '100277922', 'StreetAddress': '615 W 131ST ST MC 8741', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~5044932

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437839.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437840

{'FirstName': 'Jean-Luc', 'LastName': 'Scemama', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jean-Luc Scemama', 'EmailAddress': 'scemamaj@ecu.edu', 'NSF_ID': '000255072', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'East Carolina University', 'CityName': 'GREENVILLE', 'ZipCode': '278582502', 'PhoneNumber': '2523289530', 'StreetAddress': '1000 E 5TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NC01', 'ORG_UEI_NUM': 'HWPEKM8VFTJ9', 'ORG_LGL_BUS_NAME': 'EAST CAROLINA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'East Carolina University', 'CityName': 'Greenville', 'StateCode': 'NC', 'ZipCode': '278582502', 'StreetAddress': '1000 E 5TH ST GREENVILLE, NC', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NC01'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~159000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437840.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution<br/>.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437844

{'FirstName': 'Mark', 'LastName': 'Riley', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mark A Riley', 'EmailAddress': 'mriley@nucmar.physics.fsu.edu', 'NSF_ID': '000347221', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Florida State University', 'CityName': 'TALLAHASSEE', 'ZipCode': '323060001', 'PhoneNumber': '8506445260', 'StreetAddress': '874 TRADITIONS WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'FL02', 'ORG_UEI_NUM': 'JF2BLNN4PJC3', 'ORG_LGL_BUS_NAME': 'FLORIDA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Florida State University', 'CityName': 'Tallahassee', 'StateCode': 'FL', 'ZipCode': '323060001', 'StreetAddress': '874 TRADITIONS WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'FL02'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~204123

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437844.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437845

{'FirstName': 'Scott', 'LastName': "D'Urso", 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': "Scott C D'Urso", 'EmailAddress': 'scott.durso@marquette.edu', 'NSF_ID': '0000A04RW', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Marquette University', 'CityName': 'MILWAUKEE', 'ZipCode': '532332244', 'PhoneNumber': '4142887200', 'StreetAddress': '313 N 13TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'WI04', 'ORG_UEI_NUM': 'HKJCKTFJNBM7', 'ORG_LGL_BUS_NAME': 'MARQUETTE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Marquette University', 'CityName': 'Milwaukee', 'StateCode': 'WI', 'ZipCode': '532332244', 'StreetAddress': '313 N 13TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'WI04'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~106000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437845.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

09/01/2024

08/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.076

1

4900

4900

2437847

{'FirstName': 'Will', 'LastName': 'Cantrell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Will Cantrell', 'EmailAddress': 'cantrell@mtu.edu', 'NSF_ID': '000349433', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan Technological University', 'CityName': 'HOUGHTON', 'ZipCode': '499311200', 'PhoneNumber': '9064871885', 'StreetAddress': '1400 TOWNSEND DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MI01', 'ORG_UEI_NUM': 'GKMSN3DA6P91', 'ORG_LGL_BUS_NAME': 'MICHIGAN TECHNOLOGICAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'GKMSN3DA6P91'}

{'Name': 'Michigan Technological University', 'CityName': 'HOUGHTON', 'StateCode': 'MI', 'ZipCode': '499311200', 'StreetAddress': '1400 TOWNSEND DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MI01'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~159000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437847.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

09/01/2024

08/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/23/2024

08/23/2024

None

Grant

47.076

1

4900

4900

2437848

{'FirstName': 'Robert', 'LastName': 'Coleman', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert A Coleman', 'EmailAddress': 'Robert.Coleman2@einsteinmed.edu', 'NSF_ID': '000939443', 'StartDate': '08/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Albert Einstein College of Medicine', 'CityName': 'Bronx', 'ZipCode': '104611900', 'PhoneNumber': '7184302668', 'StreetAddress': '1300 MORRIS PARK AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_ORG': 'NY14', 'ORG_UEI_NUM': 'H6N1ZF5HJ2G3', 'ORG_LGL_BUS_NAME': 'ALBERT EINSTEIN COLLEGE OF MEDICINE', 'ORG_PRNT_UEI_NUM': 'SFMSA57QK2B1'}

{'Name': 'Albert Einstein College of Medicine', 'CityName': 'Bronx', 'StateCode': 'NY', 'ZipCode': '104611900', 'StreetAddress': '1300 MORRIS PARK AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_PERF': 'NY14'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~53000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437848.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437850

{'FirstName': 'Ralph', 'LastName': 'Albano', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ralph Albano', 'EmailAddress': 'albano@cua.edu', 'NSF_ID': '000100969', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Catholic University of America', 'CityName': 'WASHINGTON', 'ZipCode': '200640001', 'PhoneNumber': '2026355000', 'StreetAddress': '620 MICHIGAN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'C31ES3WEAVQ5', 'ORG_LGL_BUS_NAME': 'CATHOLIC UNIVERSITY OF AMERICA (THE)', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Catholic University of America', 'CityName': 'Washington', 'StateCode': 'DC', 'ZipCode': '200640001', 'StreetAddress': '620 MICHIGAN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~53000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437850.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Joel Schildbach', 'PO_EMAI': 'jschildb@nsf.gov', 'PO_PHON': '7032920000'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437851

{'FirstName': 'Brian', 'LastName': 'Feinstein', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brian Feinstein', 'EmailAddress': 'brian.feinstein@rosalindfranklin.edu', 'NSF_ID': '000963386', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'ROSALIND FRANKLIN UNIVERSITY OF MEDICINE AND SCIENCE', 'CityName': 'NORTH CHICAGO', 'ZipCode': '600643037', 'PhoneNumber': '8475788524', 'StreetAddress': '3333 GREEN BAY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'IL10', 'ORG_UEI_NUM': 'V913TCT2SFZ9', 'ORG_LGL_BUS_NAME': 'ROSALIND FRANKLIN UNIVERSITY OF MEDICINE & SCIENCE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'ROSALIND FRANKLIN UNIVERSITY OF MEDICINE AND SCIENCE', 'CityName': 'North Chicago', 'StateCode': 'IL', 'ZipCode': '600643037', 'StreetAddress': '3333 GREEN BAY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'IL10'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~53000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437851.xml'}

Graduate Research Fellowship Program (GRFP)

NSF

08/15/2024

07/31/2029

{'Value': 'Fellowship Award'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.076

1

4900

4900

2437852

{'FirstName': 'Daniel', 'LastName': 'Crocker', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel E Crocker', 'EmailAddress': 'crocker@sonoma.edu', 'NSF_ID': '000258520', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Sonoma State University', 'CityName': 'ROHNERT PARK', 'ZipCode': '949283613', 'PhoneNumber': '7076643972', 'StreetAddress': '1801 E COTATI AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'GZ6NCMJFL6R4', 'ORG_LGL_BUS_NAME': 'SONOMA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Sonoma State University', 'CityName': 'ROHNERT PARK', 'StateCode': 'CA', 'ZipCode': '949283613', 'StreetAddress': '1801 E COTATI AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}

{'Code': '717200', 'Text': 'Graduate Research Fellowship'}

2024~53000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437852.xml'}

EAGER: Integrating Small and Medium Sized Manufacturing Enterprises (SMEs) into the Next Generation Manufacturing Ecosystems for National Security and Self Sufficiency

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Janis Terpenny', 'PO_EMAI': 'jterpenn@nsf.gov', 'PO_PHON': '7032922487'}

This EArly-concept Grant for Exploratory Research (EAGER) project focuses on establishing rigorous foundational artificial intelligence and network science-based strategies to represent data, build search strategies, and help form clusters of Small and Medium Manufacturing Enterprises (SMEs) to meet production demands. SMEs form the backbone of our country’s economic prosperity, community welfare, and self-sufficiency. Strengthening the USA’s manufacturing base will help in the nation to become less dependent on global supply chains, thus helping national security and self-sufficiency. However, finding and selecting relevant SMEs for a specific product currently requires manual consultation of databases, manual collation of data, and compiling information which is not ideal in the age of information explosion. This research will help establish the scientific foundation for representing SMEs data, provide for distilling the relevant information about the SMEs of user’s interest, and facilitate building collaborations among SMEs. By providing such methodologies, this effort will help enhance an indigenous manufacturing base. This award will also result in enhanced national security by providing efficient provenances for all manufactured products. Many SMEs in the USA tend to have 3rd or 4th generation workers and are predominantly rurally located. The efforts from this award will help in establishing a platform for the manufacturing ecosystems for the future wherein diverse SMEs irrespective of location and scale, will have an equal opportunity to participate.<br/><br/>The research focus is on using a network science-based representation to connect SMEs as graph database formalisms that offer representation power, help build efficient search mechanisms, and offer intuitive methods to connect SMEs to fulfill the demand that cannot be met by a single provider. Machine learning and economic theory based foundational algorithms resulting from this research will help in creating optimal search and coalition formation among SMEs. The scientific foundations of this research will be developed through SME inspired use cases, thus addressing both theoretical and engineering considerations to make this research generalizable to all SMEs. By the nature of design, the methodologies will help build a high level of data security and long-term sustainability of the ensuing platform. This award will address: 1) data models for representing SMEs, 2) search mechanisms to find SMEs based on specific contexts, 3) composition of SMEs to meet the requirements of larger enterprises in an economic and sustainable manner, and 4) federated learning schemes to recommend relevant SMEs for specific contexts. Graph databases offer a unique representation formalism that is dynamic, flexible, and scalable, making them suitable for addressing these research problems. Additionally, game theoretic and auction-based mechanisms will be used to compose SMEs and help in supplier selection. Real-time issues, dynamic updates, and scaling up of computational considerations are considered in this research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.041

1

4900

4900

2437873

[{'FirstName': 'Paul', 'LastName': 'Griffin', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Paul M Griffin', 'EmailAddress': 'pmg14@psu.edu', 'NSF_ID': '000567546', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kamesh', 'LastName': 'Madduri', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kamesh Madduri', 'EmailAddress': 'madduri@cse.psu.edu', 'NSF_ID': '000598267', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Soundar', 'LastName': 'Kumara', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Soundar R Kumara', 'EmailAddress': 'skumara@psu.edu', 'NSF_ID': '000288942', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'ZipCode': '168021503', 'PhoneNumber': '8148651372', 'StreetAddress': '201 OLD MAIN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_ORG': 'PA15', 'ORG_UEI_NUM': 'NPM2J7MSCF61', 'ORG_LGL_BUS_NAME': 'THE PENNSYLVANIA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Pennsylvania State Univ University Park', 'CityName': 'UNIVERSITY PARK', 'StateCode': 'PA', 'ZipCode': '168021503', 'StreetAddress': '201 OLD MAIN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'PA15'}

{'Code': '229Y00', 'Text': 'MSI-Manufacturing Systms Integ'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437873.xml'}

Development of advanced quantitative tools for laser radiation safety evaluation in laser urology

NSF

05/01/2024

11/30/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Adam Wax', 'PO_EMAI': 'awax@nsf.gov', 'PO_PHON': '7032928809'}

Laser lithotripsy is the most common procedure to treat urinary stones. In this procedure, a small flexible endoscope is introduced up the urinary tract to the location of a stone. An optical fiber is passed through the endoscope and the tip is placed near the stone. High-energy laser pulses are delivered through the optical fiber to the tip. The laser energy transmitted to the stone breaks it into small pieces that can pass through the urinary tract. Recently, high-power laser systems have been created that make the procedure easier, shortening operating time and producing smaller fragments. However, the energy from these high-power lasers turns into heat that can damage kidney and other tissues. The FDA and the public health community do not presently have standard regulatory science tools for safety evaluation of laser lithotripsy devices. The objective of this project is to develop advanced tools to be used by industry, researchers and regulatory groups to evaluate heating from these lasers to improve the safety of future devices. This project will perform computer simulations and lab experiments to identify how heating is impacted by different laser characteristics. The project will create a database to identify safe power limits, and guidance documentation for evaluating new devices. It will also involve training future scientists and engineers in regulatory science, and educating physician and medical student groups on these effects. The project will support public health by reducing the risk of serious complications during these procedures and introduce protocols for safe use.<br/><br/>Laser lithotripsy is the most common intervention for urinary stones, where a laser fiber is passed through an endoscope to deliver pulsed laser energy causing stone fragmentation. The recent introduction of high-power laser systems has expanded the capabilities of laser lithotripsy. However, higher laser power presents a risk of overheating the calyceal fluid and tissue. The impact of various physical, biological, and operator factors on this thermal effect is unknown. Furthermore, the biological sequelae from thermal injury to these tissues are not fully characterized. The FDA and public health community are lacking standard test tools, test protocols and guidance documents for laser radiation safety evaluation of these technologies. The objective of this project is to develop advanced quantitative regulatory science tools to evaluate photothermal effects to the urinary tract during laser lithotripsy and improve the safety of future devices. A computational finite-element model for laser lithotripsy will be developed to simulate physical processes of laser-induced heating, as well as laser, irrigation, and gravity induced fluid flow within the urinary tract to determine the spatiotemporal distributions of heat and pressure. The models will include realistic parameters of the biological fluids and tissues. The models will be used to simulate clinically relevant scenarios of laser lithotripsy to assess and predict thermal and pressure effects to the tissues, and a database will be defined for relevant limits of the exposure parameters required to produce bioeffects. Finally, guidance documents will be produced for evaluating future devices and exposure scenarios.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/18/2024

07/18/2024

None

Grant

47.041

1

4900

4900

2437884

{'FirstName': 'Adam', 'LastName': 'Maxwell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adam Maxwell', 'EmailAddress': 'amax38@uw.edu', 'NSF_ID': '000928055', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}

{'Code': '723600', 'Text': 'BioP-Biophotonics'}

2023~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437884.xml'}

Conference: 2024 NY RNA Symposium in The Finger Lakes

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Manju Hingorani', 'PO_EMAI': 'mhingora@nsf.gov', 'PO_PHON': '7032927323'}

This award will support The NY 2024 RNA Meeting in the Finger Lakes to be held on October 13th-15th, 2024. The meeting will include participants from a wide range of career stages and research areas, including undergraduates, graduate students, postdoctoral fellows, principal investigators, and scientists in the biotechnology industry. It will be organized through the joint efforts of the Center for RNA Biology at The University of Rochester and the RNA Institute at The State University of New York at Albany. The meeting provides an opportunity to bring together leaders in the field of RNA biology with new investigators and trainees at multiple career levels to present, discuss, and disseminate their work. The conference affords a rich opportunity for broader impacts on the community through (i) participation of diverse researchers, including from groups underrepresented in STEM fields, (ii) advancement of STEM education, and (iii) development of a diverse and competitive STEM workforce by catalyzing partnerships between researchers in the academia and industry.<br/><br/>The format of this meeting is designed to maximize attendee exposure to the frontiers of RNA biology through seminars from invited speakers on a range of topics, ‘lightning’ talks by trainees, an extensive poster session, and many opportunities for informal conversations. The meeting topics include nascent RNA metabolism, structural RNA biology, RNA in neuroscience, CRISPR biology, RNA therapeutics, and RNA vaccine development. Meeting participants will thus be immersed in a broad swath of contemporary interests driving RNA biology both in academia and the biotechnology industry.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/19/2024

07/19/2024

None

Grant

47.074

1

4900

4900

2437889

{'FirstName': 'Eric', 'LastName': 'Wagner', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric J Wagner', 'EmailAddress': 'Eric_Wagner@urmc.rochester.edu', 'NSF_ID': '000981067', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Rochester', 'CityName': 'ROCHESTER', 'ZipCode': '146113847', 'PhoneNumber': '5852754031', 'StreetAddress': '910 GENESEE ST', 'StreetAddress2': 'STE 200', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'F27KDXZMF9Y8', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ROCHESTER', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Rochester', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146113847', 'StreetAddress': '910 GENESEE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}

{'Code': '111200', 'Text': 'Genetic Mechanisms'}

2024~12000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437889.xml'}

Conference: CI PAOS: BRICCs-RDM: Exploring Research Data Management Practices in Cyberinfrastructure

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}

{'SignBlockName': 'Plato Smith', 'PO_EMAI': 'plsmith@nsf.gov', 'PO_PHON': '7032924278'}

Building Research Innovation at Community Colleges - Research Data Management (BRICCs-RDM) is a unique workshop that leverages the growing BRICCs community to understand how RDM can be used to advance CI-enabled scientific use-cases in academic research. The workshop will work to identify clear strategies to ensure support and access from all stakeholder communities who produce and consume data on CI resources.<br/><br/>Ensuring equitable access to research Cyberinfrastructure (CI) is critical to scientific discovery. The richness of the CI landscape has given researchers opportunities to incorporate computational approaches in their research workflows in their own unique ways. While fields of science like drug design have focused on speeding numerical simulations using GPUs, others like economic forecasting rely on artificial intelligence approaches to consolidate data from documents to build models. Much like computing, research data too is produced and consumed in different ways by researchers. While fields like astrophysics and large visual models (LVMs) have large community data sets, others like social sciences may have smaller but equally valuable data sets. To support these seemingly divergent approaches, research data management practices that can support sophisticated advanced CI technologies are needed. The CI community needs to go beyond supporting container-based workflows for scientific reproducibility, and address the increasingly complex data-management challenges faced by researchers. Researchers should be able to store and share data in ways that will foster innovation and support technological advances. Data repositories and CI-adjacent storage need to ensure that the data is Findable, Accessible, Interoperable, and Reusable (FAIR). Care should be taken to ensure that these advances support the needs of different scientific domains. Toward this, the community needs to identify the challenges, gaps, and opportunities that can inform RDM practices in research computing efforts at the campus, regional, and national levels.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.070

1

4900

4900

2437898

[{'FirstName': 'Tabitha', 'LastName': 'Samuel', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tabitha K Samuel', 'EmailAddress': 'tsamuel@utk.edu', 'NSF_ID': '000656402', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lisa', 'LastName': 'Perez', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lisa M Perez', 'EmailAddress': 'perez@tamu.edu', 'NSF_ID': '000684096', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Dhruva', 'LastName': 'Chakravorty', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dhruva Chakravorty', 'EmailAddress': 'chakravorty@tamu.edu', 'NSF_ID': '000718169', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lizely', 'LastName': 'Madrigal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lizely Madrigal', 'EmailAddress': 'lmadriga@nmsu.edu', 'NSF_ID': '000946210', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKY S STE 30', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'JF6XLNB4CDJ5', 'ORG_LGL_BUS_NAME': 'TEXAS A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Texas A&M University', 'CityName': 'College Station', 'StateCode': 'TX', 'ZipCode': '778430001', 'StreetAddress': '3361 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}

{'Code': '741400', 'Text': 'NSF Public Access Initiative'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437898.xml'}

EAGER: CI PAOS: KnowLedger: An Open Digital Research Notebook for Research Data Management

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}

{'SignBlockName': 'Plato Smith', 'PO_EMAI': 'plsmith@nsf.gov', 'PO_PHON': '7032924278'}

This project focuses on creation of an open ecosystem, KnowLedger, through developing a suite of components needed for an open digital research notebook (DRN) that will nominally serve all research communities, putting the control of the development in the hands of the research community (as far as possible), promoting data science/informatics as an important part of all research activities, and encouraging research data sharing and reuse. KnowLedger is envisioned to be a complete rethink of what a research notebook should be able to do, enabling new ways to record data/take notes, connect with online resources, and flexible so it can be tailored to the needs of the science and the scientific workflow.<br/><br/>Giving researchers the ability within KnowLedger to develop resources they need for RDM in an open and free ecosystem is anticipated to encourage contribution to/participation in its development and garner suggestions for configuration options and functionality broadly. The ecosystem will be developed as an open and distributed model using GitHub repositories as hubs for community development of data access/data analysis modules, data templates (including minimum metadata standards), and research workflows. The goal is to outline an approach, setup several key resources, provide ideas of how the ecosystem could be setup, and enable the research community to; understand the idea, see the future of RDM, galvanize their disciplines into action, and leverage their disciplines’ available funding for community needs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.070

1

4900

4900

2437951

{'FirstName': 'Stuart', 'LastName': 'Chalk', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stuart J Chalk', 'EmailAddress': 'schalk@unf.edu', 'NSF_ID': '000095187', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of North Florida', 'CityName': 'JACKSONVILLE', 'ZipCode': '322247699', 'PhoneNumber': '9046202455', 'StreetAddress': '1 U N F DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'FL05', 'ORG_UEI_NUM': 'MHM6MGJFANE7', 'ORG_LGL_BUS_NAME': 'UNIVERISTY OF NORTH FLORIDA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of North Florida', 'CityName': 'JACKSONVILLE', 'StateCode': 'FL', 'ZipCode': '322247699', 'StreetAddress': '1 U N F DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'FL05'}

{'Code': '741400', 'Text': 'NSF Public Access Initiative'}

2024~299776

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437951.xml'}

EAGER: Collaborative Research: Fostering Collective Rationality Among Self-Interested Agents to Improve Design and Efficiency of Mixed Autonomy Networks and Infrastructure Systems

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Siqian Shen', 'PO_EMAI': 'siqshen@nsf.gov', 'PO_PHON': '7032927048'}

This EArly-Concept Grants for Exploratory Research (EAGER) project will investigate the emergence, mechanisms, and applications of collective rationality (CR) among self-interested agents in the design of mixed autonomy networks and infrastructure systems. In many natural and engineering systems, various collective phenomena, such as spontaneous cooperation, spatial segregation, and behavior evolution and formation of social norms, can emerge at system level when the decisions and maneuvers of self-interested agents interlace with each other. Strategic agent behaviors play a key role in this process. This observation suggests that one may obtain a system with desired properties by carefully designing behaviors of its agents. The research will explore this idea and put forward the concept of “collective rationality” of mixed traffic towards with the intent of explaining the formation of cooperation among self-interested driving agents in mixed autonomy transportation systems, to reduce travel cost, uncertainties, fuel emission, as well as to enhance equity among all road users. Broader applications include autonomous vehicle behavior design, emergency evacuation, and mitigation of pandemic spread. The research will be further disseminated through curriculum design, K-12 education, and collaboration with practitioners, local government, and industry partners. <br/><br/>This research project will explore and rigorously define the concept of collective rationality in mixed traffic and its application in designing strategic behaviors of autonomous driving agents in mixed autonomy environments. The core research hypothesis is that collective rationality can emerge in broad scenarios even if the involved agents are self-interested. Game theory and reinforcement learning will be leveraged to verify this hypothesis theoretically and computationally. To establish theoretical models of collective rationality in mixed traffic, two classes of models with different levels of agent behavior details will be developed, respectively focusing on the one-shot interaction of n-class driving agents, and dynamic inter- and intra-class interactions and an analytical Fokker-Planck approximation to the corresponding evolution dynamics. To develop frameworks for collective rationality-informed autonomous vehicle behavior design, researchers will consider two autonomous vehicle behavior design frameworks using reinforcement learning, which incorporate collective rationality in reward design and employ a bi-level pricing structure to equitably fine-tune the benefit of cooperation among agents. The research team will also expand and explore the CR concept for other application contexts, such disaster evacuations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2437982

{'FirstName': 'Jia', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jia Li', 'EmailAddress': 'jia.li1@wsu.edu', 'NSF_ID': '000756687', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Washington State University', 'CityName': 'PULLMAN', 'ZipCode': '991640001', 'PhoneNumber': '5093359661', 'StreetAddress': '240 FRENCH ADMINISTRATION BLDG', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'WA05', 'ORG_UEI_NUM': 'XRJSGX384TD6', 'ORG_LGL_BUS_NAME': 'WASHINGTON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Washington State University', 'CityName': 'PULLMAN', 'StateCode': 'WA', 'ZipCode': '991640001', 'StreetAddress': '240 FRENCH ADMINISTRATION BLDG', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'WA05'}

{'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}

2024~154063

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437982.xml'}

EAGER: Collaborative Research: Fostering Collective Rationality Among Self-Interested Agents to Improve Design and Efficiency of Mixed Autonomy Networks and Infrastructure Systems

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Siqian Shen', 'PO_EMAI': 'siqshen@nsf.gov', 'PO_PHON': '7032927048'}

This EArly-Concept Grants for Exploratory Research (EAGER) project will investigate the emergence, mechanisms, and applications of collective rationality (CR) among self-interested agents in the design of mixed autonomy networks and infrastructure systems. In many natural and engineering systems, various collective phenomena, such as spontaneous cooperation, spatial segregation, and behavior evolution and formation of social norms, can emerge at system level when the decisions and maneuvers of self-interested agents interlace with each other. Strategic agent behaviors play a key role in this process. This observation suggests that one may obtain a system with desired properties by carefully designing behaviors of its agents. We explore this idea and put forward the concept of “collective rationality” of mixed traffic towards explaining the formation of cooperation among self-interested driving agents in mixed autonomy transportation systems, to reduce travel cost, uncertainties, fuel emission, as well as to enhance equity among all road users. Broader applications include autonomous vehicle behavior design, emergency evacuation, and mitigation of pandemic spreading. The research will be further disseminated through curriculum design, K-12 education, and collaboration with practitioners, local government, and industry partners. <br/><br/>This project will explore and rigorously define the concept of collective rationality in mixed traffic and explore its application in designing strategic behaviors of autonomous driving agents in mixed autonomy environments. Our core hypothesis is that collective rationality can emerge in broad scenarios even if the involved agents are self-interested. We will leverage game theory and reinforcement learning to verify this hypothesis theoretically and computationally. To establish theoretical models of collective rationality in mixed traffic, we will develop two classes of models with different levels of agent behavior details, respectively focusing on the one-shot interaction of n-class driving agents, and dynamic inter- and intra-class interactions and an analytical Fokker-Planck approximation to the corresponding evolution dynamics. To develop frameworks for collective rationality-informed autonomous vehicle behavior design, we consider two autonomous vehicle behavior design frameworks using reinforcement learning, which incorporate collective rationality in reward design and employ a bi-level pricing structure to equitably fine-tune the benefit of cooperation among agents. The research team will also expand and explore the CR concept in other application contexts such disaster evacuations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2437983

{'FirstName': 'Michael', 'LastName': 'Zhang', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael H Zhang', 'EmailAddress': 'hmzhang@ucdavis.edu', 'NSF_ID': '000491178', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'ZipCode': '956186153', 'PhoneNumber': '5307547700', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'TX2DAGQPENZ5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, DAVIS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'StateCode': 'CA', 'ZipCode': '956186153', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}

{'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}

2024~145305

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437983.xml'}

Mathposium: Student Research Symposium and Peer Mentoring Network

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '11040100', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}

{'SignBlockName': 'Mike Ferrara', 'PO_EMAI': 'mferrara@nsf.gov', 'PO_PHON': '7032922635'}

This project serves the national interest by providing undergraduate and graduate students in the mathematical sciences with professional development, mentoring, and deeper exposure to research opportunities. Specifically, this project will support the third offering of the Mathposium, a two-day student-organized conference at the University of Texas at Arlington, an Hispanic Serving Institution (HSI). Building from two prior, local offerings the 2024 conference will include the following activities for student participants: (1) student poster presentations; (2) lightning talks; (3) panels on careers and student research opportunities; and (4) vertical mentoring experiences and a networking lunch. Marketing and outreach activities will focus on institutions in Texas, Louisiana, and Oklahoma, although participants from any institution will be welcome to participate. A particular emphasis will be placed on encouraging participation of students from community colleges, HSIs, and HBCUs. <br/><br/>This conference looks to provide mentoring and networking opportunities to promote access to opportunities for all students, including first-generation college students and members of populations that have traditionally been underrepresented in mathematics degree programs. The main goals of the conference are as follows: (1) expose undergraduates to mathematics research and current topics in the discipline; engage undergraduates and graduate students in activities designed to provide opportunities for mentoring; (3) create a friendly and inclusive environment around mathematics; and (4) allow student participants to share their research through posters and lightning talks. The conference will also include a faculty workshop on mentoring students for non-academic careers. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM learning at HSIs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.076

1

4900

4900

2437995

[{'FirstName': 'Theresa', 'LastName': 'Jorgensen', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Theresa A Jorgensen', 'EmailAddress': 'jorgensen@uta.edu', 'NSF_ID': '000505186', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Talon', 'LastName': 'Johnson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Talon Johnson', 'EmailAddress': 'taloneverrettjohnson@gmail.com', 'NSF_ID': '000857599', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Darsh', 'LastName': 'Gandhi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Darsh Gandhi', 'EmailAddress': 'dxg5343@mavs.uta.edu', 'NSF_ID': '0000A0F5G', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}

{'Code': '077Y00', 'Text': 'HSI-Hispanic Serving Instituti'}

2024~29375

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2437995.xml'}

Collaborative Research: AF: Small: A Unified Framework for Analyzing Adaptive Stochastic Optimization Methods Based on Probabilistic Oracles

NSF

07/01/2024

12/31/2024

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': 'kwimmer@nsf.gov', 'PO_PHON': '7032922095'}

Data science and machine learning have transformed modern science, engineering, and business. One of the pillars of modern-day machine-learning technology is mathematical optimization, which is the methodology that drives the process of learning from available and/or real-time generated data. Unfortunately, however, despite the successes of certain optimization techniques, large-scale learning remains extremely expensive in terms of time and energy, which puts the ability to train machines to perform certain fundamental tasks exclusively in the hands of those with access to extreme-scale supercomputing facilities. A significant deficiency of many contemporary techniques is that they "launch" an algorithm with a prescribed "trajectory," despite the fact that the actual trajectory that the algorithm will follow depends on unknown factors. Contemporary optimization techniques for machine learning essentially account for this by "tuning" algorithmic parameters, which means that the target is typically only hit after numerous expensive misses. Another significant deficiency of contemporary techniques is the restrictive set of assumptions often made about the optimization being performed, which typically includes the assumption that the machine-learning model is being trained with uncorrupted data. Modern real-world applications are far more complex.<br/><br/>This project will explore the design and analysis of adaptive ("self-tuning") optimization techniques for machine learning and related topics. One goal is to produce adaptive algorithms with rigorous guarantees that can avoid the extreme amounts of wasteful computation that are required by contemporary algorithms for parameter tuning. Another goal is to extend the use of these algorithms to settings with imperfect data/information, which may be due to biased function information, corrupted data, or novel techniques for approximating the objective. Finally, many applications ultimately require the learning process or model to satisfy some explicit or implicit constraints. Optimization methods for such machine-learning applications are still in their infancy, largely due to their more complicated nature and further dependence on algorithmic parameters. This project aims to design a unified framework for analyzing adaptive stochastic optimization methods that will offer researchers and practitioners a set of easy-to-use tools for designing next-generation algorithms for cutting-edge applications.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.070

1

4900

4900

2438005

{'FirstName': 'Katya', 'LastName': 'Scheinberg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katya Scheinberg', 'EmailAddress': 'katyascheinberg@gmail.com', 'NSF_ID': '000544723', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}

{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303186395', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}

{'Code': '779600', 'Text': 'Algorithmic Foundations'}

2022~108000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438005.xml'}

CAREER: Dynamic connectivity: a research and educational frontier for sustainable environmental management under climate and land use uncertainty

NSF

08/15/2024

07/31/2029

{'Value': 'Continuing Grant'}

{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

Dynamic landscapes represent a network of hydrologic, environmental, and anthropogenic features that work in tandem to confer ecosystem benefits and provide for societal demands. Increasingly, landscapes are at risk under the growing pressures of land use alteration and climate change. Understanding how landscapes dynamically connect the transfer of water, sediment, and nutrients to rivers and the role humans play in modulating this connectivity is crucial if we are to sustainably manage our shared water resources. Thus, the driving questions behind this work are “how have humans changed the landscapes around us for the worse and how are we able to manage them for the better?” This project will answer these questions and advance the frontiers of research and education for sustainable water management by coupling agricultural, municipal, and stormwater expertise together with high-frequency aquatic sensing, deep learning modeling, and large-sample water quality datasets. This research will generate fundamental scientific advances to identify the magnitude, duration, and extent of landscape loading to river systems across climatological, geomorphic, and anthropogenic settings. The education of today’s students, who will become tomorrow’s stakeholders, is deeply embedded in this project through hands-on experiences that will equip them with the confidence and communication skills to handle big data and tackle society’s grandest water challenges. <br/><br/>Contemporary research in hydrologic sciences recognizes the importance of connectivity in most aspects of the water cycle; however, despite its ubiquity, connectivity is often assessed either qualitatively or in a static, structural context. The proposed research has the potential to be transformative in moving toward a dynamic assessment of connectivity. This project will quantify dynamic connectivity through time and across space for the United States. This will be achieved by leveraging high-frequency aquatic sensors for nitrate and turbidity from over 150 rivers, which serve as training data for a deep learning model. Further, a mathematical description of dynamic connectivity will inform dominant pathways of connection. Explainable machine learning techniques will link how dynamic landscape attributes lead to riverine water quality impacts. Thereafter, the potential to use dynamic connectivity as a management tool will be assessed through a web application developed for practitioners. The outcomes will lead directly into the education and training of the stakeholders-of-tomorrow, including through building big data confidence in high school settings and science communication skills in college students.<br/><br/>This project is jointly funded by Hydrologic Sciences and the Established Program to Stimulate Competitive Research (EPSCoR).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.050

1

4900

4900

2438017

{'FirstName': 'Admin', 'LastName': 'Husic', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Admin Husic', 'EmailAddress': 'husic@vt.edu', 'NSF_ID': '000820493', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}

{'Code': '157900', 'Text': 'Hydrologic Sciences'}

2024~67705

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438017.xml'}

NSF-SSRC: Sociodemographic Influences on Vaccine Decision-Making

NSF

07/01/2024

06/30/2026

{'Value': 'Continuing Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Jeffrey Mantz', 'PO_EMAI': 'jmantz@nsf.gov', 'PO_PHON': '7032927783'}

Healthcare decisions, including decisions to vaccinate, are an amalgamation of complex cultural, social, and psychological interactions, including perceptions of risk, trust in healthcare, locally relevant norms of behavior, and social learning. Understanding both the drivers of vaccine decision making is crucial to alleviating the burden of disease and increasing vaccine uptake. In particular, more work is needed from underserved communities, which tend to have disproportionate vulnerabilities and disease burden. In addition to potential impacts on public health and public policy, this study facilitates training of a diverse group of graduate and undergraduate students, including groups typically underrepresented in STEM research.<br/><br/>This study takes a multi-modal approach to studying health care decision-making, particularly around the acceptance and uptake of vaccines. The team examines: (1) how local models of illness shape vaccination practice, (2) how individual-level factors, including medical mistrust, shape perceptions and use of the healthcare system, (3) how sociodemographic factors shape vaccine beliefs, and (4) how social learning influences individual vaccination decisions. To do this the team uses a mix of interviews, surveys and focus groups, along with innovative vignette studies designed specifically for this study. This multi-layered approach to understanding vaccination is rare in health sciences, and should highlight the value of an anthropological approach to the study of vaccination.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

08/27/2024

None

Grant

47.075

1

4900

4900

2438025

[{'FirstName': 'Brooke', 'LastName': 'Scelza', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brooke A Scelza', 'EmailAddress': 'bscelza@anthro.ucla.edu', 'NSF_ID': '000539999', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sean', 'LastName': 'Prall', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sean Prall', 'EmailAddress': 'sprall@me.com', 'NSF_ID': '000918794', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'The Regents of the University of California, Los Angeles', 'CityName': 'LOS ANGELES', 'StateCode': 'CA', 'ZipCode': '900951553', 'StreetAddress': 'BOX 951553, 385 Haines Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_PERF': 'CA36'}

[{'Code': '139000', 'Text': 'Cultural Anthropology'}, {'Code': '139700', 'Text': 'Cross-Directorate Activities'}]

['2023~295039', '2024~147439']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438025.xml'}

Conference: Online Undergraduate Resource Fair for the Advancement and Alliance of Marginalized Mathematicians (OURFA2M2)

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '11040000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}

{'SignBlockName': 'Mike Ferrara', 'PO_EMAI': 'mferrara@nsf.gov', 'PO_PHON': '7032922635'}

This project serves the national interest by providing undergraduate and graduate students in the mathematical sciences with "insider" knowledge that will allow them to make informed decisions about their educational and career choices. Specifically, this project will support the fourth offering of the Online Undergraduate Resource Fair for the Advancement and Alliance of Marginalized Mathematicians, a two-day online conference organized by current students. Building from three prior offerings from 2021 to 2023, the 2024 conference will include six main activities for participating students: (1) Our Stories talks, where recent PhD recipients will share their experiences; (2) crash courses that provide brief overviews of fields of mathematics common in undergraduate research; (3) a summer opportunities panel; (4) a student experiences panel; (5) two plenary presentations; and (6) two virtual networking lunches. Each activity is designed to shine a light on aspects of graduate education and career opportunities that can be complex for participants to explore on their own.<br/><br/>Too often, students can be excluded from educational and career opportunities simply because they are not "in the know." This may be due to insufficient mentorship, underdeveloped institutional advising systems, or other circumstances. This is a particularly common challenge for individuals from low-income backgrounds, first-generation students, and students from populations that have historically been underrepresented in the mathematical sciences. This conference looks to provide mentoring and networking opportunities to promote access to opportunities for all students. The conference builds upon three pillars: (1) sharing information about resources and opportunities through conference presentations and panel discussions; (2) providing access to role models and representation through a careful selection of speakers with diverse identities and experiences and a history of supporting students; and (3) providing access to networking opportunities. A participant overview will be disseminated and an assessment of the conference's effectiveness will be conducted using data from a Zoom meeting report, a survey immediately after the conference, and a second survey four months after the conference. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.076

1

4900

4900

2438032

[{'FirstName': 'Bowen', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bowen Li', 'EmailAddress': 'bowenli.math@gmail.com', 'NSF_ID': '0000A0GZS', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kiera', 'LastName': 'Palma', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kiera L Palma', 'EmailAddress': 'kedwards@maa.org', 'NSF_ID': '000805110', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ashka', 'LastName': 'Dalal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ashka Dalal', 'EmailAddress': 'dalalas@rose-hulman.edu', 'NSF_ID': '000936899', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'tahda', 'LastName': 'queer', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'tahda queer', 'EmailAddress': 'tahdaqueer@gmail.com', 'NSF_ID': '0000A0GZX', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Mathematical Association of America', 'CityName': 'WASHINGTON', 'ZipCode': '200361206', 'PhoneNumber': '2023875200', 'StreetAddress': '11 DUPONT CIRCLE NW', 'StreetAddress2': 'STE 200', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'TY44D55D6B65', 'ORG_LGL_BUS_NAME': 'THE MATHEMATICAL ASSOCIATION OF AMERICA (INCORPORATED)', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Mathematical Association of America', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200361206', 'StreetAddress': '11 DUPONT CIRCLE NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '199800', 'Text': 'IUSE'}

2024~49933

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438032.xml'}

NSF-DFG MISSION “In-situ analysis of Li transport through solid state interfacial systems by neutron reflectometry measurements"

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Catherine Walker', 'PO_EMAI': 'cawalker@nsf.gov', 'PO_PHON': '7032927125'}

This grant supports research that will advance investigations of lithium transport in multilayer systems with nano-sized layers, under realistic operating conditions. Lithium is of immense importance in the development of a diverse set of applications, such as drug release for pharmaceuticals, quantum technology and electronics, and energy storage devices such as batteries. Interfaces are more prevalent in nanosized systems and can drastically change the functionality of a material for lithium transport. Understanding lithium transport through the interfacial systems can have a significant impact on the design and applications of nano-scaled multilayer systems. This joint project between the University of Kentucky of USA and Technische Universität Clausthal of Germany will develop a specialized measurement technique of neutron reflectometry and numerical modeling to investigate lithium transport in nano-scaled multilayer systems. Results from this research will help to strengthen U.S. standing and influence in the development of electric vehicles and hybrid electric vehicles, increase the safety and reliability in pharmaceuticals, quantum technology, and energy storage devices, as well as help the American workforce become more competitive in these industries through the training of graduate and undergraduate students. The PI will also actively recruit and mentor women and minorities to foster their interest in the fields of nanotechnology and energy storage.<br/><br/>There is a lack of systematic investigations of atomic transport through interfaces and confined systems by standard diffusion measurement techniques. The primary goal of this joint research project between the University of Kentucky of USA and Technische Universität Clausthal of Germany is to develop advanced in-situ techniques for investigating atomic transport that can clarify the rate mechanisms responsible for anomalous atomic transport through interfacial systems and aid in the design of nano-scaled multilayer systems of high quality. Specifically, the research group from the University of Kentucky will develop and parameterize models for Li+ transport in nano-scaled Si/Li3NbO4 multilayer systems and aim to find approximate and numerical solutions for the nano-scaled multilayer systems studied using neutron reflectometry by the research group from the Technische Universität Clausthal of Germany. The dependence of Li+ transport on mechanical stress and space charge zones at the interfaces will be examined to elucidate the mechanisms responsible for anomalous atomic motion through interfacial systems. Students will be trained in the development of in-situ neutron reflectometry and modeling analysis to understand the rate mechanisms controlling atomic transport in multilayer systems with nano-sized layers and to design nano-scaled multilayer systems of high quality.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2438033

{'FirstName': 'Fuqian', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Fuqian Yang', 'EmailAddress': 'fyang2@uky.edu', 'NSF_ID': '000125577', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'ZipCode': '405260001', 'PhoneNumber': '8592579420', 'StreetAddress': '500 S LIMESTONE', 'StreetAddress2': '109 KINKEAD HALL', 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'KY06', 'ORG_UEI_NUM': 'H1HYA8Z1NTM5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'StateCode': 'KY', 'ZipCode': '405260001', 'StreetAddress': '500 S LIMESTONE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'KY06'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2024~246000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438033.xml'}

Conference: 2025 Southeast Region Chemical Engineering Chairs Meeting

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Ron Joslin', 'PO_EMAI': 'rjoslin@nsf.gov', 'PO_PHON': '7032927030'}

The Southeast Region Chemical Engineering Chairs’ meeting is an annual conference held by department heads and chairs of Chemical Engineering in the area nominally bordered by Texas in the west up to the Ohio River in the north. This is an important meeting that aims to promote collaboration and innovation by sharing best practices and research advancements, enhance equity and inclusion within departments, and align educational programs with industry needs. In prior years, topics discussed included modernization of chemical engineering curriculum, machine learning and artificial intelligence in the chemical engineering field, mentoring of junior faculty, among many others. Additionally, the meeting aims to support faculty development through workshops and mentoring, and advance research by identifying funding opportunities for projects that address global challenges. As such, this meeting has the greatest impact when as many department chairs from the southeast region can participate. However, due to financial barriers, the attendance of minority serving institutions has been limited. <br/><br/>The goal of the next conference is on facilitating interactions with minority serving institutions to support minority students in chemical engineering through joint programs, research collaborations, and exchange opportunities. A travel grant will be used entirely to support department chairs or program leaders from minority serving institutions, who otherwise may not have the financial resources, to attend the meeting. Personalized invitations will be sent to potential speakers and attendees, describing the conference, stating the benefits of attending, and informing them of the availability of travel grants to cover transportation, accommodation, and meals. After the meeting, data will be collected on the participant demographics, and attendee feedback. This data will be evaluated for the effectiveness of the recruitment and support strategies, assessing the impact of the travel grants towards broadening participation. Using this information, we will provide recommendations on how to improve recruitment and participation for future events.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.041

1

4900

4900

2438034

{'FirstName': 'Thomas', 'LastName': 'Dziubla', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas Dziubla', 'EmailAddress': 'dziubla@engr.uky.edu', 'NSF_ID': '000287861', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'ZipCode': '405260001', 'PhoneNumber': '8592579420', 'StreetAddress': '500 S LIMESTONE', 'StreetAddress2': '109 KINKEAD HALL', 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'KY06', 'ORG_UEI_NUM': 'H1HYA8Z1NTM5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KENTUCKY RESEARCH FOUNDATION, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Kentucky Research Foundation', 'CityName': 'LEXINGTON', 'StateCode': 'KY', 'ZipCode': '405260001', 'StreetAddress': '500 S LIMESTONE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'KY06'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2024~8000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438034.xml'}

Collaborative Research: NSF-DFG MISSION: Heterogeneous Nanoparticle Dynamics at Chromatographic Interfaces

NSF

01/01/2025

12/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Christina Payne', 'PO_EMAI': 'cpayne@nsf.gov', 'PO_PHON': '7032922895'}

The ability to precisely separate and characterize nanoscale objects, such as molecules, inorganic particles, and biological particles (e.g., exosomes), is crucial in fields like analytical chemistry, environmental science, and medical diagnostics. Chromatography is a key method used for these purposes. As such, it remains a vibrant academic and industrial research and development field. In fact, the chromatography industry generates approximately $9 billion in net global revenue, which is expected to grow by 7% annually over the next decade. Liquid chromatography separates the nanoscale objects (solutes), which are dissolved in a liquid, by passing the solute-laden fluid over the separation medium. The interactions between the solutes and the separation medium govern the effectiveness of the separation. Despite the economic and scientific importance of chromatographic separations, a detailed understanding of the dynamic interactions between solutes and the separation medium at a microscopic level has not been established, hindering progress toward developing more robust and effective techniques. This knowledge gap exists primarily because few experimental techniques can reliably observe these interactions in situ at the interfacial layer. This research project brings together an international team of scientists from the U.S. and Germany to address this gap. The team will use their newly developed, state-of-the-art instruments to directly observe the chromatographic steps at the fundamental, single-particle level during the separation process. Graduate students will gain valuable technical and professional experience through this international collaboration. <br/><br/>Liquid chromatography is an important separation technique. Its wide-ranging applications include chemical purification, pharmaceutical analysis and production, and environmental monitoring, among others. Furthermore, it is foundational in understanding complex biological systems, developing new materials, and optimizing chemical processes. The basic principle of liquid chromatography involves partitioning components between a stationary phase and a mobile phase, with differential interactions leading to their separation based on relative retention times. The general view of the underlying principle is that smaller flexible molecular species are segregated by their retention in the porous environment of the solid substrate. This notion that entropic and enthalpic contributions can be separated in a purely size-exclusion process or by affinity chromatography is now being challenged by the development of liquid chromatography for hybrid nanomaterials with inorganic hard cores and functional soft organic shells. New studies reveal a complex interplay of entropic and enthalpic interactions, the latter resulting from the hybrid materials’ functional shells. Unfortunately, a comprehensive microscopic picture of this interplay cannot be developed because of the limited experimental techniques capable of in situ observations at the interfacial layers governing the chromatographic process. This project aims to shed new light on the interfacial layer dynamics that occur during the chromatographic separation of nanomaterials. Recent advancements in nanomaterials synthesis and functionalization, high-resolution three-dimensional (3D) fluorescence microscopy, and boundary layer thermofluidic manipulation enable this project. The enthalpic contributions will be controlled by synthesizing functional quantum dots (QDs) and modifying the stationary phase of the chromatography column with complementary DNA strands. The 3D dynamics of the functionalized QDs will be explored in situ with unprecedented spatial (10 nanometers) and temporal resolution (10 microseconds). The dynamics and enthalpic interaction of functionalized QDs will be further investigated with complementary planar interfaces by controlling thermo-osmotic flows induced directly at the liquid-solid interface. The results are expected to lead to a new fundamental understanding of chromatography that will considerably improve performance and trigger the development of more efficient or selective separation methods based on novel osmotic flows in microfluidic environments.<br/><br/>This project was awarded through the “Measurements of Interfacial Systems at Scale with In-situ and Operando aNalysis (NSF-DFG MISSION)" opportunity, a collaborative solicitation that involves the National Science Foundation and Deutsche Forschungsgemeinschaft (DFG).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2438037

{'FirstName': 'Haw', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Haw Yang', 'EmailAddress': 'hawyang@princeton.edu', 'NSF_ID': '000490593', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'StateCode': 'NJ', 'ZipCode': '085442001', 'StreetAddress': '1 NASSAU HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2024~273999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438037.xml'}

Collaborative Research: NSF-DFG MISSION: Heterogeneous Nanoparticle Dynamics at Chromatographic Interfaces

NSF

01/01/2025

12/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Christina Payne', 'PO_EMAI': 'cpayne@nsf.gov', 'PO_PHON': '7032922895'}

The ability to precisely separate and characterize nanoscale objects, such as molecules, inorganic particles, and biological particles (e.g., exosomes), is crucial in fields like analytical chemistry, environmental science, and medical diagnostics. Chromatography is a key method used for these purposes. As such, it remains a vibrant academic and industrial research and development field. In fact, the chromatography industry generates approximately $9 billion in net global revenue, which is expected to grow by 7% annually over the next decade. Liquid chromatography separates the nanoscale objects (solutes), which are dissolved in a liquid, by passing the solute-laden fluid over the separation medium. The interactions between the solutes and the separation medium govern the effectiveness of the separation. Despite the economic and scientific importance of chromatographic separations, a detailed understanding of the dynamic interactions between solutes and the separation medium at a microscopic level has not been established, hindering progress toward developing more robust and effective techniques. This knowledge gap exists primarily because few experimental techniques can reliably observe these interactions in situ at the interfacial layer. This research project brings together an international team of scientists from the U.S. and Germany to address this gap. The team will use their newly developed, state-of-the-art instruments to directly observe the chromatographic steps at the fundamental, single-particle level during the separation process. Graduate students will gain valuable technical and professional experience through this international collaboration. <br/><br/>Liquid chromatography is an important separation technique. Its wide-ranging applications include chemical purification, pharmaceutical analysis and production, and environmental monitoring, among others. Furthermore, it is foundational in understanding complex biological systems, developing new materials, and optimizing chemical processes. The basic principle of liquid chromatography involves partitioning components between a stationary phase and a mobile phase, with differential interactions leading to their separation based on relative retention times. The general view of the underlying principle is that smaller flexible molecular species are segregated by their retention in the porous environment of the solid substrate. This notion that entropic and enthalpic contributions can be separated in a purely size-exclusion process or by affinity chromatography is now being challenged by the development of liquid chromatography for hybrid nanomaterials with inorganic hard cores and functional soft organic shells. New studies reveal a complex interplay of entropic and enthalpic interactions, the latter resulting from the hybrid materials’ functional shells. Unfortunately, a comprehensive microscopic picture of this interplay cannot be developed because of the limited experimental techniques capable of in situ observations at the interfacial layers governing the chromatographic process. This project aims to shed new light on the interfacial layer dynamics that occur during the chromatographic separation of nanomaterials. Recent advancements in nanomaterials synthesis and functionalization, high-resolution three-dimensional (3D) fluorescence microscopy, and boundary layer thermofluidic manipulation enable this project. The enthalpic contributions will be controlled by synthesizing functional quantum dots (QDs) and modifying the stationary phase of the chromatography column with complementary DNA strands. The 3D dynamics of the functionalized QDs will be explored in situ with unprecedented spatial (10 nanometers) and temporal resolution (10 microseconds). The dynamics and enthalpic interaction of functionalized QDs will be further investigated with complementary planar interfaces by controlling thermo-osmotic flows induced directly at the liquid-solid interface. The results are expected to lead to a new fundamental understanding of chromatography that will considerably improve performance and trigger the development of more efficient or selective separation methods based on novel osmotic flows in microfluidic environments.<br/><br/>This project was awarded through the “Measurements of Interfacial Systems at Scale with In-situ and Operando aNalysis (NSF-DFG MISSION)" opportunity, a collaborative solicitation that involves the National Science Foundation and Deutsche Forschungsgemeinschaft (DFG).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2438038

{'FirstName': 'Preston', 'LastName': 'Snee', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Preston T Snee', 'EmailAddress': 'sneep@uic.edu', 'NSF_ID': '000254937', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606124305', 'PhoneNumber': '3129962862', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'IL07', 'ORG_UEI_NUM': 'W8XEAJDKMXH3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606124305', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'IL07'}

{'Code': '164200', 'Text': 'Special Initiatives'}

2024~201000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438038.xml'}

EAGER GERMINATION Collaborative Research: Leveraging a Research Development Professional Network to Catalyze Statewide Innovative and Societally Relevant Research

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '07040000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EFMA', 'LongName': 'Emerging Frontiers & Multidisciplinary Activities'}}

{'SignBlockName': 'Louise R. Howe', 'PO_EMAI': 'lhowe@nsf.gov', 'PO_PHON': '7032922548'}

This project is funded through the NSF Directorate for Engineering Germination program, which seeks to foster the development of pedagogical approaches to increase the ability of academic researchers to formulate research questions and ideas with potentially transformative outcomes. Major societal challenges can benefit from large, coordinated solutions that leverage interdisciplinary teams with collaborations from academia, government, industry, and other stakeholders. However, many college and university faculty have limited experience, tools, and support to successfully engage in diverse teams that extend beyond their department, much less their institution. The goal of this project is to create and sustain inter-institutional teams composed of junior and senior faculty members with diverse STEM perspectives and methodologies focusing on pressing regional issues such as coastal challenges. This statewide research intervention project will be developed and supported by research development professionals embedded in higher education institutions across Florida. Broader impacts will accrue from instantiation of interdisciplinary, inter-institutional research teams who develop research projects capable of successfully addressing societal challenges. Success in this project will provide a template for replication and scaling by states and other sizable networks focused on addressing intractable problems with team-based solutions that cross disciplinary boundaries.<br/><br/>This project directly addresses gaps in researcher professional development, networking, and support by creating and guiding inter-institutional teams formed around important societal needs and informed by key community stakeholders. It involves a two-stage research intervention that commences with a collaborative learning and ideation event and continues with supported team and project development. The facilitators of these activities will be Research Development (RD) staff from Florida colleges and universities, under the guidance of a faculty expert in team science. These RD professionals are members of FloRDA, a statewide network of research staff from a diverse set of 21 member institutions, including primarily undergraduate and minority-serving institutions. During this program, RD professionals will serve as the “glue” to form and facilitate faculty teams, as connective boundary spanners with institutional knowledge as well as broader knowledge encompassing opportunities for strategic growth, existing community partnerships, and statewide policy and funding initiatives. These facilitators will nurture newly formed research teams into stable groups with aligned goals and defined member roles, leveraging activities designed to enhance knowledge integration and create a shared transdisciplinary framework. Success in this project may enhance understanding of how to implement team science approaches in geographically dispersed groups. It will also be important for charting a path through which RD professionals can foster and support team science spanning multiple and diverse partner organizations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/30/2024

07/30/2024

None

Grant

47.041

1

4900

4900

2438047

{'FirstName': 'Jeanne', 'LastName': 'Viviani-Ayers', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeanne M Viviani-Ayers', 'EmailAddress': 'jeanne.vivianiayers@ucf.edudisabled', 'NSF_ID': '000266847', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'ZipCode': '328168005', 'PhoneNumber': '4078230387', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'FL10', 'ORG_UEI_NUM': 'RD7MXJV7DKT9', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF CENTRAL FLORIDA BOARD OF TRUSTEES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'The University of Central Florida Board of Trustees', 'CityName': 'ORLANDO', 'StateCode': 'FL', 'ZipCode': '328168005', 'StreetAddress': '4000 CENTRAL FLORIDA BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'FL10'}

{'Code': '763300', 'Text': 'EFRI Research Projects'}

2022~2801

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438047.xml'}

Travel: NSF Student Travel Grant for 2024 ACM International Conference on Mobile Computing and Networking (ACM MobiCom)

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Joseph Lyles', 'PO_EMAI': 'jlyles@nsf.gov', 'PO_PHON': '7032922087'}

This project supports students’ travel to the 2024 Association for Computing Machinery (ACM) International Conference on Mobile Computing and Networking (ACM MobiCom), which will be held in Washington, D.C., USA, between November 18th and 22nd, 2024. MobiCom is a premier international conference focusing on systems issues in the emerging area of mobile computing and wireless communications. The conference attendance supported by this grant will provide career development and learning opportunities for 25 US-based students, with priority given to students from underrepresented groups (women, minorities, and people with disabilities) or students who would typically find it challenging to attend as the result of having not having a paper accepted in the conference.<br/><br/>This proposal will increase the dissemination of the conference's research results to a larger and more diverse audience. Moreover, MobiCom has a strong track record of giving preference in grant awards to women and minority students. To encourage researchers from under-represented groups in their research in the nationally critical area of mobile networking, in the selection process, under-represented groups or institutions will be given priority for about two thirds of the travel awards. Advertising to a wide range of colleges and universities, participants from a more diverse set of institutions should also be able to attend and benefit from the conference.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/31/2024

07/31/2024

None

Grant

47.070

1

4900

4900

2438050

{'FirstName': 'Rui', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rui Zhang', 'EmailAddress': 'ruizhang@udel.edu', 'NSF_ID': '000651467', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'ZipCode': '197160099', 'PhoneNumber': '3028312136', 'StreetAddress': '220 HULLIHEN HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Delaware', 'StateCode': 'DE', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DE00', 'ORG_UEI_NUM': 'T72NHKM259N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DELAWARE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'StateCode': 'DE', 'ZipCode': '197160099', 'StreetAddress': '220 HULLIHEN HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Delaware', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DE00'}

{'Code': '736300', 'Text': 'Networking Technology and Syst'}

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438050.xml'}

NSF-DFG MISSION: Unraveling Structures and Dynamics of Plasmonic Catalysts by In Situ X-ray and Electron-Based Probing (CAPTURE)

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': "Francis D'Souza", 'PO_EMAI': 'frdsouza@nsf.gov', 'PO_PHON': '7032924559'}

Energy generation and storage, environmental remediation, and chemical manufacturing require materials that speed up important chemical reactions such as carbon fixation. Often these materials operate in complex, dynamic environments where their structures change. For designing robust high-performance catalysts that reduce energy consumption and waste, it is important to know the atomic-level structure of the catalyst under operating conditions so as to understand why a specific material catalyzes an important chemical reaction or why performance deteriorates under certain conditions. Principal Investigator Jain from University of Illinois at Urbana-Champaign and his collaborators from Humboldt University and Helmholtz-Zentrum in Berlin are using advanced characterization methods to image in real time the atomic structures of catalysts comprised of light-absorbing nanoparticles of metals that catalyze carbon fixation using light energy. Their research will lead to more robust catalysts for solar-powered carbon fixation and sustainable chemical manufacturing technologies. <br/> <br/>In the practice of heterogeneous catalysis, the surface structure, composition and/or oxidation state of the catalyst may change into the active form in response to operating conditions. Therefore, there is a need to probe the chemical state of catalysts in situ under the action of stimuli and reactive conditions. As one prime example, plasmonic nanostructures are known to exhibit superlative catalytic activity under light; however, such nanostructures can dynamically evolve in operando due to effects of plasmonic excitation, heat, and reactive environments. Principal Investigator Jain and collaborators will elucidate currently unknown active-state structures and dynamics of plasmonic nanocatalysts using a laser-coupled dynamic environmental transmission electron microscopy at UIUC complemented by high-resolution electron energy loss spectroscopy and in-situ X-ray absorption spectroscopy in Berlin. The team will probe hybrid nanostructures consisting of plasmonic absorbers with catalytic domains during plasmon-catalyzed carbon dioxide and carbon monoxide hydrogenation. The aim is to uncover the structures of the active states of these hybrid nanostructures and elucidate dynamic structural fluctuations that may underlie their catalytic activities. These insights will fill the current knowledge gap in structure–reactivity relationships for hybrid plasmonic catalysts. The success of this project may lead to design principles and protocols for more robust photocatalysts for solar-powered carbon dioxide reduction and sustainable synthesis of fuels and chemicals from carbon dioxide. The work may also advance the use of advanced electron microscopy methods in the chemical industry for examination of nanoparticle-based catalysts and train students for the research and development workforce.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.049

1

4900

4900

2438061

{'FirstName': 'Prashant', 'LastName': 'Jain', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Prashant K Jain', 'EmailAddress': 'jain@illinois.edu', 'NSF_ID': '000598990', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': 'V2PHZ2CSCH63'}

{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'StateCode': 'IL', 'ZipCode': '618013620', 'StreetAddress': '506 S WRIGHT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'IL13'}

{'Code': '688400', 'Text': 'Chemical Catalysis'}

2024~333850

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438061.xml'}

Integrated Multiscale Computational and Experimental Investigations on Fracture of Additively Manufactured Polymer Composites

NSF

06/01/2024

06/30/2026

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Siddiq Qidwai', 'PO_EMAI': 'sqidwai@nsf.gov', 'PO_PHON': '7032922211'}

This project will create new computational capabilities using experimental investigations to understand fracture and failure in 3D printed polymer composites. 3D printing is transitioning from demonstrative prototypes to functional products that impact a wide range of industrial sectors. However, many polymer-based 3D printed parts are prone to fracture and failure. This limits their applications in load-bearing components. Various polymer composite filaments reinforced with particles and/or fibers are being developed to improve the performance of 3D printed components. The current research and development are hindered by the complex variabilities of 3D printing. It thus largely remains in a trial-and-error stage with insufficient scientific guidance. This project will develop a science-based strategy that combines computational modeling and simulations with an optimal suite of experiments. This approach helps to gain a fundamental understanding of multiscale fracture as well as to quantify uncertainties associated with 3D printed polymer composites. The new knowledge achieved through this research can develop new technologies for 3D printing of high-performance components. The outcomes of this research can be applied to a broad array of industries. The research will be complemented by educational and outreach activities. These include curriculum enhancements, hands-on 3D printing workshops, and STEM education programs that engage K-12 and underrepresented minority students.<br/><br/>This project will take on the challenges of quantifying the process-structure-property-performance relationship and deriving multiscale fracture mechanics mechanisms for additively manufactured polymer composites. Although additive manufacturing is capable of printing parts with relatively complex geometries, several fundamental issues must be addressed before AM can advance to producing functional composites. Current limitations include microstructural defects due to strong thermal gradients induced during manufacturing, heterogeneous interface bonding conditions, and large fracture and failure performance variations. The research objectives of this project thus include: 1) developing direct mesoscale simulations capable of predicting thermo-mechanical-chemical coupling and fluid-structure interactions during the additive manufacturing process, which will address fundamental questions of how motions and deformations, temperature gradients, melting/solidification between filaments and reinforced particles/fibers interplay with one other in assocoation with micro-crack nucleation and propagation; 2) deriving multiscale modeling of fracture based on machine learning of micro-crack simulations and phase-field models of macro-crack predictions, with in-situ monitoring of manufacturing processes and multiscale experimental characterizations being used for direct model validations; and 3) developing an optimal model-based uncertainty quantification protocol that organizes computational and experimental activities to validate the model, investigate parameter sensitivities, and quantify process/property variations. The research outcomes will advance fundamental knowledge of the complex interplay between additive manufacturing process parameters and fracture behaviors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.041

1

4900

4900

2438062

{'FirstName': 'Jun', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jun Li', 'EmailAddress': 'jun.li@erau.edu', 'NSF_ID': '000741020', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Embry-Riddle Aeronautical University', 'CityName': 'DAYTONA BEACH', 'ZipCode': '321143910', 'PhoneNumber': '3862267695', 'StreetAddress': '1 AEROSPACE BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'FL06', 'ORG_UEI_NUM': 'U5MMBAC9XAM5', 'ORG_LGL_BUS_NAME': 'EMBRY-RIDDLE AERONAUTICAL UNIVERSITY, INC.', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Embry-Riddle Aeronautical University', 'CityName': 'DAYTONA BEACH', 'StateCode': 'FL', 'ZipCode': '321143910', 'StreetAddress': '1 AEROSPACE BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'FL06'}

{'Code': '163000', 'Text': 'Mechanics of Materials and Str'}

2023~336081

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438062.xml'}

Collaborative Research: RAPID: Airborne LIDAR and Hyperspectral observations to support characterization of litter pool distributions in partnership with NSF DeAD project

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '08080000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}

{'SignBlockName': 'Andrew J. Elmore', 'PO_EMAI': 'aelmore@nsf.gov', 'PO_PHON': '7032927939'}

Drylands cover more of the Earth’s surface than any other biome and nearly half of the United States. They are characterized by low rainfall amounts, yet high variability in rainfall. This makes drylands unique from wetter locations, yet research is lacking that helps us understand how rainfall variability impacts ecosystem services such as removal of carbon from the atmosphere and the ability of landscapes to store water during drought. In this project researchers will leverage high rainfall variability at the Santa Rita Experimental Site to explore the production and decomposition of plant litter, which influences ecosystem services. Researchers will collect high resolution airborne images and surface elevation data to explore spatial and temporal patterns in plant litter. This funding will enable a multi-year investigation of variability by filling a gap in annual remote sensing data collection. The data will be made available to the public by the National Ecological Observatory Network (NEON) to enable a variety of research related to understanding the ecosystem outcomes of high rainfall variability.<br/><br/>Researchers recognize that dryland litter decay differs from that of mesic systems in part due to higher heterogeneity and temporal variability in litter inputs, litter distribution, and environmental conditions across time and space. The unvegetated interspaces characteristic of drylands allow litter transport by wind and water until restricted by surface features (e.g., plant bases, rocks). Environmental conditions (e.g., moisture, temperature, solar radiation) differ greatly among the microsites where litter accumulates, strongly affecting decomposition rates. Accordingly, quantifying decomposition across drylands is a microbial-to-macroscale problem of integrating fine-scale process controls across spatial-temporal heterogeneity in environmental conditions. Researchers will integrating fieldwork, modeling, and remote sensing approaches across a hierarchical range of scales to capture the distribution of litter across a range of environmental conditions. The project will fund a survey by the NEON Airborne Observation Platform at the Santa Rita Experimental Site that will provide an annual record of imaging spectroscopy and lidar data, enabling landscape-scale multi-temporal analysis of ecosystem dynamics.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.074

1

4900

4900

2438071

{'FirstName': 'Jiwei', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jiwei Li', 'EmailAddress': 'jiweili@asu.edu', 'NSF_ID': '000717884', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}

{'Code': '795900', 'Text': 'MacroSysBIO & NEON-Enabled Sci'}

2024~24365

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438071.xml'}

Collaborative Research: RAPID: Airborne LIDAR and Hyperspectral observations to support characterization of litter pool distributions in partnership with NSF DeAD project

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '08080000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}

{'SignBlockName': 'Andrew J. Elmore', 'PO_EMAI': 'aelmore@nsf.gov', 'PO_PHON': '7032927939'}

Drylands cover more of the Earth’s surface than any other biome and nearly half of the United States. They are characterized by low rainfall amounts, yet high variability in rainfall. This makes drylands unique from wetter locations, yet research is lacking that helps us understand how rainfall variability impacts ecosystem services such as removal of carbon from the atmosphere and the ability of landscapes to store water during drought. In this project researchers will leverage high rainfall variability at the Santa Rita Experimental Site to explore the production and decomposition of plant litter, which influences ecosystem services. Researchers will collect high resolution airborne images and surface elevation data to explore spatial and temporal patterns in plant litter. This funding will enable a multi-year investigation of variability by filling a gap in annual remote sensing data collection. The data will be made available to the public by the National Ecological Observatory Network (NEON) to enable a variety of research related to understanding the ecosystem outcomes of high rainfall variability.<br/><br/>Researchers recognize that dryland litter decay differs from that of mesic systems in part due to higher heterogeneity and temporal variability in litter inputs, litter distribution, and environmental conditions across time and space. The unvegetated interspaces characteristic of drylands allow litter transport by wind and water until restricted by surface features (e.g., plant bases, rocks). Environmental conditions (e.g., moisture, temperature, solar radiation) differ greatly among the microsites where litter accumulates, strongly affecting decomposition rates. Accordingly, quantifying decomposition across drylands is a microbial-to-macroscale problem of integrating fine-scale process controls across spatial-temporal heterogeneity in environmental conditions. Researchers will integrating fieldwork, modeling, and remote sensing approaches across a hierarchical range of scales to capture the distribution of litter across a range of environmental conditions. The project will fund a survey by the NEON Airborne Observation Platform at the Santa Rita Experimental Site that will provide an annual record of imaging spectroscopy and lidar data, enabling landscape-scale multi-temporal analysis of ecosystem dynamics.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.074

1

4900

4900

2438072

{'FirstName': 'Tristan', 'LastName': 'Goulden', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tristan Goulden', 'EmailAddress': 'tgoulden@battelleecology.org', 'NSF_ID': '000782310', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Battelle Memorial Institute', 'CityName': 'COLUMBUS', 'ZipCode': '432012696', 'PhoneNumber': '6144244873', 'StreetAddress': '505 KING AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'F125YU6SWK59', 'ORG_LGL_BUS_NAME': 'BATTELLE MEMORIAL INSTITUTE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Battelle Memorial Institute', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432012696', 'StreetAddress': '505 KING AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}

{'Code': '795900', 'Text': 'MacroSysBIO & NEON-Enabled Sci'}

2024~118061

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438072.xml'}

NSF-DFG MISSION: "INCUBATOR - Exploring the Interfacial Chemistry in Sulfide-Based Solid-State Batteries by Soft and Hard X-ray Spectroscopies Under Operating Conditions"

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': "Francis D'Souza", 'PO_EMAI': 'frdsouza@nsf.gov', 'PO_PHON': '7032924559'}

Solid-state batteries (SSBs) have emerged as strong contenders for next generation LIB technologies as they are expected to achieve higher energy and power densities and increased safety through replacement of liquid electrolyte formulations with solid electrolytes. This recent global and commercial interest in SSBs has helped illuminate the key challenges for the realization of this technology, such as increased understanding and control of the solid-state composite cathodes and the impact of the active material/solid electrolyte interfaces. Supported by the Division of Chemistry at NSF and DFG, Profession Guo from University of California-Santa Cruz in US, and Dr. Adelhelm at Humboldt University and Dr. Bär at HZB in Germany will work together focus on studying new cathode chemistries for SSBs, including materials development and multi-modal characterization of their properties and interfaces with solid electrolytes. The collaboration also provides students the opportunities to be exposed to international research activities and different culture. <br/><br/>An understanding of the processes at the interfaces and in bulk that occur in batteries requires obtaining qualitative and quantitative atom-specific information under realistic operating conditions at relevant time scales. X-ray spectroscopies are critical tools to achieve this understanding. State-of-the art high-brilliance synchrotron sources provide a powerful means to use photons for probing buried interfaces. The ability to study buried interfaces is of great importance for energy storage devices, such as batteries. The international team supported by this grant will develop a mechanistic understanding of the redox and decomposition processes occurring in sulfide-based electrode/electrolyte composites. Achieving this goal is dependent on the development of a new multi-modal characterization platform that enables experiments with high energy resolution on different length scales. This new platform will enable the study of SSBs under in-situ and operando conditions by XAS and RIXS for an atom-specific understanding of electrochemical phenomena and associated degradation processes at electrode/electrolyte.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.049