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Conference: Pacific Northwest Geometry Seminar

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Eriko Hironaka', 'PO_EMAI': 'ehironak@nsf.gov', 'PO_PHON': '7032927041'}

This award will support meetings of the Pacific Northwest Geometry Seminar (PNGS) to be held at the University of British Columbia (2025), Seattle University (2026) and Lewis & Clark College (2027). Active researchers in geometry are scattered throughout the various colleges and universities involved in the Pacific Northwest Geometry Seminar. The PNGS meetings will bring these researchers together for consultation, collaboration, and stimulation of new ideas, and will give graduate students an excellent opportunity to see the broader picture of research in geometry. The meetings are also valuable for the growing number of geometers working at some of the smaller universities in the region, such as Pacific University, Seattle University, and Idaho State University. Conference support will be especially targeted toward graduate students, early career researchers and members of groups underrepresented in mathematics. <br/> <br/>The meetings will feature five to six invited research talks by leading experts in differential geometry and geometric analysis, as well as three to four shorter talks by junior researchers or graduate students. The meetings will also include discussion sessions in which the speakers and participants assess the state of various areas in geometry and highlight open problems in these areas. For the first meeting at the University of British Columbia the grant will support travel of US based participants only. More information can be found on the conference website: https://sites.google.com/view/pnwgeometryseminar/home.<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.

04/26/2024

04/26/2024

None

Grant

47.049

1

4900

4900

2426238

[{'FirstName': 'Christine', 'LastName': 'Escher', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christine M Escher', 'EmailAddress': 'tine@math.orst.edu', 'NSF_ID': '000204160', 'StartDate': '04/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Tracy', 'LastName': 'Payne', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tracy L Payne', 'EmailAddress': 'payntrac@isu.edu', 'NSF_ID': '000236941', 'StartDate': '04/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Eric', 'LastName': 'Bahuaud', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric Bahuaud', 'EmailAddress': 'bahuaude@seattleu.edu', 'NSF_ID': '000630627', 'StartDate': '04/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'ZipCode': '973318655', 'PhoneNumber': '5417374933', 'StreetAddress': '1500 SW JEFFERSON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'MZ4DYXE1SL98', 'ORG_LGL_BUS_NAME': 'OREGON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'StateCode': 'OR', 'ZipCode': '973318655', 'StreetAddress': '1500 SW JEFFERSON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}

{'Code': '126500', 'Text': 'GEOMETRIC ANALYSIS'}

2024~50397

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426238.xml'}

I-Corps: Translation Potential of an Artificial Intelligence-based Course Front Desk for Facilitating Student-Instructor Interactions

NSF

07/01/2024

06/30/2025

{'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 a novel artificial intelligence-enhanced chatbot system to provide affordable engagement and enhanced accessibility to students. By automating routine tasks, the system can free up time to focus on instructional design and teaching, alleviating the workload on instructors and teaching assistants. This innovation represents an affordable alternative for institutions (including community colleges and other non-traditional teaching institutions) that cannot afford additional teaching assistance for instructors, allowing them to focus on more complex and creative educational tasks and student engagement. The benefit of this approach is its potential to enhance teaching effectiveness, increase engagement in the learning process for large classes, and improve individualized learning, while preserving and reflecting the personalized approach of the instructor. <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 Retrieval Augmented Generative artificial intelligence (RAG) “always available” chatbot system called ChaTA (short for Chat Teaching Assistant). The technology is an instructor-customizable interface between students and instructors, based on a novel approach to RAG prompting where a Large Language Model (LLM) is combined with an instructor supplied database of information (their notes, presentations and videos, and answers). The LLM will interpret the student questions, classify them based on instructor policy, convert them into a query of the database, and evaluate if the results answer the original question. The chatbot learns from the student ratings of the acceptability of the answers and is moderated by the instructor (to identify "hallucinations" or erroneous or nonresponsive answers) as it learns to reflect the instructor’s point of view. Unlike current approaches where a chatbot is used as a fully automated teaching assistant, the current approach is designed to help instructors by providing summary reports of student questions and acceptable answers, helping the instructor fine-tune their teaching.<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.

06/25/2024

06/25/2024

None

Grant

47.084

1

4900

4900

2426266

[{'FirstName': 'Arun', 'LastName': 'Srinivasa', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Arun R Srinivasa', 'EmailAddress': 'asrinivasa@tamu.edu', 'NSF_ID': '000444693', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Mary', 'LastName': 'Hipwell', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mary C Hipwell', 'EmailAddress': 'cynthia.hipwell@tamu.edu', 'NSF_ID': '000780414', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Co-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': '778433123', 'StreetAddress': '3123 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426266.xml'}

RAPID: Ecosystem-level responses along the mainstem of Lookout Creek after a major wildfire

NSF

06/01/2024

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}

{'SignBlockName': "Catherine O'Reilly", 'PO_EMAI': 'coreilly@nsf.gov', 'PO_PHON': '7032927934'}

This project will investigate how Lookout Creek, Oregon, was affected by the Lookout Fire that occurred from August to October 2023. The researchers aim to understand the changes in stream ecosystem structure and function, focusing on microbial decomposition, aquatic vertebrates, and riparian wildlife. This research will advance scientific knowledge because it sheds light on how wildfires impact ecosystems, particularly in forested watersheds like Lookout Creek. By testing alternative hypotheses, researchers gain insights into how both the stream and wildlife in the surrounding forest might change after a major wildfire. The study will help scientists predict and manage the aftermath of similar wildfires in the future, informing land management practices and conservation efforts to understand post-fire ecosystem recovery. This project will provide experiential learning opportunities for a wide range of graduate and undergraduate students, especially those from diverse backgrounds who are underrepresented in STEM. The inclusion of students from diverse backgrounds will contribute to a more diverse workforce that will ultimately strengthen innovation and problem-solving on issues related to wildfires and freshwaters. Studying post-fire changes in biodiversity has broader societal impacts as wildfires have significant economic and social implications affecting clean water, air quality regulation, and recreational opportunities. <br/><br/>Three hypotheses will be tested by examining the stream and riparian zone after this extreme fire, compared to prior conditions. The cumulative effect suggests the effects of the fire will accumulate downstream whereas the diluted effect hypothesis posits that downstream sites will buffer the effects from the fire. The stream resilience hypothesis proposes faster recovery in areas with high fire severity due to habitat heterogeneity. The researchers will assess microbial decomposition rates in riparian soils and streams using similar pre- and post-fire methodologies. A cotton strip assay placed in different locations will measure decomposition rates, with strips deployed for two to three weeks and analyzed for changes in dissolved oxygen concentrations. Electrofishing will be conducted during low streamflow conditions to capture the abundance and size of fish and salamanders. Gastric lavage will be used to assess diet composition, prey richness and diet overlap between fish and salamanders pre- and post-fire. Motion-sensor camera traps will monitor terrestrial vertebrate biodiversity, recording behavior and species identification. This project will provide experiential learning opportunities for a wide range of graduate and undergraduate students, especially those from diverse backgrounds who are underrepresented in STEM. Collectively, findings from this research will help managers and decision-makers be better informed as they create climate- and fire-smart management plans in the era of changing climate and increasing wildfires.<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.

05/29/2024

05/29/2024

None

Grant

47.074

1

4900

4900

2426267

[{'FirstName': 'Ivan', 'LastName': 'Arismendi', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ivan D Arismendi', 'EmailAddress': 'Ivan.Arismendi@oregonstate.edu', 'NSF_ID': '000634860', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Brooke', 'LastName': 'Penaluna', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brooke Penaluna', 'EmailAddress': 'brooke.penaluna@usda.gov', 'NSF_ID': '000865264', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Rebecca', 'LastName': 'Flitcroft', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca L Flitcroft', 'EmailAddress': 'rebecca.flitcroft@usda.gov', 'NSF_ID': '000997706', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ashley', 'LastName': 'Coble', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ashley A Coble', 'EmailAddress': 'acoble@ncasi.org', 'NSF_ID': '000997512', 'StartDate': '05/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'ZipCode': '973318655', 'PhoneNumber': '5417374933', 'StreetAddress': '1500 SW JEFFERSON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'MZ4DYXE1SL98', 'ORG_LGL_BUS_NAME': 'OREGON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'StateCode': 'OR', 'ZipCode': '973318655', 'StreetAddress': '1500 SW JEFFERSON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}

{'Code': '738100', 'Text': 'Ecosystem Science'}

2024~195763

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426267.xml'}

NSF-NFRF: A Collaboratively Designed and Managed Flood Resilience Framework for Affected Communities in the Caribbean Region

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

This award aims to achieve flood resilience and reduce the impacts of flooding on coastal communities in the Caribbean region, particularly in Guyana, Trinidad and Tobago, and St. Lucia. The project outcomes will benefit coastal and riverine communities in the Caribbean region by addressing flood risks while fostering community education and building partnerships between researchers, decision-makers, community organizations, and citizens. The project will deliver decision-support tools that reduce the social, economic, and environmental damage caused by climate change. The project will generate new insights into government policies, institutional frameworks, land use and zoning regulations, and social networks required for resilience. Engineers, natural scientists, climate scientists and modelers, ecologists, social scientists, and land-use planners, working iteratively with flood-prone communities, will pool their expertise in an integrated manner to address the human, physical, and social devastation and increasing financial damages of flooding. The project team includes several early-career researchers and will provide training opportunities to diverse populations from the local communities and graduate education training to several students, with a dedicated effort to recruit students from the Caribbean region.<br/><br/>The project has the following main goals: (a) To develop a community learning platform that provides a comprehensive understanding of how vulnerable communities are affected by floods and (b) To empower decision-making using integrated social, economic, and environmental data supported by open-source modeling tools. The project will engage the affected communities in the potential solutions throughout the project phases. The project includes six work packages with tasks that focus on: (1) Community learning and creation of flood mitigation measures, (2) Development of data systems for decision-making, (3) Flood prediction models, (4) Inclusive and adaptive flood risk governance, (5) Capacity development, and (6) Building flood resilience in communities both nationally and regionally. The project will incorporate green systems such as mangroves, wetlands, and native vegetation species into flood control infrastructure. New digital tools incorporating remotely sensed data, satellite imagery, climate forecasting, and prediction models will lead to improved designs of flood control structures, siting of infrastructure, and an early flood warning system to be used by the community, government agencies, and flood relief organizations.<br/><br/>This award is part of a multilateral project supported jointly by the National Science Foundation and funding agencies in Canada and the United Kingdom under the International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition, led by Canada. Each agency supports scientists at institutions in its country.<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.

05/31/2024

05/31/2024

None

Grant

47.079

1

4900

4900

2426270

{'FirstName': 'Emad', 'LastName': 'Habib', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emad Habib', 'EmailAddress': 'habib@louisiana.edu', 'NSF_ID': '000391963', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'ZipCode': '705032014', 'PhoneNumber': '3374825811', 'StreetAddress': '104 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'LA03', 'ORG_UEI_NUM': 'C169K7T4QZ96', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF LOUISIANA AT LAFAYETTE', 'ORG_PRNT_UEI_NUM': 'C169K7T4QZ96'}

{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'StateCode': 'LA', 'ZipCode': '705032014', 'StreetAddress': '104 E UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'LA03'}

{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}

2024~648579

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426270.xml'}

I-Corps: Translation potential of a chemical-free recycling process to recover materials from post-consumer electronic waste

NSF

06/15/2024

05/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': 'rshuman@nsf.gov', 'PO_PHON': '7032922160'}

The broader impact of this I-Corps project is the development of a chemical-free and zero waste recycling method for printed circuit boards and other waste streams, including solar panels, wind turbines, and batteries. Currently, the surge in digitalization has led to a staggering amount of electronic waste (e-waste), with approximately 53.6 million metric tons discarded annually, and only 17.4% of which is collected and recycled. This technology addresses e-waste by using a sustainable process for recycling. The goal is to recover base and precious metals from printed circuit boards and other urban waste streams to reduce the need for mining and its associated environmental impact. This approach may minimize material and energy consumption and may create new revenue streams through the recovery of valuable materials from post-consumer electronic waste.<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 a process for the selective and efficient physical separation of components in e-waste. Current recycling methods, marked by high energy consumption, environmental pollution, and low recovery of valuable materials, typically involve energy-intensive size reduction, hydrometallurgical process. This process departs from current methods by leveraging inherent material properties and differences in malleability and size among e-waste components. This technology efficiently liberates components without the need for intensive energy use. It further capitalizes on physical separation techniques, exploiting differences in size, density, and magnetic susceptibility to isolate high-grade, saleable elements and other products, including base metals (such as copper and aluminum), precious metals (such as gold, silver, and palladium), ferrous metals (such as iron, cobalt, nickel, and manganese), silicon, and plastics. High-purity metals were obtained when the process was tested with a char-metal mixture from e-waste thermolysis. Embracing circular economy principles, this chemical-free and zero-waste approach not only maximizes resource recovery and product quality but also reduces the carbon footprint, offering a sustainable and economically viable alternative to current recycling methods.<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.

06/04/2024

06/04/2024

None

Grant

47.084

1

4900

4900

2426287

{'FirstName': 'Mohammad', 'LastName': 'Rezaee', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mohammad Rezaee', 'EmailAddress': 'm.rezaee@psu.edu', 'NSF_ID': '0000A02PH', 'StartDate': '06/04/2024', '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': 'The Pennsylvania State University', 'CityName': 'UNIVERSITY PARK', 'StateCode': 'PA', 'ZipCode': '168021503', 'StreetAddress': '122 Hosler Building', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '15', 'CONGRESS_DISTRICT_PERF': 'PA15'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426287.xml'}

CAP: EXPanding Education & Research in AI-ENabled Swarm Computing Evolution (EXPERIENCE)

NSF

09/01/2024

08/31/2026

{'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': 'James Donlon', 'PO_EMAI': 'jdonlon@nsf.gov', 'PO_PHON': '7032928074'}

This project is an ExpandAI Capacity building pilot (CAP), designed to establish and fortify the Artificial Intelligence (AI) infrastructure at Alabama A&M University (AAMU), thereby enhancing both institutional research capacity and facilitating AI-focused educational programs. Towards this goal, the project will augment AAMU research capabilities, infrastructure, and educational offerings in AI-enabled robotics. Leveraging this research enhancement, AAMU aims to establish a world-class academic program focused on AI-enabled unmanned systems that are capable of operating independently while also working with one another to make collective decisions (referred to as "swarm computing"). This exciting research in AI-enabled autonomous systems has the potential to attract, nurture, and equip underrepresented students with the skills and knowledge they need to succeed and lead in this rapidly-evolving field. <br/><br/>This project builds upon established Artificial Intelligence (AI) infrastructure at Alabama A&M University (AAMU) to enhance the research capacity of the institution and facilitate AI-focused educational curriculum development and training. Towards this goal, the project focused on three main aspects: AI-based research on AI-driven autonomy, curriculum expansion, and an outreach component. AAMU builds upon current research in the field of AI-enabled swarm robotics with new focus on the security and trustworthiness of AI in autonomous in swarm computing, communications-based swarm intelligence, adaptive swarms of heterogeneous platforms, and vision-based object detection within such systems. The project also builds educational capacity, drawing from the new swarm research programs to enhance AI-focused undergraduate classes and a related undergraduate AI concentration. Two new graduate courses will also be developed, in support of a new graduate concentration in AI. The project also includes outreach efforts that leverage the new ExpandAI platform, including a summer bootcamp that will focus on creating a pipeline for high school students to engage in programming, AI, machine learning, and robotics to foster interest in STEM careers among high school juniors and seniors.The ExpandAI Program supports AI-powered education and workforce development, infrastructure and research at Minority Serving Institutions to strengthen and diversify U.S. research and education pathways and provide historically marginalized communities with new opportunities in STEM careers.<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.

06/24/2024

06/24/2024

None

Grant

47.070

1

4900

4900

2426293

[{'FirstName': 'Yujian', 'LastName': 'Fu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yujian Fu', 'EmailAddress': 'yujian.fu@aamu.edu', 'NSF_ID': '000498189', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Terry', 'LastName': 'Miller', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Terry Miller', 'EmailAddress': 'terry.miller@aamu.edu', 'NSF_ID': '000937966', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kaveh', 'LastName': 'Heidary', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kaveh Heidary', 'EmailAddress': 'kaveh.heidary@aamu.edu', 'NSF_ID': '000187240', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Raziq', 'LastName': 'Yaqub', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Raziq Yaqub', 'EmailAddress': 'raziq.yaqub@aamu.edu', 'NSF_ID': '000742899', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ed', 'LastName': 'Pearson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': 'III', 'PI_FULL_NAME': 'Ed Pearson', 'EmailAddress': 'ed.pearson@aamu.edu', 'NSF_ID': '000865419', 'StartDate': '06/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Alabama A&M University', 'CityName': 'NORMAL', 'ZipCode': '357627500', 'PhoneNumber': '2563728186', 'StreetAddress': '4900 MERIDIAN STREET NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'AL05', 'ORG_UEI_NUM': 'JDVGS67MSLH7', 'ORG_LGL_BUS_NAME': 'ALABAMA A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Alabama A&M University', 'CityName': 'NORMAL', 'StateCode': 'AL', 'ZipCode': '357627500', 'StreetAddress': '4900 MERIDIAN STREET NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alabama', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'AL05'}

{'Code': '284Y00', 'Text': 'ExpandAI'}

2024~400000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426293.xml'}

Travel: NSF Student Travel Grant for 2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)

NSF

05/01/2024

04/30/2025

{'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': 'Almadena Chtchelkanova', 'PO_EMAI': 'achtchel@nsf.gov', 'PO_PHON': '7032927498'}

The IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) is a premier forum for presenting, sharing, and discussing advanced academic and industrial research on performance analysis in computer systems and software design. The symposium brings together researchers in the fields related to computer chips and systems, processor architecture, compilers, and operating systems. This award provides travel support funds to help up to 23 undergraduate and graduate students attend and participate in the 2024 IEEE International symposium on Performance Analysis of Systems and Software (ISPASS). The conference is held May 7-9 in Indianapolis, IN. Priority will be given to US citizens and students from universities that do not have a strong tradition in the ISPASS research domain. This grant will also encourage participation by members of under-represented groups, including students with disabilities. Funds from this award will cover expenses such as travel, lodging, and conference registration.<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.

04/19/2024

04/19/2024

None

Grant

47.070

1

4900

4900

2426297

{'FirstName': 'Timothy', 'LastName': 'Rogers', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Timothy G Rogers', 'EmailAddress': 'timrogers@purdue.edu', 'NSF_ID': '000723981', 'StartDate': '04/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479061332', 'PhoneNumber': '7654941055', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'YRXVL4JYCEF5', 'ORG_LGL_BUS_NAME': 'PURDUE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'StateCode': 'IN', 'ZipCode': '479061332', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IN04'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

2024~14000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426297.xml'}

I-Corps: Translation Potential of Functional Textiles Coated with Thermochromic Pigment

NSF

05/15/2024

04/30/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': 'rshuman@nsf.gov', 'PO_PHON': '7032922160'}

The broader impact of this I-Corps project is the development of product to detect fever in babies and young children using a temperature sensitive textile. The initial application is a headband to monitor forehead temperature that uses yarn coated with a pigment that changes color when the temperature increases. The product is envisioned to be used in hospitals, daycare centers, and homes by caregivers of infants and young children who may need to be monitored for fever. The goal is to allow caregivers to monitor body temperature continuously with less effort while maintaining the comfort of the infant or child. <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 temperature-sensing textiles utilizing yarns that are coated with thermochromic pigments. The thermochromic yarn changes color once its surface temperature surpasses a specific threshold. A prototype has been developed to detect body temperature on the forehead by incorporating thermochromic yarn into the headband of a hat. The threshold temperature is tailored to facilitate color changes for the purpose of detecting the presence of fever. Integrating functional textiles into clothing and textile accessories may have benefits for healthcare 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.

05/13/2024

05/13/2024

None

Grant

47.084

1

4900

4900

2426298

[{'FirstName': 'Sibei', 'LastName': 'Xia', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sibei Xia', 'EmailAddress': 'sibeixia@lsu.edu', 'NSF_ID': '0000A02MM', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Chuanlan', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chuanlan Liu', 'EmailAddress': 'clliu@lsu.edu', 'NSF_ID': '0000A02MW', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Louisiana State University', 'CityName': 'BATON ROUGE', 'ZipCode': '708030001', 'PhoneNumber': '2255782760', 'StreetAddress': '202 HIMES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'LA06', 'ORG_UEI_NUM': 'ECQEYCHRNKJ4', 'ORG_LGL_BUS_NAME': 'LOUISIANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Louisiana State University', 'CityName': 'BATON ROUGE', 'StateCode': 'LA', 'ZipCode': '708030001', 'StreetAddress': '202 HIMES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'LA06'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426298.xml'}

CAREER: Protecting Deep Learning Systems against Hardware-Oriented Vulnerabilities

NSF

02/01/2024

04/30/2026

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Karen Karavanic', 'PO_EMAI': 'kkaravan@nsf.gov', 'PO_PHON': '7032922594'}

Artificial intelligence (AI) has recently approached or even surpassed human-level performance in many applications. However, the successful deployment of AI requires sufficient robustness against adversarial attacks of all types and in all phases of the model life cycle. Although much progress has been made in enhancing the robustness of AI algorithms, there is a lack of systematic studies on hardware-oriented vulnerabilities and countermeasures, which also opens up demand for AI security education. Given this pressing need, this project aims at exploring novel hardware-oriented adversarial AI concepts and developing fundamental defensive strategies against such vulnerabilities to protect next-generation AI systems. <br/><br/>This project has four thrusts. In Thrust 1, this project will exploit new adversarial attacks on deep neural network systems, featuring the design of an algorithm-hardware collaborative backdoor attack. Then in Thrust 2, it will develop methodologies that incorporate the hardware aspect into defense for enhancing adversarial robustness against vulnerabilities in the untrusted semiconductor supply chain. Subsequently, in Thrust 3, this project will develop novel signature embedding frameworks to protect the integrity of deep neural network models in the untrusted model building supply chain and finally in Thrust 4, it will model recovery strategies as an innovative approach to mitigate hardware-oriented fault attacks in the untrusted user-space.<br/><br/>This project will yield novel methodologies for ensuring trust in AI systems from both the algorithm and hardware perspectives to meet the future needs of commercial products and national defense. In addition, it will catalyze advances in emerging AI applications across a broad range of sectors, including healthcare, autonomous vehicles, and Internet of things (IoT), triggering widespread implementation of AI in mobile and edge devices. New theories and techniques developed in this project will be integrated into undergraduate and graduate education and used to raise public awareness and promote understanding of the importance of AI security.<br/><br/>Data, code and results generated in this project will be stored when appropriate in the research database managed by the Holcombe Department of Electrical and Computer Engineering at Clemson University. All data will be retained for at least five years after the end of this project or at least five years after publications, whichever is later. Longer periods will apply when questions arise from inquiries or investigations with respect to research. The project repository will be maintained under http://ylao.people.clemson.edu/hardware_AI_security<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.

03/29/2024

03/29/2024

None

Grant

47.070

1

4900

4900

2426299

{'FirstName': 'Yingjie', 'LastName': 'Lao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yingjie Lao', 'EmailAddress': 'yingjie.lao@tufts.edu', 'NSF_ID': '000729841', 'StartDate': '03/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Tufts University', 'CityName': 'SOMERVILLE', 'ZipCode': '021442401', 'PhoneNumber': '6176273696', 'StreetAddress': '169 HOLLAND ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'WL9FLBRVPJJ7', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF TUFTS COLLEGE', 'ORG_PRNT_UEI_NUM': 'WL9FLBRVPJJ7'}

{'Name': 'Tufts University', 'CityName': 'SOMERVILLE', 'StateCode': 'MA', 'ZipCode': '021442401', 'StreetAddress': '169 HOLLAND ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

[{'Code': '171400', 'Text': 'Special Projects - CNS'}, {'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}]

['2022~15323', '2023~192639']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426299.xml'}

The Incoherent Scatter Radar Community and Research Workshop; San Diego, California; June 2024

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '06020200', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}

{'SignBlockName': 'Roman Makarevich', 'PO_EMAI': 'rmakarev@nsf.gov', 'PO_PHON': '7032927207'}

The Incoherent Scatter Radar Community and Research Workshop will be held in San Diego, California, in June 2024. For over 60 years, Incoherent Scatter Radars (ISRs) have provided the geospace community with valuable and unique data about the state of geospace over a vast range of altitudes, geographical locations, and time scales ranging from seconds to full solar cycles. These observations have contributed to significant advances in space science and fundamental plasma physics. The Workshop will facilitate ISR science by generating a report that outlines the state and direction of the ISR community, as well as action items to improve the community and dissemination of ISR associated materials. This workshop will generate research collaborations through research talks (prioritizing students and early-career researchers), discussions on open scientific problems, and by building a cohort of people interested in ISR science.<br/><br/>The 2024 workshop will begin developing: (1) a “living” long-term ISR community vision document, (2) a unified ISR data management plan, (3) an ISR Facility User Guide, (4) a standard ISR textbook, (5) highly qualified personnel development and training, and (6) a regular North American ISR community workshop. The proposing team is diverse, and this workshop had interest from a diverse group of individuals. The workshop also aims to have a strong student presence by overlapping with the student day at the Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR) Workshop 2024, encouraging students to attend and present at this workshop, and by working with the 2024 CEDAR student reps to have a presence during the CEDAR workshop.<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.

04/15/2024

04/15/2024

None

Grant

47.050

1

4900

4900

2426312

[{'FirstName': 'Gareth', 'LastName': 'Perry', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gareth Perry', 'EmailAddress': 'gperry@njit.edu', 'NSF_ID': '000801205', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Cooper', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew B Cooper', 'EmailAddress': 'mbc9@njit.edu', 'NSF_ID': '000945429', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lindsay', 'LastName': 'Goodwin', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lindsay V Goodwin', 'EmailAddress': 'lindsay.v.goodwin@njit.edu', 'NSF_ID': '000862665', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Longley', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William J Longley', 'EmailAddress': 'william.longley@njit.edu', 'NSF_ID': '000795766', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'New Jersey Institute of Technology', 'CityName': 'NEWARK', 'ZipCode': '071021824', 'PhoneNumber': '9735965275', 'StreetAddress': '323 DR MARTIN LUTHER KING JR BLV', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NJ10', 'ORG_UEI_NUM': 'SGBMHQ7VXNH5', 'ORG_LGL_BUS_NAME': 'NEW JERSEY INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New Jersey Institute of Technology', 'CityName': 'NEWARK', 'StateCode': 'NJ', 'ZipCode': '071021824', 'StreetAddress': '323 DR MARTIN LUTHER KING JR BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NJ10'}

{'Code': '420200', 'Text': 'Upper Atmospheric Facilities'}

2024~34300

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426312.xml'}

Collaborative Research: SHF: Medium: Heterogeneous Architecture for Collaborative Machine Learning

NSF

04/01/2024

06/30/2025

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Danella Zhao', 'PO_EMAI': 'dzhao@nsf.gov', 'PO_PHON': '7032924434'}

The recent breakthrough of on-device machine learning with specialized artificial-intelligence hardware brings machine intelligence closer to individual devices. To leverage the power of the crowd, collaborative machine learning makes it possible to build up machine-learning models based on datasets that are distributed across multiple devices while preventing data leakage. However, most existing efforts are focused on homogeneous devices; given the widespread yet heterogeneous participants in practice, it is urgently important but challenging to manage immense heterogeneity. The research team develops heterogeneous architectures for collaborative machine learning to achieve three objectives under heterogeneity: efficiency, adaptivity, and privacy. The proposed heterogeneous architecture for collaborative machine learning is bringing tangible benefits for a wide range of disciplines that employ artificial intelligence technologies, such as healthcare, precision medicine, cyber physical systems, and education. The research findings of this project are intended to be integrated with the existing courses and K-12 programs. Furthermore, the research team is actively engaged in activities that encourage students from underrepresented groups to participate in computer science and engineering research.<br/><br/>This project provides the theoretical underpinning and empirical evidence for an efficient, adaptive and privacy-preserving design under heterogeneity, which fills a critical void - the existing collaborative machine-learning approach fails to manage the immense heterogeneity in practice. This project centers on three aspects: (1) design of specialized neural architectures for heterogeneous hardware platforms to cope with the limited efficiency of collaborative training due to heterogeneity; (2) design of an efficient and adaptive knowledge-transfer framework to bridge heterogeneous participants based on their underlying proximity benefits; (3) privacy strategies for heterogeneous collaboration by identifying new vulnerabilities and developing privacy-preserving mechanisms. A general-purpose testbed is built to rigorously validate the proposed research and expand the impact of this project. It is expected that this project opens a new research paradigm to unleash the utmost potential of heterogeneous and collaborative machine 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.

04/19/2024

04/19/2024

None

Grant

47.070

1

4900

4900

2426318

{'FirstName': 'Xiaoyong', 'LastName': 'Yuan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaoyong Yuan', 'EmailAddress': 'xyyuan@mtu.edu', 'NSF_ID': '000826560', 'StartDate': '04/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'ZipCode': '296340001', 'PhoneNumber': '8646562424', 'StreetAddress': '201 SIKES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'SC03', 'ORG_UEI_NUM': 'H2BMNX7DSKU8', 'ORG_LGL_BUS_NAME': 'CLEMSON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'StateCode': 'SC', 'ZipCode': '296340001', 'StreetAddress': '201 SIKES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'SC03'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

['2021~74836', '2022~109022', '2023~90790']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426318.xml'}

Conference: Increasing student participation in the American Ecological Engineering Society 2024 conference

NSF

05/15/2024

10/31/2024

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': 'bhamilto@nsf.gov', 'PO_PHON': '7032920000'}

Ecological Engineering has been defined as “the design of sustainable ecosystems that integrate human society with the natural environment for the benefit of both” (Mitsch, 2012). Ecological engineering incorporates the disciplines of ecology and engineering to solve environmental problems and to design, build, and restore systems that provide long-term economic, environmental, and social benefits. As a field that seeks to integrate knowledge from across diverse fields to address today’s challenges, Ecological Engineering is an example of Growing Convergence Research, one of NSF’s 10 Big Ideas. This conference grant will increase student participation in the American Ecological Engineering Society (AEES) 2024 conference, deepening student engagement and ownership in the Ecological Engineering discipline. The funds will be used to support student activities at the 2024 annual meeting of AEES at Virginia Tech in Blacksburg, Virginia. The conference theme is: Ecological Engineering & Design: Launching a New Era, to emphasize the anticipated approval of ABET criteria, completion of the Ecological Engineering body of knowledge, and updated Certified Ecological Designers (CED) training. <br/><br/>This conference is expected to have approximately 200 to 225 attendees, nearly half of which are expected to be university students studying fields related to Ecological Engineering. By providing students with accommodation scholarships, presentation opportunities, and professional networking opportunities, this conference will directly contribute to NSF’s major initiative in Broadening Participation in STEM. Moreover, as the meeting theme is “Ecological Engineering & Design: Launching a New Era", this topic will provide an opportunity for students to learn how their field is advancing and will excite them in learning how the field is addressing some of society’s most pressing issues.<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.

05/28/2024

05/28/2024

None

Grant

47.041

1

4900

4900

2426320

[{'FirstName': 'Theresa', 'LastName': 'Wynn Thompson', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Theresa M Wynn Thompson', 'EmailAddress': 'tthompson@vt.edu', 'NSF_ID': '000245182', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jonathan', 'LastName': 'Czuba', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jonathan A Czuba', 'EmailAddress': 'jczuba@vt.edu', 'NSF_ID': '000715595', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Natasha', 'LastName': 'Bell', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natasha L Bell', 'EmailAddress': 'natashabell@vt.edu', 'NSF_ID': '000816224', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Co-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': '764300', 'Text': 'EnvS-Environmtl Sustainability'}

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426320.xml'}

OCE-PRF: Drivers of phenotypic diversity and adaptation in asexually propagating coral populations

NSF

10/01/2023

10/31/2024

{'Value': 'Standard Grant'}

{'Code': '06040000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'Timothy Crone', 'PO_EMAI': 'tjcrone@nsf.gov', 'PO_PHON': '7032924344'}

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>In this era of rapid environmental change and degradation, the survival of marine organisms will depend largely upon their ability to tolerate increasing environmental stress. However, the processes that drive resilience (e.g., the relative contribution of genetic versus environmental factors) remain largely a mystery. Corals are a major focus of current studies on organismal resilience because they are undergoing a worldwide decline, and they are so important for both the health of the oceans and the welfare of coastal communities. Corals often occupy and build habitats through asexual reproduction (production of clones), and it is widely assumed that such asexual populations may lack sufficient genetic diversity to respond to diverse environmental stressors. However, few previous studies have quantified the effects of asexual reproduction on the ability of corals to respond to environmental change. This research explores the different mechanisms that contribute to differences in coral stress response among two predominately clonal populations of the Caribbean thin finger coral (Porites divaricata) dwelling in distinct habitat types (mangroves vs. reef). This research will illuminate the drivers of organismal resilience, potentially impacting ongoing coral conservation and restoration efforts. It will also broaden the participation of underrepresented groups by encouraging active participation by local community members, students and scientists at the University of Belize, as well as providing unique training opportunities for next-generation scientists at the interface of field marine ecology and genomics. Importantly, these results will be communicated to a wide audience through diverse venues, including technical reports and management recommendations provided for government agencies and non-profit Belizean conservation organizations, popular articles and curricular materials for the community at large, and peer-reviewed manuscripts and presentations targeted to the scientific community.<br/><br/>Among conservation biologists and ecologists, there is an urgent effort underway to understand the causes of diversity in traits impacting organismal survival and reproduction. If we are to understand how natural populations will respond to environmental change, it is critical to understand how genetic, epigenetic, and environmental factors impact resilience. Such studies have advanced significantly in many plant species, but they are only just beginning to be applied to animals like corals. As in many plants, the model species used here— Caribbean thin finger coral (Porites divaricata)–reproduces primarily asexually, allowing us to compare the performance of clones in different environments and isolate the effects of genotype, epigenetics (namely DNA methylation), environment, and somatic mutations on variation in stress-related coral traits. Specially, combining fully-crossed reciprocally transplanted coral ramets across mangrove and reef sites with genomic and methylation sequencing data, this research will evaluate 1) the role of intra-genet variation accumulated during asexual reproduction in facilitating adaptation in the mangrove population, relative to roles of between-genet variation and phenotypic plasticity, 2) assess the role of new DNA methylation states, and 3) measure the rate of accumulation of new DNA methylation marks and base-changes during asexual reproduction. Results from this research effort will advance our understanding of the role of mechanisms like DNA methylation and somatic mutations in driving phenotypic variation in critical stress-response traits and how these mutations accumulate over time, provide insight into how such mechanisms are generated and inherited across asexual generations, build upon the sparse understanding of the role of novel habitat types, i.e. mangroves, in coral ecology and evolution; and generate novel molecular resources including the first reference genome assembly for the non-model coral, P. divaricata.<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.

05/07/2024

05/07/2024

None

Grant

47.050

1

4900

4900

2426345

{'FirstName': 'Karina', 'LastName': 'Scavo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karina Scavo', 'EmailAddress': 'kscavo@bu.edu', 'NSF_ID': '000840172', 'StartDate': '05/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Trustees of Boston University', 'CityName': 'BOSTON', 'ZipCode': '022151703', 'PhoneNumber': '6173534365', 'StreetAddress': '1 SILBER WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'THL6A6JLE1S7', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF BOSTON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Trustees of Boston University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '022151703', 'StreetAddress': '1 SILBER WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '820500', 'Text': 'OCE Postdoctoral Fellowships'}

2021~24818

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426345.xml'}

Conference: National Association of Plant Breeders (NAPB) Meeting 2024 - Rethink, Reinvent, Revolutionize: Innovation for Change

NSF

07/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Diane Jofuku Okamuro', 'PO_EMAI': 'dokamuro@nsf.gov', 'PO_PHON': '7032924508'}

Plant breeding is pivotal in addressing the three priorities for U.S. agriculture: plant health, production, and products; food safety, nutrition, and health; and bioenergy, natural resources, and the environment. Developing improved plant breeding practices is crucial for overcoming future agricultural challenges, including climate variability and the need for secure, sustainable, and nutritious food supplies. Each year, the National Association of Plant Breeders (NAPB) holds an annual conference that highlights cutting edge interdisciplinary research and the methodologies and technologies applied by today's plant breeders. In addition, this meeting seeks to educate young scientists on the latest methods for developing sustainable plants and provide a platform for networking and collaborations, ensuring that discoveries translate into commercially relevant products with real-world impact. NSF funds will be used to provide travel awards to students and early career investigators, especially those from underrepresented groups in STEM, to participate in the annual NAPB conference to be held July 21-25, 2024, in St. Louis (MO). <br/><br/>The 2024 NAPB Annual Conference will serve as a dynamic platform for scientists and professionals from diverse backgrounds to present research findings, network, discover cutting- edge research, and foster collaborations. By championing diversity and inclusion, the conference aims to enrich the plant breeding community with a broader range of perspectives, fostering more innovative research and improved agricultural practices. The event is poised to make significant strides in advancing the field of plant breeding, addressing key agricultural challenges, and cultivating a collaborative and inclusive community, thereby contributing to global food security and sustainable agricultural practices.<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.

06/18/2024

06/18/2024

None

Grant

47.074

1

4900

4900

2426347

{'FirstName': 'Martin', 'LastName': 'Bohn', 'PI_MID_INIT': 'O', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Martin O Bohn', 'EmailAddress': 'mbohn@illinois.edu', 'NSF_ID': '000315762', 'StartDate': '06/18/2024', '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': None}

{'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': '132900', 'Text': 'Plant Genome Research Project'}

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426347.xml'}

CAREER: Electrochemical pumping with high-temperature ionomers for challenging gas separations

NSF

12/01/2023

05/31/2027

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}

Hydrogen is an important energy vector and chemical feedstock and is expected to see wide-spread adoption because of its ability to decarbonize difficult sectors of the U.S. economy – e.g., fertilizer production, metal refining/steel production, and powering heavy duty vehicle transportation. Furthermore, hydrogen is a cost-effective energy storage solution for intermittent renewable electricity generation and when long-term seasonal energy storage is required. Meeting ambitious goals of greenhouse gas and carbon emission reduction necessitates the maturation of electrochemical technologies that generate, store, and distribute hydrogen. This project seeks to understand how electrode polymeric binder materials in electrochemical hydrogen pumps (EHPs) affect the efficiency performance for hydrogen purification from challenging gas mixtures that contain low hydrogen concentrations (1% to 20%). This is important because it is posited that U.S.’s existing natural gas pipelines may have the ability to store and distribute hydrogen from centralized production facilities. Leveraging existing infrastructure can reduce the cost of hydrogen to end users as hydrogen storage and distribution make up a large portion of the cost of hydrogen today. However, endpoint use applications necessitate pure hydrogen at high pressures. Hence, EHPs are promising technology to separate hydrogen from gas mixtures while simultaneously compressing it. Advancing materials’ performance and durability for electrochemical hydrogen pumps, such as electrode binders, can reduce capital costs for EHPs while also improving their energy efficiency. Electrochemical processes are poised to decarbonize chemical processes and is paramount to train future engineers proficient in electrochemical engineering and electrochemical systems integration. This project will commission the first electrochemical unit operation, an EHP, in Penn State’s Unit Operations Laboratory to give students hands-on training with electrochemical systems. Outreach activities for this project will engage and recruit individuals from rural communities in central Pennsylvania to teach them about sustainable chemical manufacturing using electrochemical systems.<br/><br/>The overall goal of this fundamental research project aims to understand how electrode ionomer binders’ composition and processing influence hydrogen diffusivity and hydrogen oxidation/evolution reaction kinetics in high-temperature polymer electrolyte membrane (HT-PEM) electrochemical hydrogen pumps (EHPs). With the advent of ion-pair HT-PEMs and phosphonic acid ionomer electrode binders, preliminary experiments demonstrated hydrogen separations from syngas, and other reformed hydrocarbons with varying hydrogen and carbon monoxide concentrations, to +99.3% hydrogen at 1 A cm-2. In these experiments, it was observed that cell polarization was largely governed by hydrogen content in the gas mixture feed because CO poisoning was minimized. Addressing EHP cell polarization with gas feeds containing low hydrogen content requires new electrode binders that promote hydrogen diffusivity and foster better electrocatalyst utilization. This project will establish structure-property relationships that correlate ionomer composition and processing to reaction kinetics-transport properties. These ionomer electrochemical properties will be probed as thin films on interdigitated electrode arrays decorated with nanoscale electrocatalysts afforded from block copolymer templating. EHP studies with membrane electrode assemblies containing the new ionomers will be used for understanding cell polarization behavior for purifying hydrogen from gas mixtures with low hydrogen content.<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.

04/15/2024

04/15/2024

None

Grant

47.041

1

4900

4900

2426358

{'FirstName': 'Christopher', 'LastName': 'Arges', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher Arges', 'EmailAddress': 'cga5126@psu.edu', 'NSF_ID': '000716707', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606375418', 'PhoneNumber': '7737028669', 'StreetAddress': '5801 S ELLIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'ZUE9HKT2CLC9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': 'ZUE9HKT2CLC9'}

{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606375418', 'StreetAddress': '5801 S ELLIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}

[{'Code': '150400', 'Text': 'GOALI-Grnt Opp Acad Lia wIndus'}, {'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}]

['2022~241716', '2023~144829']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426358.xml'}

Compact Optomechanical Seismic Sensors for LIGO

NSF

04/01/2024

10/31/2025

{'Value': 'Standard Grant'}

{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}

{'SignBlockName': 'Pedro Marronetti', 'PO_EMAI': 'pmarrone@nsf.gov', 'PO_PHON': '7032927372'}

This award supports further development of novel compact optomechanical seismic sensing technologies that strive to provide highly sensitive measurements of seismic phenomena. Seismic activity and slow vibrations impact suspended platforms that operate in environments of low pressure (vacuum) and low temperatures (cryogenics). This project will develop a prototype optomechanical seismic sensor that will allow the team to investigate its performance under laboratory conditions. Understanding the instrument parameters of sensitivity and bandwidth, and its functionality on a suspended platform in vacuum, will help determine their expected behavior in future gravitational wave observatories, such as LIGO Voyager, which is the target application of this research. However, this type of device will likely benefit other areas in science and industrial applications such as seismology, geodesy, precision measurements of vibrations, generally inertial sensing and inertial navigation, where high sensitivity compact instruments are impactful. Furthermore, this award will support the participation and contributions of this research group to the international LIGO Scientific Collaboration and the gravitational wave community at large; allowing the training of our students in STEM areas and helping to educate the local community in topics related to gravitational waves.&lt;br/&gt; &lt;br/&gt;This project targets the development of compact and highly sensitive optomechanical seismic sensors for the Laser Interferometer Gravitational-Wave Observatory (LIGO). The proposed sensors will be readily compatible with vacuum environments and aim at high-quality measurements below 100 mHz. It is also planned to test first prototypes on relevant platforms within the LIGO Scientific Collaboration (LSC). In addition, the team will investigate the fabrication of these sensors with materials compatible with cryogenic environments. This project introduces novel technologies involving inertial sensing and high precision displacement measurements via laser interferometry within the context of ground-based gravitational wave astronomy. Furthermore, this research will pave the way for the development of cryogenic-compatible devices that could be installed in future generation gravitational wave observatories. Advancing novel technologies to levels where they become portable and can be deployed offers a wide variety of relevant interdisciplinary aspects within STEM areas for the training of future experimental physicists and engineering professionals.&lt;br/&gt;&lt;br/&gt;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.

03/25/2024

03/25/2024

None

Grant

47.049

1

4900

4900

2426360

{'FirstName': 'Felipe', 'LastName': 'Guzman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Felipe Guzman', 'EmailAddress': 'felipe@tamu.edu', 'NSF_ID': '000792534', 'StartDate': '03/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Arizona', 'CityName': 'TUCSON', 'ZipCode': '85721', 'PhoneNumber': '5206266000', 'StreetAddress': '845 N PARK AVE RM 538', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'AZ07', 'ORG_UEI_NUM': 'ED44Y3W6P7B9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ARIZONA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Arizona', 'CityName': 'TUCSON', 'StateCode': 'AZ', 'ZipCode': '85721', 'StreetAddress': '845 N PARK AVE RM 538', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'AZ07'}

{'Code': '1252', 'Text': 'LIGO RESEARCH SUPPORT'}

2022~163922

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426360.xml'}

Planning: GRANTED: A Consortium-Based, Stacked Mentorship Model for Building Inter-Institutional Research Capacity, Access, and Collaboration

NSF

06/01/2024

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '01060000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}

{'SignBlockName': 'Dina Stroud', 'PO_EMAI': 'dstroud@nsf.gov', 'PO_PHON': '7032925015'}

This planning project aims to advance research capacities that build on existing research enterprise strengths and opportunities concerning the state of research across a consortium of eight institutional partners in the Equity in Architectural Education Consortium (EAEC). The consortium includes Florida A&M University, Florida International University, Hampton University, Howard University, Morgan State University, Tuskegee University, the University of Oklahoma, and the University of Michigan. While multi-institutional, interdisciplinary collaborations are widespread amongst our nation’s top research institutions, this project focuses on better understanding the challenges and opportunities that come from inter-institutional collaboration between institutions that are very different from one another, varying with respect to infrastructure, capacity, mission, size, location, populations served, and public/private status. The project posits that widespread change and growth in the nation’s research enterprise can be accelerated via mixed-type, complementary, inter-institutional collaboration, a model that has the potential to amplify existing resources and capacity at all participating institutions. <br/><br/><br/>The Equity in Architectural Education Consortium (EAEC, est. 2018) is an eight-member, inter-institutional network that spans R1, R2, D/PU, M2, MSI, HBCU, HSI, PWI, public, private, small, medium, large, rural, suburban, and urban institution types. The EAEC’s principal initiative, the Stacked Mentorship Program cultivates a meta-mentorship community among students, faculty, staff, and professionals of color, and other underrepresented minorities in architecture, creating a framework for inter-institutional collaboration. This planning project will design a national EAEC Fellowship Program that leverages the capacities of each consortium partner while serving as an agile model for building research capacity. Each of the eight institutional leads will gather insights from across their institution, clarify, and collectively design fellowship program initiatives and projects that address the goals and functional research infrastructure needs of EAEC partners across the eight sectors in the NSF GRANTED wheel. The projected impacts include: 1) intra- and inter-institutional capacity building; 2) research on the research enterprise; and 3) improvement of research infrastructure, especially regarding emerging and minority serving institutions. This model amplifies existing resources at all participating institutions because “plugging” gaps at one institution with complementary resources from another can protect human capital at historically under-resourced partners and allow for access to research opportunities out of the reach of a single institution. The planning project’s design process will result in a matrix of fellowship projects and initiatives that model approaches for a spectrum of research institutions to address various pathways to broadening and increasing research. This planning project spans organizations with very different resource bases (both strengths and gaps) and a broad diversity of priorities (overlapping and distinct). The project’s long-term objective is to create lasting effects by increasing the participation of historically underrepresented and under-resourced institutions and individuals in STEM, while developing a more equitable, globally competitive STEM workforce that better reflects the diverse and pluralistic composition of our nation’s research enterprise.<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.

05/28/2024

05/28/2024

None

Grant

47.083

1

4900

4900

2426365

[{'FirstName': 'Carmina', 'LastName': 'Sanchez-del-Valle', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carmina Sanchez-del-Valle', 'EmailAddress': 'carmina.sanchez@hamptonu.edu', 'NSF_ID': '000478558', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Irene', 'LastName': 'Hwang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Irene Hwang', 'EmailAddress': 'ihwang@umich.edu', 'NSF_ID': '000954399', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Andrew', 'LastName': 'Chin', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew D Chin', 'EmailAddress': 'andrew.chin@famu.edu', 'NSF_ID': '000960476', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Co-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': '221Y00', 'Text': 'GRANTED'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426365.xml'}

CAS: Copper-Catalyzed Oxidation Reactions of Carboxylic Acids

NSF

06/15/2024

07/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Laura Anderson', 'PO_EMAI': 'laanders@nsf.gov', 'PO_PHON': '7032922934'}

With the support of the Chemical Catalysis Program in the Division of Chemistry, Jessica Hoover of West Virginia University is investigating new catalysts to convert carboxylic acids to value-added compounds, taking advantage of the favorable energetics associated with carbon dioxide release from such compounds. The investigation of new reactions of carboxylic acids can help advance the use of abundant and renewable resources as chemical feedstocks, as a good number of carboxylic acids are available from biomass sources. Dr. Hoover and her research team are identifying new catalysts to tune and control oxidation and decarboxylation reactions of carboxylic acids. These activities include developing a fundamental understanding of how the catalysts work to carefully adapt their applications. This research program is further providing research experiences to future West Virginia teachers to support and enrich chemistry education in the state. Dr. Hoover is also involved in career planning activities for both graduate and undergraduate chemistry students to support their futures in STEM (science, technology, engineering and mathematics) disciplines.<br/><br/>Catalyst-controlled conversion of carboxylic acids to a variety of molecular fragments is an attractive strategy for the synthesis of complex chemical structures because carboxylic acid starting materials are abundant, stable and can be obtained from renewable sources. Currently, this strategy has practical limitations because methods to convert carboxylic acids into value-added materials are restricted to coupling reactions of benzoic acids, in which the carboxylic acid group is replaced with a new functional group through a combined decarboxylative and oxidative process. Dr. Hoover and her research group are exploring new copper-catalyzed reactions that separate the oxidation and decarboxylation steps of carboxylic acid coupling reactions to allow the controlled divergent conversion of carboxylic acids to compounds that are important intermediates in the synthesis of biologically active and pharmaceutically relevant molecules. Mechanistic studies of these systems are being used to aid in understanding the overall reaction pathway and how reaction conditions can be adjusted to favor the oxidation and/or decarboxylation steps. These activities are supporting the training and development of graduate and undergraduate researchers in the interdisciplinary fields of catalysis, organic and organometallic synthesis, and reaction mechanism elucidation to prepare them for future careers in the chemical 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.

05/22/2024

05/22/2024

None

Grant

47.049

1

4900

4900

2426388

{'FirstName': 'Jessica', 'LastName': 'Hoover', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jessica M Hoover', 'EmailAddress': 'jessica.hoover@mail.wvu.edu', 'NSF_ID': '000638786', 'StartDate': '05/22/2024', 'EndDate': None, 'RoleCode': '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': '688400', 'Text': 'Chemical Catalysis'}

2021~136283

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426388.xml'}

Conference: NSF Student Travel Grant for 2024 Privacy Enhancing Technologies Symposium (PETS)

NSF

05/01/2024

04/30/2025

{'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': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}

This proposal supports student travel for about 20 students to attend the 2024 Privacy Enhancing Technology Symposium (PETS), to be held in Bristol, United Kingdom, from July 15-20, 2024. PETS is a leading venue for quick and wide dissemination of cutting-edge research that address the design and realization of privacy services for the Internet and other data systems and communication networks by bringing together anonymity and privacy experts from around the world to discuss recent advances in, and new perspectives on privacy. This travel grant will enable a number of students with financial need to attend the conference, providing them the opportunity to discuss leading edge research with world-class computer researchers in privacy, and establish professional connections and mentoring relationships that will serve them well during their research careers.<br/><br/>This grant provides travel support to encourage participation in the 2024 PETS conference by students who would normally find it difficult to attend. Criteria for selection include evidence of a serious interest in the field, as demonstrated by research output, coursework and/or project experience. The organizers will also encourage participation by students from groups under-represented in computer security and ensure that students from a range of institutions are represented.<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.

05/03/2024

05/03/2024

None

Grant

47.070

1

4900

4900

2426419

{'FirstName': 'Damon', 'LastName': 'McCoy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Damon McCoy', 'EmailAddress': 'dm181@nyu.edu', 'NSF_ID': '000616444', 'StartDate': '05/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'ZipCode': '100121019', 'PhoneNumber': '2129982121', 'StreetAddress': '70 WASHINGTON SQ S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'NX9PXMKW5KW8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100121019', 'StreetAddress': '70 WASHINGTON SQ S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}

2024~21000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426419.xml'}

Conference: Student Support for the 5th IFAC Workshop on Cyber-Physical and Human Systems (CPHS) 2024

NSF

05/15/2024

04/30/2025

{'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': 'David Corman', 'PO_EMAI': 'dcorman@nsf.gov', 'PO_PHON': '7032928754'}

The International Federation of Automatic Control (IFAC) Workshop on Cyber-Physical-Human Systems (CPHS) brings together researchers and practitioners to gain understanding from a range of disciplines united in CPHS systems. This specific workshop looks to broaden participation in CPHS in the uniquely interdisciplinary and intersection of modeling, analysis and control of integrated CPHS and social and societal aspects of CPHS. The workshop is in Antalya, Turkey in December, 2024. The CPHS community is uniquely positioned to contribute to this goal. <br/><br/>The CPHS’24 includes a broad community of researchers from academia and industry. Their research includes navigation, estimation, control, communication, networking, learning, and computing and other areas. This fusion not only advances knowledge in traditional CPHS areas but also catalyzes innovation in ergonomics, assistive technology, interactive design, medical technology, public wellness, farming, and public infrastructure. The conference is directly before the Conference on Decision and Control 2024 and located to facilitate participation in both. The conference focus on Cyber Human systems has broad implications in multiple application domains where autonomy is becoming pervasive but requires significant integrated activity in modeling, human behavior and teaming, and consideration of societal aspects.<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.

05/13/2024

05/13/2024

None

Grant

47.041, 47.070

1

4900

4900

2426426

{'FirstName': 'Kadriye Merve', 'LastName': 'Dogan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kadriye Merve Dogan', 'EmailAddress': 'k.merve.dogan@gmail.com', 'NSF_ID': '000824481', 'StartDate': '05/13/2024', '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': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}, {'Code': '791800', 'Text': 'CPS-Cyber-Physical Systems'}]

2024~19500

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426426.xml'}

CAREER: Developing novel biomarker proxies to constrain Neogene changes in African woody cover and paleoecological contexts of hominin evolution

NSF

10/01/2023

08/31/2025

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Yurena Yanes', 'PO_EMAI': 'yyanes@nsf.gov', 'PO_PHON': '7032922649'}

Today humans rely on grasses (e.g., corn, wheat, and rice) as a primary food source and for feeding livestock. This dependence on grasses has deep roots. Humans and their ancestors evolved in concert with grassland ecosystems in Africa over the past 7 million years. Despite the well-documented association between human evolution and grasslands, little is known about the origin of grasses in Africa, especially before 10 million years ago. When and how did grasses rise to ecological dominance? Lack of knowledge on this subject is largely due to the sparse plant fossil record. To understand how grasslands may have shaped the evolutionary trajectory of our species and other mammals, new, widely applicable approaches are needed to reconstruct ancient ecosystems. This project is developing new methods for reconstructing vegetation in past ecosystems using molecular plant fossils preserved in ancient sediments. Combining these approaches with existing isotopic methods, the researcher is reconstructing the rise of grasslands in East Africa over the past ~25 million years and exploring the relationships between climate, ecosystem, and evolutionary change. The results could produce new insights on the interconnectedness of climate, ecosystems and human evolution over geological timescales. A parallel objective throughout the project is to support students in their pursuit of STEM careers with an emphasis on increasing participation of underrepresented groups in the Earth sciences. The project includes intensive three-week field and lab courses for graduate students and postdocs from the US and African nations, lab-based research opportunities for undergraduate and New York City high school students, and support for a graduate student to conduct PhD research. <br/><br/>African terrestrial ecosystems underwent revolutionary change in the Neogene. Sparse paleobotanical evidence suggests that denser forested ecosystems gave way to more open forests, woodlands, and perhaps nascent grasslands near the end of the early Miocene to the middle Miocene. This same period (~19 to 13 Ma) was marked by major changes in the primate and large mammal communities, yet the paleoecological context remains poorly known. By the late Miocene (10 Ma), carbon isotopic evidence shows that C4 grasslands began to spread. Despite the firm record of C4 grassland expansion beginning at 10 Ma, the role of ecological change in mammalian and human evolution through most of the Neogene has been insufficiently addressed. The Principal Investigator is developing organic geochemical approaches for reconstructing terrestrial ecosystem structure using modern ecosystems. This includes methods to estimate the fraction of woody cover from n-alkane molecular distributions and to measure grass abundance using PTMEs. Modern ecosystem research will also yield carbon and hydrogen isotope enrichment factors between biomarkers, bulk plant tissue, and soils. The researcher is applying these methods to terrestrial and marine sedimentary records from the Neogene Period in Africa to determine when and how grasslands became ecologically significant and how ecosystem change may have affected faunal and human evolution. The project will incorporate postdocs and graduate, undergraduate, and high school students into research, training, and field work. This includes developing a three-week paleoecology short course in Kenya for graduate students and postdocs from US institutions and African nations. The Principal Investigator is also providing research opportunities in his lab, built on a tiered mentoring program, for high school and undergraduate students from New York City. This program has high participation rates of students from underrepresented groups and serves as a pipeline for first-generation college students, many of whom ultimately major in STEM fields. One graduate student will be trained and supported by this project.<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.

05/02/2024

05/02/2024

None

Grant

47.050

1

4900

4900

2426448

{'FirstName': 'Kevin', 'LastName': 'Uno', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kevin T Uno', 'EmailAddress': 'kevinuno@fas.harvard.edu', 'NSF_ID': '000642427', 'StartDate': '05/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385366', 'PhoneNumber': '6174955501', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'LN53LCFJFL45', 'ORG_LGL_BUS_NAME': 'PRESIDENT AND FELLOWS OF HARVARD COLLEGE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385369', 'StreetAddress': '1033 MASSACHUSETTS AVE 5TH FL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}

{'Code': '745900', 'Text': 'Sedimentary Geo & Paleobiology'}

['2021~111941', '2022~167910', '2023~118344']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426448.xml'}

Collaborative Research: Center for Coatings Research

NSF

05/01/2024

04/30/2026

{'Value': 'Continuing Grant'}

{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}

{'SignBlockName': 'Pedro Marronetti', 'PO_EMAI': 'pmarrone@nsf.gov', 'PO_PHON': '7032927372'}

The Center for Coatings Research (CCR) focuses on the development of advanced mirror coatings for gravitational wave detectors, a new and booming field of observational astrophysics. By reducing mechanical loss and thus thermal noise in mirror coatings, the project aims to enhance the sensitivity of Cosmic Explorer (CE), the proposed third generation gravitational wave detector. This research holds significant importance as it expands our understanding of the universe by enabling observations of cosmic events, such as the collision of remnants from the first stars. Moreover, the project has broader impacts on precision measurement technology, benefiting areas like precision timing, quantum information, low noise interferometry, and the search for deviations in the gravitational inverse-square law. The outcomes of this research can also have implications for the semiconductor, laser, and quantum computing communities, as correlations between mechanical loss and other loss mechanisms are explored. Additionally, this collaboration between materials science and gravitational wave communities promotes education and diversity, providing research opportunities for students at different education levels and advancing the participation of women and underrepresented minorities.<br/><br/>This project aims to develop mirror coatings that meet the mechanical and optical requirements for implementation in CE. Through extending the length of the interferometer arms from the current 4 km to 20 and/or 40 km systems, CE's observational reach will be significantly expanded. To fully utilize this infrastructure, improvements are necessary in the mirror coatings' mechanical loss and thermal noise reduction. The CCR combines groups working on coating deposition, characterization of atomic structure and macroscopic material properties, and computational modeling. These components are often performed by three diverse communities that work in relative isolation from each other. The strength of the CCR and its promise for accelerating discoveries arises from close integration of these communities focusing on a unified research goal. Since the formation of the CCR in 2017, the collaboration has become a knowledge repository for gravitational wave detector coatings research, making significant progress on all the proposed research directions, including uncovering atomic structural motifs associated with room temperature vs cryogenic mechanical losses, using that understanding to develop Ti:GeO2 coatings that can meet the requirements for Advanced LIGO + (A+). Going forward research efforts include the development of improved amorphous coatings and crystalline AlGaAs coatings. The project will investigate atomic structural motifs associated with mechanical losses at different temperatures, aiming for at least a two-fold reduction in thermal noise compared to Advanced LIGO + coatings. CCR contributions have implications for precision measurement, impacting various fields and potentially benefiting the semiconductor, laser, and quantum computing communities. Overall, this research advances the field of gravitational wave detection, supports education at multiple levels, and promotes diversity within the physical sciences.<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.

04/25/2024

04/25/2024

None

Grant

47.049

1

4900

4900

2426460

{'FirstName': 'Hai-Ping', 'LastName': 'Cheng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hai-Ping Cheng', 'EmailAddress': 'ha.cheng@northeastern.edu', 'NSF_ID': '000307254', 'StartDate': '04/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '125200', 'Text': 'LIGO RESEARCH SUPPORT'}

['2023~179406', '2024~27000']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426460.xml'}

I-Corps: Translation potential of probiotic bacterial extracellular vesicle technology for inflammatory bowel disease

NSF

07/01/2024

06/30/2025

{'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 new class of therapeutics based on bacterial extracellular vesicles for treatment of numerous diseases. Bacterial extracellular vesicles can potentially be produced at low cost and have numerous biotechnological applications including vaccines, therapeutics for inflammatory diseases, and drug delivery vehicles. In particular, most inflammatory diseases lack desirable treatments or cures, with an unmet need existing between first line therapies and more aggressive antibody-based therapies that require costly and laborious administration via intravenous infusions. This unmet need is particularly noteworthy for inflammatory gastrointestinal diseases (e.g., inflammatory bowel disease) and inflammatory skin conditions (e.g., dermatitis). Bacterial extracellular vesicles offer the safety and convenience of first line therapies, which are typically oral small molecule drugs with favorable safety profiles, and with the potential for improved efficacy like later line therapies. Clinical translation of bacterial extracellular vesicles has been hindered by low production rates from cells and lack of tools to further improve efficacy. These challenges present untenable manufacturing costs and biologic risk when translating results from mice to humans.<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 vectors for oral delivery of immunotherapies for treatment of gastrointestinal diseases. Most therapeutics for inflammatory bowel diseases lack desirable delivery. Drugs unstable in the gastrointestinal tract require injection, and drugs with poor biodistribution and pharmacokinetics have limited efficacy and potential for systemic toxicity. The technology addresses these limitations in gastrointestinal disease treatment by leveraging bacterial extracellular vesicles - cell-secreted biologic nanoparticles naturally used by the healthy gut microbiome to communicate with human cells. The technology exploits this phenomenon by solving the most immediate bottlenecks facing bacterial extracellular vesicles therapeutics: potency and scalable biomanufacturing. The technology enables mass production of probiotic bacterial extracellular vesicles with high potency. Preclinical data in small animal models has demonstrated the technology function.<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.

06/25/2024

06/25/2024

None

Grant

47.084

1

4900

4900

2426476

{'FirstName': 'Steven', 'LastName': 'Jay', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Steven M Jay', 'EmailAddress': 'smjay@umd.edu', 'NSF_ID': '000685820', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426476.xml'}

Planning: CRISES: Planning for a Future Center on Sustainability and Governance in the Anthropocene (C-SAGA)

NSF

12/15/2023

08/31/2024

{'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'}

Current planetary crises, like climate change, biodiversity loss, and unsustainable development are accelerating rapidly due to human activity. These environmental problems are increasing in complexity and cannot be solved by simple technological fixes. Policies to address these interlinked challenges need to draw on the best available science while also ensuring that they do not create unintended consequences, especially for people who are already vulnerable. This planning grant will enable researchers at Rutgers University to work together with other scientists around the globe to explore possible solutions to these problems through case studies across fisheries, food systems, and biodiversity and invasive species that illuminate effective and innovative policies and identify key gaps in environmental governance. The team’s engagement with global partners contributes to the strengthening of international social science exchanges and partnerships on environmental challenges. Through these collaborations, the anticipated center will be a catalyst to activate social science insights and build a suite of techniques and technologies across cases that can be shared with partners in policy institutions, NGOs, local communities, and elsewhere. <br/> <br/>This planning grant will allow the research team to design a future Center on Sustainability and Governance in the Anthropocene (C-SAGA). Barriers to governing include the increasing complexity and interdependence of ecological and socio-economic systems; spatially and temporally distant and diffuse environmental impacts; novel conditions of deep uncertainty; and the potential for irreversible tipping points, cascades and feedbacks. Ensuring that any response to these Anthropocene challenges is grounded in justice is crucial. The innovation of the center will be to coordinate and advance cutting-edge social science scholarship to identify innovative mechanisms, behaviors and structures that can facilitate new forms of governance. The proposed C-SAGA center will engage in transdisciplinary research on new forms of governance for our current environmental challenges, particularly policies and innovations that improve stakeholder participation, involve different knowledge systems, and help create more equitable outcomes for all through engaging with stakeholders and policymakers to design and implement new experiments in transformative policy. The future center will be designed around experiments in innovation, diffusion and learning, including developing incubators for governance actors to exchange and scale up models, and training to improve capacities in governing across knowledges and scales. In exploring gaps in governance for sustainable socio-ecological transformations and opportunities for collaborations with other institutions and potential partners, the research team will create the foundations for a future proposal for a research center that meets local, national, and global 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.

04/08/2024

04/08/2024

None

Grant

47.075

1

4900

4900

2426487

{'FirstName': 'Pamela', 'LastName': 'McElwee', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pamela D McElwee', 'EmailAddress': 'pamela.mcelwee@rutgers.edu', 'NSF_ID': '000571546', 'StartDate': '04/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

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

2023~99470

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426487.xml'}

Workshop on advancing fluid and soft-matter dynamics with machine learning and data science

NSF

06/01/2024

05/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Shahab Shojaei-Zadeh', 'PO_EMAI': 'sshojaei@nsf.gov', 'PO_PHON': '7032928045'}

This award provides funds to partially support participants in a workshop on advancing fluid and soft-matter dynamics with machine learning and data science. This workshop brings together researchers on these topics to share their research and perspectives on the state of this rapidly evolving area of science and engineering. It also provides a unique opportunity for exchanging ideas between fluid dynamics, soft matter, and machine learning communities, since members of these communities are not necessarily in contact with one another through the normal dissemination venues such as conferences and publications. The participants are from a diverse group of researchers including those from underrepresented groups, early career scientists, and faculty from non-R1 institutions. The structure of the workshop as a small, highly interactive forum with explicit time set aside for discussion will promote cross-fertilization and development of new relationships and collaborations. <br/><br/>Recent years have seen an explosion in the use of machine learning and data science tools in Newtonian fluid dynamics, in part due to the availability of software environments for implementing these tools as well as because of improvements in algorithms and computing speed. Relevant applications of machine learning and data science include data-driven closures for RANS models, nonlinear dimension reduction and data-driven time evolution modeling for control applications and combining velocimetry and machine learning to improve velocity field measurements. In soft-matter dynamics, especially non-Newtonian fluid mechanics, machine learning and data science have begun to aid in development of effective constitutive models for very complex soft materials and efficient representations of complex data sets as arise for example in X-ray scattering measurements of complex-fluid microstructure. The workshop will provide a unique forum for researchers across a spectrum of applications, but with common goals and overlapping tools, to learn from one another, and thereby more effectively use machine learning and data science ideas and tools to advance fluid and soft-matter 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.

05/21/2024

05/21/2024

None

Grant

47.041

1

4900

4900

2426488

{'FirstName': 'Michael', 'LastName': 'Graham', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael D Graham', 'EmailAddress': 'mdgraham@wisc.edu', 'NSF_ID': '000272283', 'StartDate': '05/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}

[{'Code': '141500', 'Text': 'PMP-Particul&MultiphaseProcess'}, {'Code': '144300', 'Text': 'FD-Fluid Dynamics'}]

2024~10000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426488.xml'}

Conference: SRCOS Summer Research Conference in Statistics and Biostatistics

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Tapabrata Maiti', 'PO_EMAI': 'tmaiti@nsf.gov', 'PO_PHON': '7032925307'}

The 59th Summer Research Conference (SRC) and Statistics Undergraduate Research Experience (SURE) will be held in Clemson, South Carolina on June 2-5, 2024. The Southern Regional Council on Statistics (SRCOS) is a consortium of statistics and biostatistics programs from 45 universities in 16 states in the Southern region. The SRC is an annual conference sponsored by the SRCOS. The purpose of the SRC is to encourage the interchange and mutual understanding of current research ideas in statistics and biostatistics, and to provide motivation and direction to further research progress. The SRC will give new researchers an opportunity to participate in the meeting and to interact closely with leaders in the field in a manner not possible at larger meetings. In addition to the graduate student participation, the 59th SRC will also include the fifth annual Statistical Undergraduate Research Experience (SURE) from June 3-5, 2024. SURE is a conference within a conference aimed to encourage the participation of undergraduate students from under-represented groups to pursue graduate education and career opportunities in STEM fields. SURE will include events specifically for undergraduate students and undergraduate mentors, such as a panel about career opportunities in statistics, a real data analytics workshop, and a speed-mentoring session with current statistics and biostatistics graduate students.<br/><br/>The SRC is particularly valuable for graduate students, isolated statisticians, and faculty from smaller regional schools in the southern region at drivable distances without the cost of travel to distant venues. Speakers will present formal research talks with adequate time allowed for clarification, amplification, and further informal discussions in small groups. Under the travel support provided by this award, graduate students will attend and present their research in posters to be reviewed by more experienced researchers. Participation in SURE will encourage under-represented students to enter STEM fields, including statistics or biostatistics, and provide training to support this endeavor. The 59th SRC will strengthen the research of the statistics and biostatistics community as a whole and help bridge the gap for under-represented groups to pursue statistics or biostatistics, particularly in the sixteen states of the Southern Region. The SRCOS website can be found here: https://www.srcos.org; the 59th SRC website can be found here: https://www.srcos.org/conference; the SURE website can be found here: https://www.srcos.org/sure.<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.

04/29/2024

04/29/2024

None

Grant

47.049

1

4900

4900

2426499

[{'FirstName': 'Katherine', 'LastName': 'Thompson', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Katherine L Thompson', 'EmailAddress': 'katherine.thompson@uky.edu', 'NSF_ID': '000653124', 'StartDate': '04/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Gregory', 'LastName': 'Hawk', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gregory S Hawk', 'EmailAddress': 'greg.hawk@uky.edu', 'NSF_ID': '0000A02X0', 'StartDate': '04/29/2024', 'EndDate': None, 'RoleCode': 'Co-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': '126900', 'Text': 'STATISTICS'}

2024~34920

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426499.xml'}

CAREER: Enantioselective Syntheses of Organoboron Compounds via Transition-Metal Catalysis

NSF

05/15/2024

03/31/2027

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Laura Anderson', 'PO_EMAI': 'laanders@nsf.gov', 'PO_PHON': '7032922934'}

With the support of the Chemical Synthesis Program in the Division of Chemistry, Dr. Ming Chen of Auburn University is studying new ways to make organoboron compounds, which are important chemical building blocks. Professor Chen and his research group are developing reactions to make molecules with two distinct boryl groups on the same carbon atom (diboryl reagents) with control of handedness or stereochemistry and then to sequentially and selectively utilize each boryl group to attach new molecular fragments to the central carbon. This strategy has the potential to facilitate modular access to novel molecular building blocks that are valuable to organic synthesis, material science, as well as the agrochemical and pharmaceutical industries. Professor Chen and his team are also engaged in outreach activities through the Auburn University Summer Science Institute to provide K-12 students with hands-on research opportunities and an introduction to chiral molecules (non-superimposable mirror images like right- and left-hands) to help boost motivation in pursuing careers in STEM (science, technology, engineering, and mathematics)-related disciplines.<br/><br/>Chiral, non-racemic organoboron compounds are important building blocks in organic synthesis, material science, and medicinal chemistry. The versatile synthetic utility of chiral organoboron compounds provides an excellent platform for further derivatization to generate valuable downstream products for chemical synthesis. Dr. Chen and his research group are developing new asymmetric transformations to prepare chiral, non-racemic organoboron compounds from 1,1-bisborylalkanes with two chemically distinct boryl groups. A cobalt-catalyzed hydroboration is also being studied to access enantioenriched 1,1-bisborylalkanes to support the investigation of these compounds as building blocks for more complex organoboron structures. Fundamental studies on the reactivity of 1,1-bisborylalkanes with two chemically distinct boryl groups are expected to provide insight into how to best leverage the properties of these reagents to access classes of enantioenriched organoboron compounds that are not accessible through current methodologies. These activities are providing an excellent training ground in modern, stereocontrolled synthetic chemistry for a diverse group of graduate and undergraduate 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.

05/07/2024

05/07/2024

None

Grant

47.049

1

4900

4900

2426500

{'FirstName': 'Ming', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ming Chen', 'EmailAddress': 'mzc0102@vt.edu', 'NSF_ID': '000786219', 'StartDate': '05/07/2024', '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': '687800', 'Text': 'Chemical Synthesis'}

['2021~95492', '2022~420816']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426500.xml'}

NSF-NFRF: Climate Adaptation and Resilience Strategies (CLARS): Socio-Economic Vulnerabilities among Urban Migrants in the Lake Victoria Basin and Great Lakes Region

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

The projected impacts of climate change on human mobility are staggering, with estimates suggesting that anywhere from 200 million people by 2050 to 2 billion people by 2100 will be on the move due to environmental changes across the globe. Research on climate migration has traditionally focused on the factors that attract or force individuals to relocate such as better opportunities for education and jobs and the impact of violence and poverty. One particularly understudied aspect of climate-driven migration is how the influx of people might affect communities in receiving cities already at-risk due to climate change impacts. The Climate Adaptation and Resilience Strategies (CLARS) project aims to address this through a community engagement, urban models and decision support tools that involves stakeholders from diverse sectors in the Lake Victoria Basin (LVB) in Africa and the Great Lakes Region (GLR) in North America. CLARS will test and refine adaptive strategies that build resilience among both migrants and host communities in urban settings across these areas.<br/><br/>The project’s approach to tackle these challenges is using advanced tools like the Participatory Public Geographical Information System (PPGIS) to encourage a wide range of community members to: 1) express their preferences about, for example, where to promote new housing developments and where to place green infrastructure given the potential of more severe flooding in the future, and 2) how to communicate these preferences to city officials. This effort not only aims to reflect the real needs and aspirations of the communities involved but also to facilitate dialogue amongst local stakeholders to better understand the impacts of migration on their environments and economies. By comparing across several cities in the GLR and the LVB, the project will offer insights into how these tools can be scaled and adapted elsewhere, potentially transforming how cities worldwide approach the complexities of climate-driven migration and fostering more resilient and inclusive communities. This initiative will also facilitate the communication among cities of best practices to prepare, respond and adapt to climate migrants. This recognizes that the experiences of cities in the LVB are incredibly valuable for those in the GLR, which may soon face similar challenges due to climate migration. Simultaneously, this project will facilitate the sharing of strategies and insights from the Great Lakes cities, which have valuable experience in planning for and anticipating the complexities of these migration challenges.<br/><br/>This is a project jointly funded by the U.S. National Science Foundation and funding agencies from Canada, Germany, and the United Kingdom via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.079

1

4900

4900

2426552

[{'FirstName': 'Maria Carmen', 'LastName': 'Lemos', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria Carmen M Lemos', 'EmailAddress': 'lemos@umich.edu', 'NSF_ID': '000104036', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Derek', 'LastName': 'Van Berkel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Derek Van Berkel', 'EmailAddress': 'dbvanber@umich.edu', 'NSF_ID': '000827116', 'StartDate': '05/31/2024', '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': '481091041', 'StreetAddress': '440 Church St', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}

{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}

2024~614333

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426552.xml'}

Collaborative Research: Unlocking the evolutionary history of Schiedea (carnation family, Caryophyllaceae): rapid radiation of an endemic plant genus in the Hawaiian Islands

NSF

01/01/2024

07/31/2024

{'Value': 'Standard Grant'}

{'Code': '08010206', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}

{'SignBlockName': 'Carolyn J. Ferguson', 'PO_EMAI': 'cferguso@nsf.gov', 'PO_PHON': '7032922689'}

-------------------------------------------------------------------------------------------------------------------------------<br/>Plants exhibit a diverse array of breeding strategies, but the genetic changes and environmental conditions that lead to this diversity are poorly known. Pinpointing these genetic mutations and understanding the environmental conditions that favor changes in breeding system are of great interest to both evolutionary biologists and plant breeders. The plant genus Schiedea (carnation family, Caryophyllaceae) is only found on the Hawaiian Islands and is a model to better understand the evolution of breeding strategies in plants. Among the 32 species of Schiedea, some only breed with other individuals of the same species, others only self-fertilize, and others still are transitional between the two. Additionally, different outbreeding species of Schiedea use different pollinators, including a recently discovered moth found only in Hawaii. This project will apply cutting-edge DNA sequencing and analysis methods to reconstruct the genealogy of Scheidea and investigate the evolution of plant breeding strategies within the group. Data from this project will provide new insights into the evolution of plant breeding strategies that could be applied to crop species in the carnation family, including amaranth, rhubarb, quinoa and spinach. The project incorporates extensive opportunities for education and training at multiple levels, including high school teachers, undergraduate and graduate students, and a postdoctoral researcher. The project will produce educational videos about Hawaiian plants for posting on the internet to inform the public. Researchers will also offer public seminars about Schiedea highlighting their research findings about the group.<br/><br/><br/><br/>The primary aim of this project is to reconstruct the pattern of breeding system evolution in Schiedea (Caryophyllaceae) through an integrated program of field, laboratory, and genomic studies. Nuclear genome sequencing, targeted sequence capture, and Genotyping By Sequencing (GBS) methods will be used to reconstruct a highly resolved phylogenetic tree of Schiedea, identify sources of phylogenetic conflict, and investigate patterns of introgression among taxa. The phylogenetic hypotheses developed will be used to interpret the evolution of breeding systems including transitions from hermaphroditism to dioecy, shifts from biotic to abiotic pollination, and traits associated with pollination biology (including scent and nectar production). Field studies and densely distributed Single Nucleotide Polymorphisms (SNP) markers generated by GBS will be used to test hypotheses concerning the influence of reproductive systems on gene flow, hybridization, and population genetic structure. Data obtained during this project will be applied directly to land management in Hawaii, including the establishment of wild populations of different Schiedea species.<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.

04/05/2024

04/05/2024

None

Grant

47.074

1

4900

4900

2426560

{'FirstName': 'Norman', 'LastName': 'Wickett', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Norman Wickett', 'EmailAddress': 'nwicket@clemson.edu', 'NSF_ID': '000612498', 'StartDate': '04/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'ZipCode': '296340001', 'PhoneNumber': '8646562424', 'StreetAddress': '201 SIKES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'SC03', 'ORG_UEI_NUM': 'H2BMNX7DSKU8', 'ORG_LGL_BUS_NAME': 'CLEMSON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'StateCode': 'SC', 'ZipCode': '296340001', 'StreetAddress': '230 Kappa Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'SC03'}

[{'Code': '117100', 'Text': 'PHYLOGENETIC SYSTEMATICS'}, {'Code': '737400', 'Text': 'Systematics & Biodiversity Sci'}]

['2018~133687', '2022~96875']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426560.xml'}

Collaborative Research: Understanding the Turbulent Dynamics of Convective Bursts and Tropical Cyclone Intensification Using Large Eddy Simulations and High-Order Numerics

NSF

02/01/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '06020100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}

{'SignBlockName': 'Nicholas Anderson', 'PO_EMAI': 'nanderso@nsf.gov', 'PO_PHON': '7032924715'}

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Hurricane intensity changes are governed by a number of complex and competing processes that are difficult to simulate. This project will address one of the key uncertainties in hurricane intensity, the turbulent mixing of air and moisture in the inner core of a hurricane. In particular, the study will focus on convective bursts, which are roughly equivalent to large thunderstorms near the hurricane’s eyewall, and how they influence the intensification cycle. Rapid intensification changes have occurred in many recent high-impact storms and while forecasters know the general conditions that may lead to rapid intensification, the exact timing and magnitude of those changes are difficult to predict. This research will provide additional information to the scientific community which may result in improved numerical modeling of these storms. The project will also provide training and outreach opportunities to several students, thereby training the next generation of scientists.<br/><br/>The goal of the project is to understand the fundamental physics of tropical cyclone intensification with an emphasis on the role of turbulent dynamics. The researchers aim to 1) understand the turbulent nature of the convective burst cycle from formation to maturation and decay during intensification, and 2) identify the roles of axisymmetric and asymmetric dynamics in the intensification of tropical cyclones in a fully turbulent regime characterized by a wide range of energetic length scales with a minimally dissipative dynamic core. To address these aims, the researchers plan to conduct very high-resolution Large Eddy Simulations (LES) of tropical cyclones at 50m horizontal and vertical grid spacing using the newly developed ClimateMachine community model. The model output will be analyzed using diagnostic budget calculations for angular momentum, kinetic energy, and thermal energy equations in a Eulerian and Lagrangian reference from to enable improved physical insight.<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.

05/06/2024

05/17/2024

None

Grant

47.050

1

4900

4900

2426563

[{'FirstName': 'Charles', 'LastName': 'Eggleton', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charles D Eggleton', 'EmailAddress': 'eggleton@umbc.edu', 'NSF_ID': '000452224', 'StartDate': '05/06/2024', 'EndDate': '05/17/2024', 'RoleCode': 'Former Principal Investigator'}, {'FirstName': 'Stephen', 'LastName': 'Guimond', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephen R Guimond', 'EmailAddress': 'stephen.guimond@hamptonu.edu', 'NSF_ID': '000678093', 'StartDate': '05/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Hampton University', 'CityName': 'HAMPTON', 'ZipCode': '236694561', 'PhoneNumber': '7577275363', 'StreetAddress': '200 WILLIAM R HARVEY WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'VA03', 'ORG_UEI_NUM': 'KSJKE3KVNBB4', 'ORG_LGL_BUS_NAME': 'HAMPTON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Hampton University', 'CityName': 'HAMPTON', 'StateCode': 'VA', 'ZipCode': '236694561', 'StreetAddress': '200 WILLIAM R HARVEY WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'VA03'}

{'Code': '152500', 'Text': 'Physical & Dynamic Meteorology'}

['2021~189402', '2023~20000']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426563.xml'}

WORKSHOP: Doctoral Consortium at Interaction Design and Children (IDC) 2024

NSF

06/01/2024

05/31/2025

{'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': 'Ephraim Glinert', 'PO_EMAI': 'eglinert@nsf.gov', 'PO_PHON': '7032924341'}

This is funding to partially support participation by approximately 10 graduate students from United States institutions along with four distinguished faculty mentors, in a Doctoral Consortium (workshop) that will take place in conjunction with the 23rd Annual Interaction Design and Children conference (IDC 2024), which will be held June 17-20 in Delft, the Netherlands, and which is sponsored by the Association for Computing Machinery (ACM). IDC is the premier international conference for researchers, educators, and practitioners to share the latest research findings, innovative methodologies, and new technologies in the areas of inclusive child-centered design, learning, and interaction. The theme of this year's conference is "Inclusive Happiness." More information is available online at https://idc.acm.org/2024/. The IDC doctoral consortium is a forum where students and mentors create a safe space for constructive refinement of the research endeavors of the doctoral students within this important research area. Underrepresented groups and those from smaller schools or with smaller research programs will be given preference. Participants in the workshop create a network that strengthens the overall research community while at the same time advancing their own research through valuable interactions with peers and mentors with diverse perspectives. Additional broad impacts will derive from planting the seeds to a better understanding of how children interact with technology, the impact that technology has on children, and how to design, develop, evaluate, and improve technology for children. <br/><br/>The IDC doctoral consortium is a full-day event that will take place on Monday, June 17, the day before the main conference. Workshop participants will present their research questions, approach and agenda, and receive constructive yet critical feedback from faculty mentors and peers, which will enrich their research by enabling them to better articulate their focus and to refine their research methods and approach. Participants will also present a poster about their research during the main conference, in order to give them further opportunities to connect to a larger scholarly network. Abstracts of the students' doctoral work and progress will be included in the IDC conference proceedings, which are published in the Association for Computing Machinery (ACM) Digital Library.<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.

04/21/2024

04/21/2024

None

Grant

47.070

1

4900

4900

2426567

{'FirstName': 'Jerry', 'LastName': 'Fails', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jerry Fails', 'EmailAddress': 'jerryfails@boisestate.edu', 'NSF_ID': '000548573', 'StartDate': '04/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Boise State University', 'CityName': 'BOISE', 'ZipCode': '837250001', 'PhoneNumber': '2084261574', 'StreetAddress': '1910 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Idaho', 'StateCode': 'ID', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'ID02', 'ORG_UEI_NUM': 'HYWTVM5HNFM3', 'ORG_LGL_BUS_NAME': 'BOISE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'HYWTVM5HNFM3'}

{'Name': 'Boise State University', 'CityName': 'Boise', 'StateCode': 'ID', 'ZipCode': '837250001', 'StreetAddress': '1910 University Dr', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Idaho', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'ID02'}

{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}

2024~27036

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426567.xml'}

CAS: Understanding the Electrochemistry of Carboxylate Compound-Based Organic Anodes in Rechargeable Sodium and Potassium Batteries

NSF

06/01/2024

07/31/2025

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Tingyu Li', 'PO_EMAI': 'tli@nsf.gov', 'PO_PHON': '7032924949'}

In this project, funded by the Chemical Structure, Dynamics & Mechanisms B Program of the Chemistry Division, Professors Chao Luo and Andre Clayborne of the Department of Chemistry and Biochemistry at George Mason University are investigating the electrochemistry of carboxylate compounds in rechargeable sodium batteries and rechargeable potassium batteries. They are seeking a fundamental understanding of the correlation between chemical structures and electrochemical behaviors. Rechargeable sodium batteries and rechargeable potassium batteries are attractive alternatives to the well-known lithium ion battery, which are widely used in electric cars, electronic, and energy storage. Research activities will involve graduate, undergraduate, high school, and middle school students. Outreach activities include the development of sustainable battery workshops for high school and middle school students, and the training of high school students with basic hands-on skills for battery research to enhance their interests in science, technology, engineering, and mathematics. <br/><br/>Current inorganic anodes limit the development of rechargeable sodium batteries and rechargeable potassium batteries, because of low capacity, poor cycle life, and sluggish reaction kinetics. Carboxylate compounds, with their advantages of lightweight and low cost, stand out as promising anode materials for rechargeable sodium batteries and rechargeable potassium batteries. However, they can suffer from low Coulombic efficiency and slow reaction kinetics. Professors Chao Luo and Andre Clayborne plan to overcome these limitations by studying functional groups, heteroatoms, conjugation structure, structural isomerism, and interfacial chemistry in conjunction with computation chemistry and data analytics. Innovative structure design and facile fabrication approaches will be developed to synthesize carboxylate-based organic anodes. The combination of extensive electrochemical and material characterizations, in situ/ex situ electrode measurements, and computational chemistry could lead to the fundamental understanding of the battery chemistry of new carboxylate anodes.<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.

06/18/2024

06/18/2024

None

Grant

47.049

1

4900

4900

2426591

{'FirstName': 'Chao', 'LastName': 'Luo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chao Luo', 'EmailAddress': 'cxl1763@miami.edu', 'NSF_ID': '000811306', 'StartDate': '06/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'ZipCode': '331462919', 'PhoneNumber': '3052843924', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'FL27', 'ORG_UEI_NUM': 'RQMFJGDTQ5V3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MIAMI', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'StateCode': 'FL', 'ZipCode': '331462919', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'FL27'}

{'Code': '910200', 'Text': 'CMFP-Chem Mech Funct, and Prop'}

['2022~142593', '2023~206768']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426591.xml'}

RI: Small: Understanding Hand Interaction In The Jumble of Internet Videos

NSF

01/01/2024

09/30/2025

{'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': 'Jie Yang', 'PO_EMAI': 'jyang@nsf.gov', 'PO_PHON': '7032924768'}

Hands are the primary way that humans interact with and manipulate the world. Intelligent machines will need to be able to understand how humans use their hands if they are to understand human actions and to work in the world humans have built with their hands. Unfortunately, videos that show people using their hands are surprisingly difficult to understand for current artificial intelligence (AI) systems. Hands may be temporarily hidden as people interact with objects, and even if they are visible, hands can interact with a myriad of different objects ranging from refrigerator handles to coffee mugs to garage door openers. This project develops systems that can enable learning about how humans use their hands from large scale Internet video data. As hands are central to many other areas of study, this project has the potential to empower research in many other disciplines. For instance, robotics researchers may use the systems to teach robots how to interact with objects by observation. Similarly, kinesiologists and mechanical engineers who study how the human hand is used could use the systems to better quantify hand motions and thus improve the lives of people. <br/><br/>This project aims to achieve its goal via three technical directions that together advance the science of understanding human activities and affordances (human/object interaction). The first direction of the project will build systems for automatically parsing hand interaction data from large-scale video. The goal of this direction is to understand what the hand is doing in terms of interaction with the world in physical terms as opposed to via naming the interaction with nouns and verbs. To help understand the context of an interaction, the second direction aims to build learning-based systems that can understand human poses from partial observations that occur naturally in video data. Finally, the third direction puts these systems together by building a graph of interaction where hand interaction examples are nodes, and edges are induced by observations of human pose. This web of interactions will enable systems to learn about how humans can manipulate objects from large-scale data across viewpoints and examples and enable new applications of computer vision.<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.

04/11/2024

04/11/2024

None

Grant

47.070

1

4900

4900

2426592

{'FirstName': 'David', 'LastName': 'Fouhey', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David F Fouhey', 'EmailAddress': 'fouhey@umich.edu', 'NSF_ID': '000807235', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'ZipCode': '100121019', 'PhoneNumber': '2129982121', 'StreetAddress': '70 WASHINGTON SQ S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'NX9PXMKW5KW8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100121019', 'StreetAddress': '70 WASHINGTON SQ S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

{'Code': '749500', 'Text': 'Robust Intelligence'}

2020~178880

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426592.xml'}

Conference: SSMC Workshop on Assemblies of Nanomaterials

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}

{'SignBlockName': 'Robert Meulenberg', 'PO_EMAI': 'rmeulenb@nsf.gov', 'PO_PHON': '7032927106'}

NON-TECHNICAL SUMMARY<br/><br/>For a century the atom has been the building block of chemistry and materials science. However, with the advancement of nanoscience, it may become possible to generalize the concept of the building blocks for designing novel functional materials. Nanometer sized components with precisely engineered sizes, shapes, compositions, and concomitant properties can be used as “meta-atoms” for building unprecedented materials. Just as atoms combine to form molecules or crystals with dramatically different properties than the atomic constituents, the assemblies of nanomaterials can lead to new objects whose properties are determined by the interplay of the properties of individual building blocks and the interactions between these building blocks. In contrast to true atoms, nanomaterials can be continuously varied and changed in ways that traditional atoms in the periodic table cannot. This workshop, co-organized by Dmitri Talapin (University of Chicago), Richard Robinson (Cornell University) and Kristie Koski (University of California Davis) with support by the Solid State and Materials Chemistry program within the Division of Materials Research, is designed to facilitate an exchange among both emerging and established scientists working on nanomaterial assemblies. A series of presentations and roundtable discussions across six focus areas will launch discussions among experts from various niches within materials chemistry to advance the field of nanomaterial assemblies. This event will tackle key questions that lie at the heart of basic nanomaterial assembly science. The workshop engages diverse groups of researchers to ensure a rich mix of backgrounds, regions, and scientific expertise among the discussion leaders and participants. Expected from the workshop are enhanced methodologies for the controlled creation, analysis, and understanding of nanomaterial assemblies and their future applications, alongside bolstered interactions within this cross-disciplinary field.<br/><br/>TECHNICAL SUMMARY<br/><br/>The workshop on Assemblies of Nanomaterials will identify challenges and opportunities in the fundamental science of nanomaterial assemblies, including mesocrystals, hybrid materials, 2D material assemblies, and multi-component nanomaterials. It will also help establish a roadmap to (i) identify new tools and approaches in nanomaterials and assemblies, (ii) set standards for data and reproducibility with an outlook on AI integration, (iii) address how we can bring communities together across the multidisciplinary field of 0D, 1D, and 2D nanomaterial assemblies. The mission of the workshop is to understand the community views on current research frontiers, and to identify gaps and new focus areas. The workshop will advance knowledge and understanding of collective properties in nanomaterial assemblies, as well as discuss best practices and methodologies for probing the structural, morphological, and chemical properties at the nanoscale. The workshop will devise a community-driven roadmap for instrumentation, infrastructure, guidelines for future interfaces with AI, and reproducibly in data and software. By setting standards for data and reproducibility, the workshop will contribute to the development of more efficient research methodologies. This will have far-reaching implications for the ability to translate the success of applied materials into various sectors, including electronics, healthcare, and energy, where nanomaterials are increasingly being employed. <br/><br/>The workshop aims to bring together communities from different disciplines, fostering interdisciplinary collaboration that is essential for tackling complex scientific challenges. The creation of a collaborative environment will not only accelerate the pace of discovery but also facilitate the training and mentorship of the next generation of scientists and engineers. This will help align research efforts with societal needs and ensure that the advancements in nanomaterial assemblies contribute positively toward economic development, environmental sustainability, and public health.<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.

04/24/2024

04/24/2024

None

Grant

47.049

1

4900

4900

2426604

{'FirstName': 'Dmitri', 'LastName': 'Talapin', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dmitri V Talapin', 'EmailAddress': 'dvtalapin@uchicago.edu', 'NSF_ID': '000509301', 'StartDate': '04/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606375418', 'PhoneNumber': '7737028669', 'StreetAddress': '5801 S ELLIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'ZUE9HKT2CLC9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': 'ZUE9HKT2CLC9'}

{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606375418', 'StreetAddress': '5801 S ELLIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}

{'Code': '176200', 'Text': 'SOLID STATE & MATERIALS CHEMIS'}

2024~73500

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426604.xml'}

CAREER: Machine Learning for Data-Driven Fault-Tolerant Control of Complex Systems

NSF

11/01/2023

08/31/2027

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Yue Wang', 'PO_EMAI': 'yuewang@nsf.gov', 'PO_PHON': '7032924588'}

This Faculty Early Career Development (CAREER) project will create new knowledge about the dynamic behavior and control of complex systems; specifically, how to predict rare deleterious events in complex systems, and how to control these systems when faults occur to achieve a desired performance. Complex systems are networks comprising many collaborating elements that continuously interact with each other in a nonlinear and counterintuitive manner; examples include cybersecurity, manufacturing processes, automated transportation infrastructure, medical devices, and many others relevant to our well-being. Faults in these systems are malfunctions, such as cyber-attack or sensor failure, that break security, degrade system functionality, and cause safety concerns and economic losses. Control of these systems is challenging because the dynamic behavior of the ensemble is intrinsically difficult to predict. This award supports fundamental research to build a “fault-aware” control framework to study how interactions among individual elements produce the collective’s dynamics and how to alleviate the effect of faults on complex systems. To develop and test the control framework, a failing heart managed by a ventricular assist device will be used as the foundation to (i) detect device faults such as thrombosis and suction that jeopardize the survival of heart failure patients and (ii) automatically adjust the operation of the device under faults to improve the patient quality of life. The educational and outreach plan will focus on promoting active and life-long learning and engaging and training students at various levels, including veterans transitioning to civilian life, in emerging industries and transdisciplinary skills.<br/><br/>Using machine learning as the backbone, the objective of this research is to create a data-driven control strategy that regulates and maintains the system’s homeostasis following the onset of faults, while ensuring the system continues to operate in a seamless, continuous manner. This research will fill the knowledge gap for the supervision and control of complex systems when the governing phenomena are unknown and when first principle models are not readily attainable. The data-driven strategy will also overcome design limitations. Designing complex systems, such as ventricular assist devices, based on first principle models is costly, time consuming, and requires extensive expert knowledge to build application-specific models based on ubiquitous assumptions that are difficult to satisfy in practice. This research project will integrate data analytics, control theory, and machine learning into a unified framework with three innovative aspects: developing machine learning methods to discover symptomatic fingerprints of faults directly from data for real-time fault diagnosis; building an online adaptive modeling paradigm to predict performance-related variables that are not directly measurable due to economic considerations or technical constraints; designing a fault-tolerant controller to improve the system’s performance, while ensuring all operational constraints are met. In addition to its application to ventricular assist devices, this framework can be applied to protect computer systems from digital attacks, improve manufacturing efficiency, and address safety issues in automated transportation infrastructure and medical devices, leading to compelling societal and economic benefits.<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.

04/03/2024

04/03/2024

None

Grant

47.041

1

4900

4900

2426614

{'FirstName': 'Yuncheng', 'LastName': 'Du', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yuncheng Du', 'EmailAddress': 'ydu@clarkson.edu', 'NSF_ID': '000736196', 'StartDate': '04/03/2024', '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': '104500', 'Text': 'CAREER: FACULTY EARLY CAR DEV'}, {'Code': '756900', 'Text': 'Dynamics, Control and System D'}]

2022~580453

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426614.xml'}

NSF-NFRF: Climate Collaboratorium: Co-creation of Decision Labs for Exploring Climate Change Adaptation and Mitigation

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

This project addresses risks to water security in vulnerable communities and how that risk intersects with risks associated with critical physical infrastructure, networks and services, and risks to living standards. Aging water infrastructure like dams, reservoirs, tidal protection, canals, and natural flood abatement are affecting livelihoods and water security in the study regions in the U.S., Canada, Germany, and the U.K. This partnership examines shared issues affecting water security and livelihoods of vulnerable people living in those four watersheds. More specifically, the project will demonstrate the novelty of applied theater decision labs to engage individuals and communities and impact better decision making on vital issues of water security and climate change. This innovative approach engages impacted populations in design thinking through applied theater to help translate climate science into the public policies and individual actions necessary to make change. <br/><br/>For those taking part in this applied theater decision lab – including Indigenous people, those from vulnerable communities impacted by flooding or people seeing their cultural heritage literally being washed out to sea - they will have the opportunity for their voices and stories to be heard. Equally important, this project will also hear the voices that lead to inertia or seek to slow or even stop needed climate change action. The impact of this project will be the use of design thinking as part of the inter-active performance as a tool for the audience to work together to address the issues raised in this play, practicing design thinking as they pursue actionable change in their real-life community. <br/><br/>This is a project jointly funded by the U.S. National Science Foundation and funding agencies from Canada, Germany, and the United Kingdom via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.079

1

4900

4900

2426627

[{'FirstName': 'David', 'LastName': 'Kaye', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David J Kaye', 'EmailAddress': 'david.kaye@unh.edu', 'NSF_ID': '0000A016M', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dan', 'LastName': 'Kleinmann', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dan A Kleinmann', 'EmailAddress': 'dan.kleinmann@unh.edu', 'NSF_ID': '0000A01H1', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of New Hampshire', 'CityName': 'DURHAM', 'ZipCode': '038242620', 'PhoneNumber': '6038622172', 'StreetAddress': '51 COLLEGE RD', 'StreetAddress2': 'BLDG 107', 'CountryName': 'United States', 'StateName': 'New Hampshire', 'StateCode': 'NH', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NH01', 'ORG_UEI_NUM': 'GBNGC495XA67', 'ORG_LGL_BUS_NAME': 'UNIVERSITY SYSTEM OF NEW HAMPSHIRE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of New Hampshire', 'CityName': 'DURHAM', 'StateCode': 'NH', 'ZipCode': '038242620', 'StreetAddress': '51 COLLEGE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Hampshire', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NH01'}

{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}

2024~294103

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426627.xml'}

Chirality-Driven Self-Assembly of Dual Catalytic Dendrimers: Application Toward One-Pot Tandem Reactions

NSF

01/01/2024

07/31/2024

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Kenneth Moloy', 'PO_EMAI': 'kmoloy@nsf.gov', 'PO_PHON': '7032928441'}

In living cells many simultaneous chemical transformations occur with no interference between the enzymes that catalyze them. To accomplish this Nature has evolved to incorporate catalyst sites within enzyme pockets or by physical separation using membranes. The successful construction of artificial analogues of such frameworks would reduce catalyst deactivation and eliminate undesirable side reactions. These are important goals in catalysis with many potential practical applications. With funding from the Chemical Catalysis Program of the Chemistry Division, Dr. Moteki of the University of Missouri Kansas City is developing synthetic materials possessing multiple types of incompatible catalyst sites where the sites are spatially isolated. Together with Dr. Palencia of the University of Nebraska Kearney, the catalytic efficiency and reaction scope of these catalysts are being tested. Drs. Moteki and Palencia are actively recruiting students from local high schools and community colleges, targeting underrepresented minority students, and providing them with early research experience. The research experience will increasing retention, and enhancement of underserved populations in STEM field. Summer workshops for community and small college faculty are also being conducted. Such efforts are crucial in forming new generations of young research scientists.<br/><br/>Tandem-catalyzed reactions have been widely recognized as one of the most efficient atom economical and environmentally friendly processes, due to minimization of waste generation. In particular, orthogonal tandem catalysis, which features two or more distinct catalysts with differing mechanisms, offers potential for higher process efficiency. Over the past few decades only a handful of successful examples have been reported primarily due to the difficulty in creating compartmented macro-structures that spatially separate incompatible catalysts. This proposal aims at building a multi-component catalytic dendrimer complex via chiral self-discrimination, which enables the in situ quantitative assembly of various multi-domain dendrimers through metal-chiral ligand interactions. This allows tuning of the microenvironment far easier than conventional covalently assembled systems, making it a more attractive system for reaction screening targeting various multi-step tandem chemical transformations. Our research team aims to understand the underlying catalyst structure-function relationship of the dual catalytic dendrimer by varying polarity as well as architectural design of each catalytic domains. In addition, the efficiency and versatility of dual catalytic dendrimers will be investigated, by using three different types of tandem reactions as models; i) substrate-selective tandem catalysis, ii) tandem reaction involving a catalytically reversible step, and iii) tandem reaction involving competitive catalytic pathways. The operational simplicity in reaction screening and the dendron preparation synthetic steps is ideal for training the next generation of synthetic chemists. Dr. Moteki and Dr. Palencia are actively engaged in outreach activity, they will host an annual workshop as means of recruiting of underserved minority students from local high schools and community colleges for summer research internship in their research groups.<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.

04/11/2024

04/11/2024

None

Grant

47.049

1

4900

4900

2426644

{'FirstName': 'shin', 'LastName': 'moteki', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'shin moteki', 'EmailAddress': 'motekis@umkc.edu', 'NSF_ID': '000758555', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Marshall University Research Corporation', 'CityName': 'HUNTINGTON', 'ZipCode': '257550002', 'PhoneNumber': '3046964837', 'StreetAddress': '1 JOHN MARSHALL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'West Virginia', 'StateCode': 'WV', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'WV01', 'ORG_UEI_NUM': 'HH1NQ1B5MPV3', 'ORG_LGL_BUS_NAME': 'MARSHALL UNIVERSITY RESEARCH CORPORATION', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Marshall University Research Corporation', 'CityName': 'HUNTINGTON', 'StateCode': 'WV', 'ZipCode': '257550002', 'StreetAddress': '1 JOHN MARSHALL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'West Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'WV01'}

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

2019~68412

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426644.xml'}

SaTC: CORE: Medium: Collaborative: Doctor WHO: Investigation and Prevention of Online Content Management System Abuse

NSF

10/01/2023

09/30/2024

{'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': 'Sol Greenspan', 'PO_EMAI': 'sgreensp@nsf.gov', 'PO_PHON': '7032927841'}

Over half of the world's 1.8 billion websites run on Content Management Systems (CMS). Unfortunately, CMS deployments make easy targets for attackers, as they are built from an amalgam of layered software and interpreters, with varying degrees of network and system permissions, which execute on an Internet-facing web server. This project develops program-analysis-centric techniques that enable the investigation and remediation of ongoing infections as well as hardening against future CMS compromises, with the goals of 1) understanding the intent and strategy of a CMS infection and tracing their root-cause attack vector for reliable remediation, 2) revealing dynamic and sophisticated attack behaviors in malware samples in a CMS infection, 3) hardening of CMS deployments against future attacks. This project benefits national security and economic stability by creating cyber forensics and vulnerability detection techniques for CMS websites and the financial, government, and private sector operations they support. It provides server-side script code including malicious scripts and vulnerable code to help train next-generation cybersecurity experts. Students from underrepresented minority groups are involved in research activities.<br/><br/>This project develops Doctor WHO, a CMS analysis framework which combines rapid evidence collection and advanced program analysis techniques for the investigation and remediation of infections and hardening against future CMS compromises. Specifically, the data-driven prediction framework, called TARDIS, is developed to understand the temporal correlation of attack evidence across a corpus of real-world websites. TARDIS enables the automated discovery of the artifacts of a compromise, fingerprinting of the attack's propagation, and rapid investigation of cyberattacks against CMS deployments. The project also develops Torchwood, a cross-language and cross-environment program analysis framework to effectively analyze highly dynamic and sophisticated malware targeting CMSs. Torchwood can handle advanced obfuscation and anti-analysis techniques applied to malware and reveal hidden malicious behaviors and intentions of the malware effectively. Lastly, the project develops UNIT that enables the hardening and securing of CMS deployments against future attacks. UNIT accomplishes this by enabling automated dynamic testing of CMS-backed websites without requiring any runtime environment resources. UNIT eliminates false alerts and provide proof-of-concept exploits via a set of new methods to identify and model dependencies of runtime resources and reconstruct missing resources using instrumented script interpreter engines.<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.

04/12/2024

04/12/2024

None

Grant

47.070

1

4900

4900

2426653

{'FirstName': 'Yonghwi', 'LastName': 'Kwon', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yonghwi Kwon', 'EmailAddress': 'yongkwon@umd.edu', 'NSF_ID': '000784902', 'StartDate': '04/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}

{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}

2019~230491

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426653.xml'}

NSF-NFRF: Building resilience of coastal inhabitants in vulnerable regions of Bangladesh through a participatory, gender-transformative approach

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

Bangladesh places seventh on the global Climate Risk Index and the country’s coastal areas are particularly vulnerable to the changing climate. Women, members of Indigenous communities, and people with disabilities in particular face high risks and vulnerabilities due to their lack of adaptive capacity, resources, and skills. The research takes a novel approach to evidence generation within the field of climate change adaptation and mitigation by utilizing a gender-transformative and participatory approach to identify risks and create transformational mitigation/adaptation strategies for climate change risks. In the past, approaches for addressing climate change and its risk and vulnerability assessment focused mainly on the scientific and technical aspects of the problems while ignoring social, institutional, and gender issues. This research project overcomes this gap and promotes the progress of science by prioritizing partnerships with local vulnerable communities to co-create knowledge and communication strategies, and to plan and implement objectives that are devised and owned by communities and local governments to build climate change resilience. The broader scientific impact of the research is anticipated to be a demonstration that groups that are most at risk of the negative impacts of climate change are in a unique position to lead adaptation and mitigation efforts – which both can decrease their risk of experiencing negative consequences from climate change as well as can help empower them to provide ongoing leadership on this complex and ever-evolving issue within their own communities.<br/><br/>The objective of the research is to reduce risks associated with climate change affecting vulnerable coastal communities in the Cox’s Bazar and Chittagong regions of Bangladesh, while contributing to gender transformative change. This will be achieved in three phases. First, working together with community-based women, representatives of Indigenous populations and persons with disabilities who reside in highly climate insecure communities in coastal areas of Bangladesh, the research team and a women-led, community-based organization will use innovative and participatory visual and arts-based methodologies, such as storytelling, photovoice, incomplete stories, mapping and drawing, to collaboratively identify risks that these groups encounter due to climate change. In phase 2, the research team will support community representatives to analyze data collected in phase 1 and to create feasible, locally-led, community-based action plans that can be piloted in their own communities to adapt to / mitigate the impacts of climate change. In phase 3, the research will focus on analyzing the data collected throughout the implementation of the locally-developed community-action plans, synthesizing learning, and developing dissemination products.<br/><br/>This is a project jointly funded by the U.S. National Science Foundation and the National Endowment for the Humanities, as well as funding agencies from Canada via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.079

1

4900

4900

2426669

{'FirstName': 'Maureen', 'LastName': 'Murphy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maureen Murphy', 'EmailAddress': 'maureenmurphy@gwu.edu', 'NSF_ID': '0000A01ZR', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'George Washington University', 'CityName': 'WASHINGTON', 'ZipCode': '200520042', 'PhoneNumber': '2029940728', 'StreetAddress': '1918 F ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'ECR5E2LU5BL6', 'ORG_LGL_BUS_NAME': 'GEORGE WASHINGTON UNIVERSITY (THE)', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'George Washington University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200520042', 'StreetAddress': '1922 F St., NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}

2024~524987

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426669.xml'}

I-Corps: Translation Potential of a Wearable Ankle Rehabilitation Device

NSF

07/01/2024

12/31/2024

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': 'rshuman@nsf.gov', 'PO_PHON': '7032922160'}

The broader impact of this I-Corps project is the development of a smart, wearable, ankle rehabilitation system to improve mobility. Currently, most patients do not receive adequate physical therapy treatment for walking disabilities caused by conditions such as stroke, cerebral palsy, Parkinson's disease, and sarcopenia (ageing). Also, care givers and therapists do not have the tools and time needed to target improved neuromuscular control of the ankle plantar flexor muscles during gait training. This technology addresses this shortfall by providing a wearable platform that can be used daily at home for personalized precision resistance therapy. In addition, this system allows individuals to train within the functional context of walking, thereby achieving repetitive, high-volume practice. The technology may transform the treatment of gait disorders, improve physical and mental health, and lessen the financial burden of individuals with neuromuscular impairments and age-related disabilities.<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 a wearable rehabilitation system for individuals with impaired mobility due to a walking disability. The robotic system pairs targeted ankle resistance with a gamified ankle power biofeedback and may provide improvements in neuromuscular function and mobility. Applying adaptive resistance to the plantar flexion is immediately responsive to user input and fosters active engagement. In pilot studies, the device has been shown to work better than the current standard of care for delivering high-quality gait training. The solution matches the performance of high-tech motorized robotic exoskeletons. In addition, the absence of motors and heavy batteries may facilitate adoption by making it easier to use by individuals with weakness and those that historically do not adopt motorized solutions (e.g., older adults). This technology may create a foundation to treat neuromuscular impairment across a wide range of conditions.<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.

06/25/2024

06/25/2024

None

Grant

47.084

1

4900

4900

2426671

{'FirstName': 'Zachary', 'LastName': 'Lerner', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zachary F Lerner', 'EmailAddress': 'Zachary.Lerner@nau.edu', 'NSF_ID': '000754987', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Northern Arizona University', 'CityName': 'FLAGSTAFF', 'ZipCode': '86011', 'PhoneNumber': '9285230886', 'StreetAddress': '601 S KNOLES DR RM 220', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'AZ02', 'ORG_UEI_NUM': 'MXHAS3AKPRN1', 'ORG_LGL_BUS_NAME': 'NORTHERN ARIZONA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northern Arizona University', 'CityName': 'FLAGSTAFF', 'StateCode': 'AZ', 'ZipCode': '86011', 'StreetAddress': '601 S KNOLES DR RM 220', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'AZ02'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426671.xml'}

Conference: 27th International Congress on Plant Reproduction

NSF

06/01/2024

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Kan Wang', 'PO_EMAI': 'kawang@nsf.gov', 'PO_PHON': '7032924591'}

This award from the National Science Foundation will be used to enable early career scientists to attend the 27th International Congress on Plant Reproduction. This is an important professional development opportunity that will help to build research capacity and expertise in an area that is critical for crop productivity. The 27th International Congress on Plant Reproduction will be held in Providence, RI from July 7-10, 2024. This is the premier international conference dedicated to reporting advances in our understanding of how plant reproduction works at the cellular and molecular level. This field is particularly important for advancing crop productivity because reproduction is central to production of crops like corn, wheat, and rice. In addition, research in this field has led to advances in breeding technology, which benefit all crops. The conference will be highly interactive and will facilitate formal scientific discussion via oral presentations to the entire group and poster presentations to smaller groups. <br/><br/>The conference will attract ~200 scientists from around the world, with most participants coming from North America, Europe, and Asia. The conference will feature an eminent group of speakers representing multiple nations and multiple career stages and expertise. They will present their findings in major areas of research in molecular plant reproduction, ensuring a comprehensive and insightful program. Plant reproduction is sensitive to temperature and other stresses and is directly required for production of key agricultural products like maize kernels, rice and wheat grains, and tomato fruits. As we face the challenge of feeding a growing population in a changing climate, we must build a diverse and inclusive research community that is dedicated to working in this critical field. Travel awards will be granted to researchers at United States institutions who would otherwise be less likely to attend, including participants from predominantly undergraduate and minority-serving institutions.<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.

05/03/2024

05/03/2024

None

Grant

47.074

1

4900

4900

2426683

{'FirstName': 'Mark', 'LastName': 'Johnson', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mark A Johnson', 'EmailAddress': 'mark_johnson_1@brown.edu', 'NSF_ID': '000219217', 'StartDate': '05/03/2024', 'EndDate': None, 'RoleCode': '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': None}

{'Name': 'Brown University', 'CityName': 'Providence', 'StateCode': 'RI', 'ZipCode': '029129002', 'StreetAddress': '350 Eddy Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'RI01'}

{'Code': '132900', 'Text': 'Plant Genome Research Project'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426683.xml'}

Travel: NSF Student Travel Support for 2024 ACM International Conference on Information and Management (CIKM)

NSF

05/01/2024

04/30/2025

{'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': 'Sylvia Spengler', 'PO_EMAI': 'sspengle@nsf.gov', 'PO_PHON': '7032927347'}

This proposal aims to provide travel grants that facilitate the attendance of students from United States universities at the 2024 international Conference on Information and Management ( ACM CIKM), in Boise, Idaho. The CIKM conference is recognized as a premier gathering within the fields of databases, data mining, artificial intelligence and information retrieval. It will feature a curated selection of top-tier technical papers, attracting a diverse international audience. The tentative five-day schedule for CIKM 2024 includes: Tutorials and Industry Day on Monday, Main conference from Tuesday to Thursday, and Workshop and PhD Symposium on Friday. To enhance research findings dissemination, conference proceedings will be published in the Association for Computing Machinery (ACM) Digital Library.<br/><br/>The CIKM agenda boasts an array of noteworthy events, including keynote presentations, paper technical presentations, an industry-focused day with technical talks, tutorials, workshops, and a PhD symposium. The travel awards will cultivate the next generation of scholars and professionals, steering them toward understanding the fundamental scientific principles crucial for developing large-scale information and knowledge management systems with enhanced effectiveness. Furthermore, through fostering collaboration between students and senior researchers from academia and industry worldwide, this initiative holds the promise of substantial intellectual rewards for both the field and the participating 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.

04/21/2024

04/21/2024

None

Grant

47.070

1

4900

4900

2426708

[{'FirstName': 'Edoardo', 'LastName': 'Serra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edoardo Serra', 'EmailAddress': 'edoardoserra@boisestate.edu', 'NSF_ID': '000716889', 'StartDate': '04/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Francesca', 'LastName': 'Spezzano', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Francesca Spezzano', 'EmailAddress': 'francescaspezzano@boisestate.edu', 'NSF_ID': '000716890', 'StartDate': '04/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Boise State University', 'CityName': 'BOISE', 'ZipCode': '837250001', 'PhoneNumber': '2084261574', 'StreetAddress': '1910 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Idaho', 'StateCode': 'ID', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'ID02', 'ORG_UEI_NUM': 'HYWTVM5HNFM3', 'ORG_LGL_BUS_NAME': 'BOISE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'HYWTVM5HNFM3'}

{'Name': 'Boise State University', 'CityName': 'BOISE', 'StateCode': 'ID', 'ZipCode': '837250001', 'StreetAddress': '1910 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Idaho', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'ID02'}

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

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426708.xml'}

EDGE FGT: Genome-editing tools for keystone freshwater heterotrophs

NSF

12/15/2023

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Theodore Morgan', 'PO_EMAI': 'tmorgan@nsf.gov', 'PO_PHON': '7032927868'}

Microbial activity drives carbon emission and burial in freshwater environments, which cover only 4% of Earth's surface but both emit and store disproportionally large amounts of carbon. Up to 60% of the bacteria in fresh waters belong to a specific group of Actinobacteria, and this group likely controls conversion of organic matter to CO2 and buried biomass in these ecosystems. Although these bacteria have fewer than 2000 genes, they thrive in bogs, algae-choked lakes, pristine alpine ponds, rivers, estuaries, and reservoirs. To understand how bacteria with so few genes are able to dominate in such a diverse range of environments, we propose to develop genome-editing tools in two easy-to-work-with species of freshwater Actinobacteria. The work proposed here, and the research that builds on it, will enable scientists working on freshwater carbon cycling, bacterial-algal interactions, heterotrophy, and light capture to identify the genes in freshwater Actinobacteria that contribute to these processes. That work, in turn, will provide experimental data linking genes to ecosystem functions. <br/><br/>Laboratory research on the physiology and metabolism of freshwater clades of Actinobacteria has been hampered by having only a few cultivated species, none with available genome editing tools. To understand how such an apparently homogeneous group of bacteria contributes to nutrient cycling in such a diverse range of ecological settings, we propose to develop systems for targeted and random mutagenesis in Rhodoluna lacicola and Aurantimicrobium sp. strain MWH-Mo1, two easily cultivated, representative species of freshwater Actinobacteria. Targeted mutagenesis will enable not just inactivation of specific genes, but also insertion of genes for heterologous expression from the chromosome. Random transposon-based mutagenesis will enable construction of comprehensive mutant libraries that can be screened for fitness under a variety of different environmentally relevant stresses. These tools will catalyze research that connects simple genomes to complex phenotypes, phenotypes to biochemical networks in microbial communities, and microbial community metabolism to ecosystem carbon budgets.<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.

04/05/2024

04/05/2024

None

Grant

47.074

1

4900

4900

2426717

{'FirstName': 'Julia', 'LastName': 'Maresca', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Julia A Maresca', 'EmailAddress': 'jamaresc@esf.edu', 'NSF_ID': '000589310', 'StartDate': '04/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY College of Environmental Science and Forestry', 'CityName': 'SYRACUSE', 'ZipCode': '132102712', 'PhoneNumber': '3154706606', 'StreetAddress': '1 FORESTRY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_ORG': 'NY22', 'ORG_UEI_NUM': 'LVVEB3CF8MB8', 'ORG_LGL_BUS_NAME': 'THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'SUNY College of Environmental Science and Forestry', 'CityName': 'SYRACUSE', 'StateCode': 'NY', 'ZipCode': '132102712', 'StreetAddress': '1 FORESTRY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_PERF': 'NY22'}

{'Code': '137Y00', 'Text': 'EDGE Tools'}

2021~175658

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426717.xml'}

I-Corps: Translation Potential of a Remote Sensing-Based Measurement, Reporting, and Verification Tool for Sustainable Agriculture

NSF

05/15/2024

04/30/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': 'rshuman@nsf.gov', 'PO_PHON': '7032922160'}

The broader impact of this I-Corps project is the development of a technology to monitor agricultural practices and help farmers enhance agricultural productivity. Currently, more than 120 million acres of land in the U.S. corn belt is under agriculture production. This technology may be used to validate sustainable land management practices such as cover cropping and tillage at a field-scale level. The goal is to facilitate widespread adoption of sustainable land management practices, driving positive environmental impact, and fostering a more resilient and sustainable agricultural industry. Sustainable agriculture stewards the resources farms rely on, including enhanced nitrogen use efficiency, reduced greenhouse gas emissions, improved water quality, improved soil health, and maximized farmer profitability. The technology bridges a critical gap within the industry - delivering farm-specific data that empowers businesses to make more informed decisions, fosters responsible practices, and ultimately enhances the sustainability of agriculture. In addition, the technology addresses the demand for data-driven solutions and enhances environmental transparency in the agricultural supply chain without disclosing farmer data.<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 measurement, reporting, and verification tool (MRV) that addresses the challenges associated with monitoring and verifying management practices in agriculture. This technology harnesses the power of geospatial analytics and machine learning algorithms to create a method for collecting, analyzing, and validating data on agricultural practices. In addition, the platform integrates diverse data sources, including satellite imagery and field data, which allows the generation of comprehensive and precise assessments of land management practices and support carbon accounting. This multi-dimensional approach may enhance the reliability and depth of the information provided to stakeholders, enabling informed decision-making and strategic planning. Machine learning algorithms and cloud-based computing techniques also are used to detect patterns, trends, and anomalies in climate smart practices. The algorithms enable decision-makers to access more precise and timely insights, facilitating proactive measures to address emerging challenges and opportunities. Both public and private sector organizations may use the technology to track landscapes, identify areas for improvement, and pinpoint potential prospects for future conservation and restoration actions remotely and efficiently. By facilitating data-driven decision-making, the technology may empower stakeholders to enhance sustainability practices and achieve environmental conservation goals effectively.<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.

05/13/2024

05/13/2024

None

Grant

47.084

1

4900

4900

2426722

{'FirstName': 'Ranjeet', 'LastName': 'John', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ranjeet John', 'EmailAddress': 'Ranjeet.John@usd.edu', 'NSF_ID': '000628615', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of South Dakota Main Campus', 'CityName': 'VERMILLION', 'ZipCode': '570692307', 'PhoneNumber': '6056775370', 'StreetAddress': '414 E CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Dakota', 'StateCode': 'SD', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'SD00', 'ORG_UEI_NUM': 'U9EDNSCHTBE7', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF SOUTH DAKOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of South Dakota Main Campus', 'CityName': 'VERMILLION', 'StateCode': 'SD', 'ZipCode': '570692307', 'StreetAddress': '414 E CLARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Dakota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'SD00'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426722.xml'}

Collaborative Research: RUI: IRES Track I: From fundamental to applied soft matter: research experiences in Mexico

NSF

04/01/2024

07/31/2026

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Maija Kukla', 'PO_EMAI': 'mkukla@nsf.gov', 'PO_PHON': '7032924940'}

We encounter soft materials frequently in our everyday lives from ointments and lotions to paints and inks. Understanding these soft materials, which often possess both fluid-like and solid-like properties, and how they flow or deform is necessary for advancing many technologies, including 3D printing where the properties of the ink or resin must be finely tuned. To make progress on our scientific understanding of soft materials, this IRES Track I project will strengthen collaborations between researchers in Southern California and in Mexico. Each year over the 3-year duration of this project, 6 students will be recruited to take part in this international research experience. U.S. students from historically underrepresented groups and from predominantly undergraduate colleges and community colleges will be targeted in the recruitment effort. Those students will conduct research over the summer at either the Center for Research in Advanced Materials (Centro de Investigación en Materiales Avanzados, CIMAV) in Monterrey, Mexico or the University of Guanajuato in León, Mexico. Working with research mentors in Mexico and the mentors in Southern California, students will take various approaches to study the physics and chemistry of soft materials. Such approaches include using computer simulations to study fundamental aspects of soft materials and using 3D printers to apply our scientific understanding of soft materials to the design and use of new inks and resins. Students taking part in this research and receiving mentorship from U.S. and Mexican scientists will be prepared to cooperate with diverse teams across borders and to become leaders of a globally engaged scientific workforce. &lt;br/&gt;&lt;br/&gt;This IRES project will strengthen collaborations between researchers in the U.S. and Mexico by supporting the participation of 6 undergraduates per year in mentored summer research experiences. The PIs at the University of San Diego and California State University Fullerton will recruit undergraduate students from historically underrepresented groups and from predominantly undergraduate institutions and community colleges. After receiving training on basic research skills, selected students will spend approximately 8 weeks at either the Center for Research in Advanced Materials (Centro de Investigación en Materiales Avanzados, CIMAV) in Monterrey, Mexico or the University of Guanajuato in León, Mexico. Research projects undertaken by students will advance our understanding of soft matter, particularly in the areas of colloid science and rheology. Projects will include investigating the rheology of nanocellulose and cellulose composites for use in 3D printing applications, quantifying the translational and rotational diffusion of anisotropic colloids to better understand transport and microrheology in complex environments, and developing computer simulations of colloidal particles in external fields. These projects will lead to new analysis techniques in microrheology and optical microscopy and will advance the development of inks for 3D printing. The specific objectives of this project are to (1) train and mentor 18 (6 students per year for 3 years) undergraduate students on soft matter research in a collaborative and international environment, (2) develop and foster research collaborations among institutions in the U.S. and Mexico, (3) characterize and harness the rheological properties of complex fluids and gels for enhancing our fundamental knowledge of soft matter and for applying such materials to 3D printing applications, (4) disseminate research outcomes at scientific conferences and in peer-reviewed journals, and (5) develop a cohort of scientists from predominantly underrepresented groups who can network and collaborate effectively with others from various backgrounds and who can draw upon a diverse set of mentors. IRES participants will advance scientific knowledge in projects that range from applied to fundamental using experimental and computational approaches. Students will learn how these diverse approaches used by an international team can address pressing scientific and engineering problems.&lt;br/&gt;&lt;br/&gt;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.

04/02/2024

04/02/2024

None

Grant

47.079

1

4900

4900

2426728

{'FirstName': 'Ryan', 'LastName': 'McGorty', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ryan McGorty', 'EmailAddress': 'rmcgorty@sandiego.edu', 'NSF_ID': '000728711', 'StartDate': '04/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of San Diego', 'CityName': 'SAN DIEGO', 'ZipCode': '921102476', 'PhoneNumber': '6192606825', 'StreetAddress': '5998 ALCALA PARK FRNT', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '51', 'CONGRESS_DISTRICT_ORG': 'CA51', 'ORG_UEI_NUM': 'V6S1GT51XD56', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of San Diego', 'CityName': 'SAN DIEGO', 'StateCode': 'CA', 'ZipCode': '921102476', 'StreetAddress': '5998 ALCALA PARK FRNT', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '51', 'CONGRESS_DISTRICT_PERF': 'CA51'}

{'Code': '7727', 'Text': 'IRES Track I: IRES Sites (IS)'}

2023~24910

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426728.xml'}

Collaborative Research: NSF-NFRF: WhaleAdapt: adaptation of vulnerable subsistence-based North Atlantic communities to marine mammal redistribution under climate change

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

Countries of the Global South and Indigenous communities are especially vulnerable to climate change, partly due to reliance on local, wild-caught foods. At least 54 species of toothed whales are consumed across 86 countries worldwide and the practice is increasing. Yet, toothed whale harvest often occurs in remote and understudied regions, leaving a large gap in knowledge of whale populations, their contamination and nutritional value, and their socioeconomic importance to communities, particularly in the context of accelerating climate change. WhaleAdapt is an international collaboration of researchers and local organizations from Canada, the U.S., Denmark (Greenland, Faroe Islands), and St. Vincent and the Grenadines (Windward Islands, eastern Caribbean) that uses cutting-edge approaches combined with local ecological knowledge to address the overarching question – how can vulnerable communities reliant on whale consumption adapt successfully to shifting marine resources due to climate change? WhaleAdapt is engaged and integrated with the most vulnerable groups from the tropics to the Arctic to address key risks through novel interdisciplinary approaches and will contribute to better understanding how climate change is impacting the spatial and trophic ecology of cetaceans as marine predators in the North Atlantic, and to help whaling communities across three countries to make a sustainable, healthy, and socioeconomically viable adaptation to shifting marine resources. Results have broad implications for national agencies and international agreements on climate change, biodiversity, and pollution.<br/><br/>WhaleAdapt has five major objectives: 1. Investigate past, present, and future distribution and relative abundance of North Atlantic toothed whales using local ecological knowledge (LEK) and habitat suitability modelling; 2. Use chemical tracers to evaluate the trophic roles of toothed whales across the North Atlantic and study climate-driven changes; 3. Assess concentrations of key contaminants and nutrients in whales consumed as foods, and improve knowledge on their sources and pathways using isotopic tracers; 4. Inform the sustainability of harvest based on population size, structure, and demographic history; 5. Co-develop knowledge on the economic and cultural value of whales as foods relative to newly available cetaceans and other wild (e.g., fish) and imported foods. This project will use cutting-edge approaches across disciplines in habitat and distribution modeling, dietary tracers (stable isotopes, fatty acid analysis), genomics, ecotoxicology, and social science, particularly using LEK. Results will engage the academic community and policy makers. Results will be disseminated to researchers through conference presentations, invited seminars, peer‐reviewed papers, and contributions to national and international assessment reports.<br/><br/>This is a project jointly funded by the U.S. National Science Foundation and funding agencies from Canada via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.050

1

4900

4900

2426736

{'FirstName': 'Jeremy', 'LastName': 'Kiszka', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeremy J Kiszka', 'EmailAddress': 'jkiszka@fiu.edu', 'NSF_ID': '000769445', 'StartDate': '05/31/2024', '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': '769900', 'Text': 'Integrat & Collab Ed & Rsearch'}

2024~376582

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426736.xml'}

Collaborative Research: NSF-NFRF: WhaleAdapt: adaptation of vulnerable subsistence-based North Atlantic communities to marine mammal redistribution under climate change

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

Countries of the Global South and Indigenous communities are especially vulnerable to climate change, partly due to reliance on local, wild-caught foods. At least 54 species of toothed whales are consumed across 86 countries worldwide and the practice is increasing. Yet, toothed whale harvest often occurs in remote and understudied regions, leaving a large gap in knowledge of whale populations, their contamination and nutritional value, and their socioeconomic importance to communities, particularly in the context of accelerating climate change. WhaleAdapt is an international collaboration of researchers and local organizations from Canada, the U.S., Denmark (Greenland, Faroe Islands), and St. Vincent and the Grenadines (Windward Islands, eastern Caribbean) that uses cutting-edge approaches combined with local ecological knowledge to address the overarching question – how can vulnerable communities reliant on whale consumption adapt successfully to shifting marine resources due to climate change? WhaleAdapt is engaged and integrated with the most vulnerable groups from the tropics to the Arctic to address key risks through novel interdisciplinary approaches and will contribute to better understanding how climate change is impacting the spatial and trophic ecology of cetaceans as marine predators in the North Atlantic, and to help whaling communities across three countries to make a sustainable, healthy, and socioeconomically viable adaptation to shifting marine resources. Results have broad implications for national agencies and international agreements on climate change, biodiversity, and pollution.<br/><br/>WhaleAdapt has five major objectives: 1. Investigate past, present, and future distribution and relative abundance of North Atlantic toothed whales using local ecological knowledge (LEK) and habitat suitability modelling; 2. Use chemical tracers to evaluate the trophic roles of toothed whales across the North Atlantic and study climate-driven changes; 3. Assess concentrations of key contaminants and nutrients in whales consumed as foods, and improve knowledge on their sources and pathways using isotopic tracers; 4. Inform the sustainability of harvest based on population size, structure, and demographic history; 5. Co-develop knowledge on the economic and cultural value of whales as foods relative to newly available cetaceans and other wild (e.g., fish) and imported foods. This project will use cutting-edge approaches across disciplines in habitat and distribution modeling, dietary tracers (stable isotopes, fatty acid analysis), genomics, ecotoxicology, and social science, particularly using LEK. Results will engage the academic community and policy makers. Results will be disseminated to researchers through conference presentations, invited seminars, peer‐reviewed papers, and contributions to national and international assessment reports.<br/><br/>This is a project jointly funded by the U.S. National Science Foundation and funding agencies from Canada via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.050, 47.079

1

4900

4900

2426737

{'FirstName': 'Russell', 'LastName': 'Fielding', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Russell T Fielding', 'EmailAddress': 'russell.fielding@gmail.com', 'NSF_ID': '000265194', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Coastal Carolina University', 'CityName': 'CONWAY', 'ZipCode': '295268428', 'PhoneNumber': '8433495030', 'StreetAddress': '755 HIGHWAY 544', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'SC07', 'ORG_UEI_NUM': 'D9KPSNLHD9J5', 'ORG_LGL_BUS_NAME': 'COASTAL CAROLINA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Coastal Carolina University', 'CityName': 'CONWAY', 'StateCode': 'SC', 'ZipCode': '295268428', 'StreetAddress': '755 HIGHWAY 544', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'SC07'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '769900', 'Text': 'Integrat & Collab Ed & Rsearch'}]

2024~193734

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426737.xml'}

RAPID: Quantifying post-wildfire carbon retention and cycling in moist, coniferous forests of the Pacific Northwest

NSF

06/15/2024

05/31/2025

{'Value': 'Standard Grant'}

{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}

{'SignBlockName': 'Jason West', 'PO_EMAI': 'jwest@nsf.gov', 'PO_PHON': '7032927410'}

Wildfires are increasing in frequency and intensity across the western U.S. and are a major risk to forests in the region. One major impact of wildfires in forests is the release of carbon when forest vegetation and soils burn. This increases atmospheric greenhouse gas concentrations, which in turn drives climate change. However, not all carbon in forest vegetation and soils is released to the atmosphere during wildfires. A large proportion is left in the forest, with part of this carbon being chemically and physically altered to ash and charcoal (called pyrogenic carbon). Pyrogenic carbon can be a large proportion of the carbon that is affected by a wildfire and can have important effects on how forests regrow. Despite this, researchers have never studied pyrogenic carbon formation in the highly productive temperate rainforests of the Pacific Northwest region, where wildfires are predicted to increase in frequency and intensity. This RAPID project will examine pyrogenic carbon production during wildfires in Pacific Northwest forests, as well as how newly formed pyrogenic carbon affects soil carbon cycling during ecosystem regeneration. This is critical for improving our ability to estimate greenhouse gas emissions and understand the vulnerability of forests to wildfires across the Pacific Northwest.<br/><br/>Despite the potential importance of pyrogenic carbon for post-wildfire forest recovery and accurate estimations of wildfire emissions, no research on the topic has been done in the temperate rainforests of the Pacific Northwest. From August-October of 2023, the mixed-severity Lookout Fire burned the H.J. Andrews Experimental Forest in the western cascades of Oregon—including forest stands with old growth characteristics—presenting a unique opportunity to close this research gap. This study will build on a unique dataset of fire behavior and pre- and post-fire vegetation conditions collected by the U.S. Forest Service’s Fire Behavior Assessment Team (FBAT) to (i) quantify pyrogenic carbon stocks as a function of total wildfire-affected carbon, and (ii) evaluate the influence of pyrogenic carbon on pathways of soil carbon loss and accumulation. The research will integrate existing datasets with field sampling of pyrogenic carbon stocks, tracking total soil and heterotrophic respiration in addition to water extractable organic carbon throughout the growing season, and laboratory analyses of soil carbon, soil nitrogen, and microbial 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.

05/28/2024

05/28/2024

None

Grant

47.074

1

4900

4900

2426744

[{'FirstName': 'Jacob', 'LastName': 'Bukoski', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jacob J Bukoski', 'EmailAddress': 'jacob.bukoski@oregonstate.edu', 'NSF_ID': '000944753', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Georgia', 'LastName': 'Seyfried', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Georgia S Seyfried', 'EmailAddress': 'georgia.seyfried@oregonstate.edu', 'NSF_ID': '0000A021H', 'StartDate': '05/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'ZipCode': '973318655', 'PhoneNumber': '5417374933', 'StreetAddress': '1500 SW JEFFERSON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'MZ4DYXE1SL98', 'ORG_LGL_BUS_NAME': 'OREGON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'StateCode': 'OR', 'ZipCode': '973318655', 'StreetAddress': '1500 SW JEFFERSON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}

{'Code': '738100', 'Text': 'Ecosystem Science'}

2024~176388

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426744.xml'}

FMSG: Bio-Manufacturing of Hybrid Tissue-Electronic and Photonic Devices

NSF

01/01/2024

08/31/2024

{'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'}

The ability to integrate living tissues with electronic and photonic devices has potential to impact many aspects of human health, including neurological/neuromuscular disease and injury, such as spinal cord injury and Alzheimer's disease and secretory pathologies, such as diabetes and glaucoma. To date, bioelectronic devices have been employed in several arenas, most notably cardiac pacemakers, cochlear implants, which have enabled tens of thousands of profoundly deaf people to communicate in a hearing world, and deep brain stimulation, which became widely used in the 1990’s to treat Parkinson disease and essential tremor. Despite the success of these devices, the potential for bioelectrical and biophotonic devices has scarcely been realized, limited in part by challenges in interfacing devices with living tissues and the potential tissue damage due to device insertion. This future manufacturing seed grant will develop new manufacturing methods to create electronic and photonic devices that are biocompatible (i.e., able to facilitate growth and function of healthy biological tissues) and are bio-resilient (i.e., able to withstand the wet, salty, proteinaceous chemical environment of biological systems). In addition, it will address how to interface the living tissue with electronic and photonic devices so that information (e.g., brain electrical signals, muscle stimulation, neuronal responses) can be transferred between the electronic or photonic device and the living system. This project will build on existing advanced technical education programs in semiconductor technologies and biomedical advanced technologies to identify the core competencies required for the field of manufacturing and train a workforce at the community college, bachelors, masters, and doctoral degree level, broadening participation through our interactions with community college partners and engaging with industry to ensure that the curriculum developed remains responsive to industry needs. Finally, a detailed curriculum based upon core competencies identified by the project team in conjunction with the Industrial Advisory Board will be developed and piloted at key community colleges and in bachelors and masters level programs at SUNY Polytechnic Institute and Albany College of Pharmacy and Health Sciences. Feedback from trainees and the Industrial Advisory Board will be used to refine the curriculum for wider deployment in the Future Manufacturing Research Grant phase. This Future Manufacturing project is jointly funded by the Divisions of ECCS and CBET in the Directorate of Engineering. <br/><br/>Leveraging the strengths of SUNY Polytechnic Institute, AIM Photonics (a federally-funded American Institute for Manufacturing entity located at SUNY Polytechnic Institute), the Northeast Advanced Technological Education Center (an NSF-funded training program) and partners including Albany College of Pharmacy and Health Sciences and the Neural Stem Cell Institute, this future manufacturing seed grant will focus on design and manufacturing of silicon-wafer electronic and photonic devices with two technical objectives: 1) Design and manufacture of silicon-wafer electronic and photonic devices to interface with biological materials and 2) Development of interfaces for electrical and photonic interaction and measurement of 3D cultures. To identify the barriers to addressing these challenges at the manufacturing scale, the project will include preliminary research focused on two testbeds: 1) Implementation of a pressure sensing device that can measure outflow from ocular tissues to address development of glaucoma therapeutics; 2) Creation of multielectrode arrays interfaced with three-dimensional cell cultures (e.g., neuronal organoids) for electrical stimulation and observation. A significant focus in these testbed experiments will be on design for manufacturability, to enable the transition from laboratory devices to manufactured devices. In addition, a series of workshops with a wide range of academic and industrial partners will be conducted to identify additional research and manufacturing issues to be addressed in a subsequent Future Manufacturing Research Grant.<br/><br/>This Future Manufacturing project is jointly funded by the Divisions of ECCS and CBET in the Directorate of Engineering.<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.

04/18/2024

05/09/2024

None

Grant

47.041

1

4900

4900

2426775

{'FirstName': 'Susan', 'LastName': 'Sharfstein', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Susan T Sharfstein', 'EmailAddress': 'ssharfstein@albany.edu', 'NSF_ID': '000450254', 'StartDate': '04/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY at Albany', 'CityName': 'ALBANY', 'ZipCode': '122220100', 'PhoneNumber': '5184374974', 'StreetAddress': '1400 WASHINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'NY20', 'ORG_UEI_NUM': 'NHH3T1Z96H29', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'NHH3T1Z96H29'}

{'Name': 'SUNY at Albany', 'CityName': 'ALBANY', 'StateCode': 'NY', 'ZipCode': '122220100', 'StreetAddress': '1400 WASHINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_PERF': 'NY20'}

[{'Code': '142Y00', 'Text': 'FM-Future Manufacturing'}, {'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}]

['2021~70851', '2022~13200', '2023~13200', '2024~11094']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426775.xml'}

Conference: Multidisciplinary Symposium: Integrating emerging areas in physiology with genomics, breeding, and technology/AI

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Gerald Schoenknecht', 'PO_EMAI': 'gschoenk@nsf.gov', 'PO_PHON': '7032925076'}

Achieving food security in a changing climate is a major global challenge that directly impacts the world economy welfare, environmental sustainability, and human health. Such a complex challenge requires a multidisciplinary approach and the commitment of stakeholders (government, academia, industry, non-governmental organizations, producers, and consumers). This NSF award supports graduate student participation in the Multidisciplinary Symposium at the 2024 International Tri-Society-Agronomic, Crop and Soil Science Societies (ASA, CSSA, and SSSA) Annual Conference held November 10th -13th, 2024, in San Antonio, Texas. The support provides an opportunity for students from United States institutions with limited resources to attend a global conference for the first time, present their research in the oral and poster competitions, interact with researchers at different career levels, get exposed to cutting-edge technology, expand their network, and develop new collaborations with scientists from multiple disciplines. Ultimately, the selected students can incorporate the multidisciplinary approach in their current or future research projects and join the global community in fighting food insecurity. <br/><br/>The CSSA-Multidisciplinary Symposium will bring together researchers from all stages and multiple disciplines (including plant physiology, genomics, biotechnology, genetics, breeding, engineering, modeling, computational biology, and artificial intelligence (AI)) to share and discuss cutting-edge technologies, controversies, challenges, and emerging plant science research areas. The goal is to highlight the critical need for multidisciplinary research and inspire researchers to find solutions to global food security in future climates. The objectives include 1) to advance our knowledge of complex biological questions using a multidisciplinary approach, 2) to disseminate cutting-edge and emerging areas in multidisciplinary research, 3) to broaden participation and train graduate students from underrepresented groups in science, and 4) to promote collaborative academic/government/industry partnerships. The NSF conference travel grant will support 15 graduate students from US higher education institutions. The travel application will be available at the CSSA meeting website. The funds will provide travel support for outstanding graduate applicants from under-sourced universities to showcase their research at the high-reputation international conference. The proposed symposium integrates research, education, and outreach and will be open to all interested stakeholders to ensure a broad impact.<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.

05/02/2024

05/02/2024

None

Grant

47.074

1

4900

4900

2426797

{'FirstName': 'Haydee', 'LastName': 'Echevarria Laza', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Haydee Echevarria Laza', 'EmailAddress': 'haydee.laza@ttu.edu', 'NSF_ID': '000827880', 'StartDate': '05/02/2024', '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': '794091035', 'StreetAddress': '2500 BROADWAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'TX19'}

{'Code': '132900', 'Text': 'Plant Genome Research Project'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426797.xml'}

Conference: Modeling Randomness in Neural Network Training: Mathematical, Statistical, and Numerical Guarantees

NSF

06/01/2024

05/31/2025

{'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': 'Phillip Regalia', 'PO_EMAI': 'pregalia@nsf.gov', 'PO_PHON': '7032922981'}

Neural networks are at the heart of modern machine learning and artificial intelligence (ML/AI) systems. The rapid development of these technologies has led to rapid adoption across a variety of domains, particularly in speech processing, computer vision, and natural language processing. At the same time, the theoretical underpinnings of these statistical models are not yet fully understood. The question of how and why neural networks “work" can be approached from a variety of mathematical perspectives. One of the most promising mathematical tools for analysis of neural networks is random matrix theory, a field that has recently reached mathematical maturity and whose relevance and applicability to modeling, understanding, and characterizing a vast array of science and technology problems keeps growing every day. From principle component analysis and random growth processes to particle interactions and community detection in large networks, random matrices are now used to investigate and explain high-dimensional phenomena like concentration (the so- called "blessing of dimensionality" as opposed to the "curse of dimensionality"). Recent results in universality allow for usage of more complex, non-Gaussian models, sometimes even allowing for limited dependencies. This prompts the question: what can probability theory in general---and random matrix theory (RMT) in particular---tell us about neural networks, modern machine learning, and AI? Such fundamental insights could lead to novel approaches that simplify or improve the efficiency of neural network design and training.<br/><br/>The DIMACS Center at Rutgers University will hold the Workshop on Modeling Randomness in Neural Network Training: Mathematical, Statistical, and Numerical Guarantees at Rutgers University on June 5–7, 2024. This is a multidisciplinary workshop to create bridges between the different mathematical and computational communities by bringing together researchers with a diverse set of perspectives on neural networks. Random matrix theory can be used to understand different phenomena in neural network training. The workshop will center around the following themes: understanding matrix-valued random processes that arise during neural network training, modeling/measuring uncertainty and designing estimators for training processes, and applications to these designs within optimization algorithms.<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.

05/24/2024

05/24/2024

None

Grant

47.049, 47.070

1

4900

4900

2426825

[{'FirstName': 'Ioana', 'LastName': 'Dumitriu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ioana Dumitriu', 'EmailAddress': 'idumitriu@ucsd.edu', 'NSF_ID': '000071417', 'StartDate': '05/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tony', 'LastName': 'Chiang', 'PI_MID_INIT': 'Y', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tony Y Chiang', 'EmailAddress': 'tc@alum.mit.edu', 'NSF_ID': '000575652', 'StartDate': '05/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Anand', 'LastName': 'Sarwate', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anand D Sarwate', 'EmailAddress': 'anand.sarwate@rutgers.edu', 'NSF_ID': '000608994', 'StartDate': '05/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

[{'Code': '126300', 'Text': 'PROBABILITY'}, {'Code': '126600', 'Text': 'APPLIED MATHEMATICS'}, {'Code': '779700', 'Text': 'Comm & Information Foundations'}]

2024~39733

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426825.xml'}

CRII: III: Explainable Artificial Intelligence for Biodiversity Science & Conservation

NSF

03/01/2024

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': 'Sylvia Spengler', 'PO_EMAI': 'sspengle@nsf.gov', 'PO_PHON': '7032927347'}

Extinction of biological species is accelerating rapidly. Significant uncertainty is often involved in predicting the extinction or population decline of species, even with high-resolution information. Changes in the taxonomic classification of biological species is a key challenge that impacts both biodiversity conservation and policy decisions. The taxonomy is described in words and these words provide an opportunity to use natural language processing and machine learning (ML) to clarify species relationships and provide novel insights into extinction risk by addressing the variability in species taxonomy. Developing an accurate and scalable machine learning and artificial intelligence (ML/AI) for “taxonomic intelligence” can help support the robustness of conservation decision making. This is important because the taxonomic classification can move a group of organisms in or out of consideration for legal protection. AI can help in this classification and support coordination of conservation projects.<br/><br/>The goal of this project is to develop AI/ML techniques to provide novel insights into extinction risk, by projecting different contingent outcomes for species distributions and risks under different taxonomic perspectives. It is critical that the derived insights be understandable to humans, to safely translate these outcomes into operational recommendations. Biodiversity data, which include taxonomical and geospatial data, pose unique challenges to AI in that they are heterogeneous, structurally complex, and frequently change. This project aims to address these challenges with a novel approach combining Natural Language Processing (NLP) from the textual data of relevant scientific publications, and automated inductive and deductive reasoning, including qualitative spatial reasoning incorporating the taxonomic factor and relevant domain structures, for discovery of human-understandable knowledge for conservation biology applications. In doing so, this project also has the potential to advance AI beyond a single application domain. The research activities to be undertaken in this award include data and knowledge curation with the help of domain experts, and the development and evaluation of the aforementioned AI techniques.<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.

04/15/2024

04/15/2024

None

Grant

47.070

1

4900

4900

2426835

{'FirstName': 'Atriya', 'LastName': 'Sen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Atriya Sen', 'EmailAddress': 'atriya.sen@okstate.edu', 'NSF_ID': '000827137', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'ZipCode': '740781031', 'PhoneNumber': '4057449995', 'StreetAddress': '401 WHITEHURST HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OK03', 'ORG_UEI_NUM': 'NNYDFK5FTSX9', 'ORG_LGL_BUS_NAME': 'OKLAHOMA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'StateCode': 'OK', 'ZipCode': '740781031', 'StreetAddress': '401 WHITEHURST HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OK03'}

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

2023~169618

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426835.xml'}

Conference: 2024 Cytoskeletal Motors Gordon Research Conference and Seminar

NSF

06/15/2024

05/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Matt Buechner', 'PO_EMAI': 'mbuechne@nsf.gov', 'PO_PHON': '7032924675'}

This award will support the 2024 Gordon Research Conference (GRC) and Seminar (GRS) on Cytoskeletal Motors, to be held July 7-12, 2024 at the University of Southern Maine in Portland, ME. This meeting will be attended by graduate students, postdocs, and junior and senior faculty researchers from broad-ranging disciplines to discuss and advance our understanding of all aspects of the structure and function of these protein engines that move the cell itself as well as the various structure such as mitochondria and chromosomes within the cell. The interactions of cell biologists, geneticists, biochemists, and biophysicists will increase understanding of these motors and how they function to maintain cell structure, and the senior scientists will engage with and train junior scientists. This engagement is a priority of the conference and especially the seminar, in talks and poster sessions to allow all participants to display and discuss their research. NSF support will be used to defray registration fees and/or travel costs to allow attendance of participants from early stages of their careers, and for members of groups under-represented in this field.<br/><br/>This meeting will be attended by graduate students, postdoctoral fellows, and senior researchers to discuss our understanding of all aspects of the motors that drive movement along actin and microtubule tracks of organelles and chromosomes to where they are needed within cells, as well as motility of the entire cell. Sessions will focus on recent advances and new understanding of topics such as “Movements Driven by Molecular Motors and Dynamic Filament Polymerization,” “Filaments and Motors as Active Matter,” “Motor Regulation: From Adaptors to Autoinhibition,” “Filament Diversity, Dynamics and Cross Talk,” and “High Resolution Views of Motors.” In addition to formal talks, engagement will be facilitated by two poster sessions to stimulate interactions between researchers. NSF support will be used to defray travel costs to allow attendance of participants from early stages of their careers, especially for members of groups underrepresented in this field.<br/><br/>This award is funded by the Cellular Dynamics and Function Cluster of the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences.<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.

06/18/2024

06/18/2024

None

Grant

47.074

1

4900

4900

2426946

{'FirstName': 'Margaret', 'LastName': 'Titus', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Margaret A Titus', 'EmailAddress': 'titus004@umn.edu', 'NSF_ID': '000114783', 'StartDate': '06/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'ZipCode': '028183454', 'PhoneNumber': '4017834011', 'StreetAddress': '5586 POST RD UNIT 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'XL5ANMKWN557', 'ORG_LGL_BUS_NAME': 'GORDON RESEARCH CONFERENCES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'StateCode': 'RI', 'ZipCode': '028183454', 'StreetAddress': '5586 POST RD UNIT 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}

{'Code': '111400', 'Text': 'Cellular Dynamics and Function'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426946.xml'}

RAPID: Developing an Interactive Dashboard for Collecting and Curating Traffic Data after the March 26, 2024 Francis Scott Key Bridge Collapse

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

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

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

This Grants for Rapid Response Research (RAPID) award will support research that will create a centralized, interactive online dashboard for collecting and curating traffic data in and around Baltimore, during and after the Francis Scott Key Bridge collapse on March 26, 2024. Although the immediate focus is on the aftermath of the Francis Scott Key Bridge collapse in Baltimore, Maryland, the findings are expected to yield insights that extend beyond this specific event, contributing to a broader understanding of how transportation infrastructure disruptions influence travel behaviors in both short and long term. This knowledge will aid transportation planners and engineers in devising strategies and policies aimed at reducing the impacts of future infrastructure failures, enhancing emergency response protocols and fostering resilient transportation networks. The dashboard will offer the public and government agencies critical information that they need to adapt their behaviors. Research activities will be incorporated into undergraduate and graduate courses to promote the synergy of research and education. Further, to broaden participation, this project will actively seek to involve under-represented minority students at both the undergraduate and graduate levels by attracting students through an undergraduate-level research course and a summer STEM program at Drexel University. <br/><br/>This project will collect both local and regional traffic data during and after the Francis Scott Key Bridge collapse, using multiple publicly available data courses. A multi-scale sampling method will be used to reconcile the need for large-scale data collection and the demand for efficiency. Specifically, link-level traffic data for the entire road network will be collected in Baltimore and nearby counties like Anne Arundel and Howard in Maryland, while data will only be collected for major arterial routes and highways in broader regions such as Harford County in the State of Maryland. Beyond the life cycle of this project, the dataset will continue to benefit the academic community, allowing researchers to study traffic adaptation to transportation infrastructure failures. Additionally, the dashboard will become a reusable tool for future data collection and curation efforts when similar disasters happen in the future, which would much improve the response time of individuals and government agencies by offering timely information.<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.

04/17/2024

04/17/2024

None

Grant

47.041

1

4900

4900

2426947

{'FirstName': 'Zhiwei', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zhiwei Chen', 'EmailAddress': 'zc392@drexel.edu', 'NSF_ID': '000927521', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191042875', 'PhoneNumber': '2158956342', 'StreetAddress': '3141 CHESTNUT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'XF3XM9642N96', 'ORG_LGL_BUS_NAME': 'DREXEL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191042875', 'StreetAddress': '3141 CHESTNUT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426947.xml'}

NSF-NFRF: Community water systems: Climate vulnerabilities and resilience opportunities

NSF

06/01/2024

05/31/2027

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Allen Pope', 'PO_EMAI': 'apope@nsf.gov', 'PO_PHON': '7032928030'}

Today, more than two billion people live in countries experiencing high water stress. By 2050, that figure may reach 3.2 billion and by 2050 water scarcity could displace 150-200 million people. Changing climates affect water security for daily needs, livelihoods, and culture and increase the frequency and severity of extreme weather, like floods and fires which can disrupt critical infrastructure including roadways and pipelines necessary to provide water for peoples’ well-being. Threats to critical infrastructure are intrinsically connected to threats to water security through the roadways, water kiosks, pipeline infrastructure, and other mechanisms that provide water to households. This project advances knowledge on the vulnerabilities of community-managed water systems to the impacts of climate change and investigates opportunities to strengthen their resilience in the face of future climate risks. The broader impacts of the proposed work create a global water security toolkit that integrates the processes for co-producing water resilience action plans with communities; an outcome that can be scaled for use by the 3.2 billion people who may face water insecurity by 2050.<br/><br/>The goal of this inter-disciplinary project is to mitigate the risks to water security of Indigenous communities living in five climate-vulnerable locations: Turkana in Kenya, the Nile region in South Sudan, Varanger in Norway, First Nations communities in western Canada, and Native communities in rural Alaska. The project will investigate risks to water security at local to regional scales, focusing on the impacts of extreme weather on damage to the infrastructure and networks needed to support water security. The project methods will combine climate scenario modeling with stakeholder engagement targeting both local communities and experts to understand current and future climate vulnerabilities of local water systems. Broadly, the project will address the connected risks of displacement because of drought, wildfires, floods, landslides/erosion, and effects on the ecosystems impacting the traditional land-based activities, community’s livelihoods, and food security. This project will enable climate-vulnerable Indigenous communities globally to build an understanding of the climate vulnerabilities in their water systems, create action plans to support their climate resilience and water security goals, and implement and evaluate localized interventions to augment the resilience of their water systems.<br/><br/>This is a project jointly funded by the U.S. National Science Foundation and funding agencies from Canada and Norway via the 2023 International Joint Initiative for Research on Climate Change Adaptation and Mitigation Competition. This Competition allowed a single joint international proposal to be submitted and peer-reviewed by Canada. Upon successful joint determination of an award recommendation, each agency funds the proportion of the budget that supports scientists at institutions in their respective countries.<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.

05/31/2024

05/31/2024

None

Grant

47.079

1

4900

4900

2426979

[{'FirstName': 'Karl', 'LastName': 'Linden', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karl G Linden', 'EmailAddress': 'karl.linden@colorado.edu', 'NSF_ID': '000157705', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Evan', 'LastName': 'Thomas', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Evan Thomas', 'EmailAddress': 'ethomas@colorado.edu', 'NSF_ID': '000710220', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Denis', 'LastName': 'Muthike', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Denis M Muthike', 'EmailAddress': 'denis.muthike@colorado.edu', 'NSF_ID': '0000A017V', 'StartDate': '05/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'ZipCode': '803090001', 'PhoneNumber': '3034926221', 'StreetAddress': '3100 MARINE ST', 'StreetAddress2': 'STE 481 572 UCB', 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'SPVKK1RC2MZ3', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF COLORADO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'StateCode': 'CO', 'ZipCode': '803090001', 'StreetAddress': '3100 MARINE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}

{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}

2024~650920

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426979.xml'}

Travel: Student Travel Support for the Doctoral Colloquium at IEEE Visualization (IEEE VIS) 2024

NSF

06/01/2024

01/31/2025

{'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': 'Cornelia Caragea', 'PO_EMAI': 'ccaragea@nsf.gov', 'PO_PHON': '7032922706'}

This travel grant that will support student attendees of the Doctoral Colloquium at IEEE Visualization conference (October 13-18, 2024) in St. Pete Beach, Florida. It will support conference expenses for 15 US-based Ph.D. students in visualization who are in the process of formulating their dissertation project and seek feedback at a critical stage in their graduate training. The student participants and expert panelists will be selected based on their research excellence and their contribution to the goal of promoting full participation of women and other underrepresented groups. We also strive for diversity in institution, scientific discipline, and research specialization.<br/><br/>The event will foster student academic and professional development through three main prongs: (1) research, (2) mentorship, and (3) networking. To help students develop and finetune their research, each student will present and receive feedback on their dissertation topic from expert panelists, including senior researchers in the field who are not their doctoral advisors and from their peers. This guidance will provide a fresh perspective on their dissertation topics, help develop the intellectual contributions of their work, and help situate their work in topics of core interest to the broader visualization community. The work presented at the event reflects the state-of-the-art in visualization. To provide mentorship, each student participant will be assigned a mentor among the expert panelists. During the Doctoral Colloquium the mentor will provide detailed feedback on student’s submitted materials, offer support and encouragement for completing the dissertation research, and answer professional development questions. To foster networking opportunities, the Doctoral Colloquium will host a lunch for building social connections and a round table discussion to address student questions about career paths, job searches, grant writing, and becoming an independent researcher. Across all activities the Doctoral Colloquium will establish and strengthen professional networks and research collaborations among junior and senior researchers, which are beneficial for the junior researchers, and critical for the advancement of the field. By building this community at the beginning of the VIS conference, students can continue to network and potentially establish collaborations throughout the duration of IEEE VIS 2024.<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.

06/03/2024

06/03/2024

None

Grant

47.070

1

4900

4900

2426997

{'FirstName': 'Emily', 'LastName': 'Wall', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emily Wall', 'EmailAddress': 'emily.wall@emory.edu', 'NSF_ID': '000845738', 'StartDate': '06/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Emory University', 'CityName': 'ATLANTA', 'ZipCode': '303221061', 'PhoneNumber': '4047272503', 'StreetAddress': '201 DOWMAN DR NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'S352L5PJLMP8', 'ORG_LGL_BUS_NAME': 'EMORY UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Emory University', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303224250', 'StreetAddress': '400 DOWMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}

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

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2426997.xml'}

Conference: NSF Student Travel Support for the 2024 IEEE International Conference on Big Data (IEEE BigData 2024)

NSF

10/01/2024

09/30/2025

{'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': 'Judith Cushing', 'PO_EMAI': 'jcushing@nsf.gov', 'PO_PHON': '3607016450'}

This project will provide NSF support for students to attend and participate in the IEEE International Conference on Big Data to be held in Washington DC December 15-18, 2024. The grant will be used exclusively for students in US-based institutions, and it will enable the supported students to travel to the conference and thus participate in the conference and its associated workshops. The funding will defray the registration, travel, and lodging costs for the students.<br/><br/>It will enable a life-enriching first-time experience for many students, giving them a taste of the research environment in both academic and industrial circles worldwide. VLDB is a premier conference in the area of databases that brings together technical research papers, tutorials, and workshops centered on various aspects of database research and practice. Participation in this conference will enable the students to enhance their scientific foundation and build their professional networks, and thus contribute directly to training the next generation of scientists who are both consumers and developers of technology in database management system design and implementation. The grant will have a direct impact in creating a highly-qualified workforce who can take on the emerging data science challenges of the future.<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.

04/25/2024

04/25/2024

None

Grant

47.070

1

4900

4900

2427004

[{'FirstName': 'Chang-Tien', 'LastName': 'Lu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chang-Tien Lu', 'EmailAddress': 'ctlu@vt.edu', 'NSF_ID': '000258353', 'StartDate': '04/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Wei', 'LastName': 'Ding', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wei Ding', 'EmailAddress': 'wei.ding@umb.edu', 'NSF_ID': '000518968', 'StartDate': '04/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yong', 'LastName': 'Zhuang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yong Zhuang', 'EmailAddress': 'yong.zhuang@gvsu.edu', 'NSF_ID': '000988123', 'StartDate': '04/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Grand Valley State University', 'CityName': 'ALLENDALE', 'ZipCode': '494019401', 'PhoneNumber': '6163316840', 'StreetAddress': '1 CAMPUS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MI02', 'ORG_UEI_NUM': 'Y2M5HUXKJPF1', 'ORG_LGL_BUS_NAME': 'GRAND VALLEY STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Grand Valley State University', 'CityName': 'ALLENDALE', 'StateCode': 'MI', 'ZipCode': '494019403', 'StreetAddress': '1 CAMPUS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MI02'}

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

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427004.xml'}

Travel Grant: 2024 Biogenic Hydrocarbons and the Atmosphere Gordon Research Conference and Seminar; Castelldefels, Barcelona, Spain; June 8-14, 2024

NSF

05/15/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '06020100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}

{'SignBlockName': 'Sylvia Edgerton', 'PO_EMAI': 'sedgerto@nsf.gov', 'PO_PHON': '7032928522'}

The Biogenic Hydrocarbons and the Atmosphere Conference and Seminar will bring together an international group of researchers in the biological, ecological, and atmospheric sciences from universities, government laboratories, and private research institutes to promote discussion of information and ideas on topics of contemporary interest related to biogenic hydrocarbons in the atmosphere. This will be the 11th Gordon Research Conference to address the topic of “Biogenic Hydrocarbons and the Atmosphere,” the first of which was in 2000. The conference is organized with the overall goal of reporting and discussing the latest research findings on novel sources of biogenic hydrocarbons, ecosystem-atmosphere interactions, atmospheric transport, and atmospheric chemistry/air quality modulated by hydrocarbon emissions. This meeting brings together leaders and scholars to gain a better understanding of the biological, ecological, and atmospheric roles of biogenic hydrocarbons in a unique, cross-disciplinary environment.<br/><br/>The theme of the 2024 Biogenic Hydrocarbons and the Atmosphere Conference and Seminar conference is “Biosphere-Atmosphere Interactions and Impacts in the Anthropocene.” The meeting will concentrate on the latest developments in the field, including the synthesis, release and subsequent oxidation of biogenic hydrocarbons, their molecular genetics and the biochemical mechanisms through which they are produced, stored and released, as well as their function at a cellular level, and the role they play in photosynthesis, stomatal control and plant defense mechanisms. Once released to the atmosphere, these biogenic hydrocarbons rapidly react with ozone, nitrate, and hydroxyl radicals, leading to the formation of oxidants in the atmosphere, ozone, and secondary organic aerosol. These secondary products affect air quality and regional and global climate thus creating feedbacks to the land surface.<br/><br/>The Conference will take place in Castelldefels, Barcelona, Spain from June 9th to 14th, preceded by the Gordon Research Seminar (GRS), held for early career researchers, on June 8th-9th. NSF support will primarily be used for registration and travel for women, early career scientists, post docs, and graduate students from the US to participate in 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.

05/01/2024

05/01/2024

None

Grant

47.050

1

4900

4900

2427028

{'FirstName': 'Karena', 'LastName': 'McKinney', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Karena A McKinney', 'EmailAddress': 'kamckinn@colby.edu', 'NSF_ID': '000056318', 'StartDate': '05/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'ZipCode': '028183454', 'PhoneNumber': '4017834011', 'StreetAddress': '5586 POST RD UNIT 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'RI02', 'ORG_UEI_NUM': 'XL5ANMKWN557', 'ORG_LGL_BUS_NAME': 'GORDON RESEARCH CONFERENCES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Gordon Research Conferences', 'CityName': 'EAST GREENWICH', 'StateCode': 'RI', 'ZipCode': '028183454', 'StreetAddress': '5586 POST RD UNIT 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'RI02'}

{'Code': '152400', 'Text': 'Atmospheric Chemistry'}

2024~30480

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427028.xml'}

Functional characterization of the enzyme dipeptide interaction network and its role in the regulation of Arabidopsis carbon metabolism

NSF

03/01/2024

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'}

Metabolism drives the life-sustaining chemical reactions that provide energy and building blocks for plant growth and function. The goal of this project is to investigate how a class of small-molecule compounds called dipeptides control the activity of the central carbon metabolism of plants. This research may lead to innovation in the form of dipeptide-based strategies for improving plant fitness and perhaps generate knowledge that can be used in human and animal health. This project will provide research training for high school students, undergraduate students and post-doctoral associates.<br/><br/>Due to its rapid and reversible nature, small-molecule regulation of key enzymatic activities is vital to controlling metabolic fluxes. Systematic identification of regulatory metabolite-enzyme interactions remains one of the grand challenges in metabolism research. This research aims to systematically characterize the newly discovered enzyme-dipeptide interaction network and its role in regulating central carbon metabolism in the model plant Arabidopsis thaliana. To elucidate the metabolic consequences of the studied enzyme-dipeptide interactions, the research will exploit a combination of in vitro bimolecular binding assays, characterization of enzymatic activities, comprehensive metabolomic analysis of steady-state metabolite levels, and 13C metabolic flux analysis after dipeptide treatments. The results of these assays will be overlaid with dipeptide accumulation patterns to demonstrate the physiological relevance of the identified interactions. The basic knowledge accrued through this project will shed light on one of the central questions in biology: how organisms regulate their metabolism as they adapt to the environment. The research will characterize a hidden world of largely uninvestigated enzyme-dipeptide interactions, as well as their role in the critical yet poorly understood regulatory nexus of protein degradation and metabolism.<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.

05/07/2024

05/07/2024

None

Grant

47.074

1

4900

4900

2427055

{'FirstName': 'Aleksandra', 'LastName': 'Skirycz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aleksandra Skirycz', 'EmailAddress': 'skirycza@msu.edu', 'NSF_ID': '000847194', 'StartDate': '05/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': 'EAST LANSING, MI 488242600', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

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

2022~289171

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427055.xml'}

CAREER: Untangling Inter-Area Communication in the Brain Using Multi-Region Neural Networks

NSF

10/01/2023

08/31/2026

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Kenneth Whang', 'PO_EMAI': 'kwhang@nsf.gov', 'PO_PHON': '7032925149'}

Human and animal behaviors like learning, remembering, and deciding require the interactions of neurons and circuits across regions of the brain. However, despite the importance of these interactions, remarkably little is known about the processes regulating these brain-wide communications. This research builds computer models of the brain based on measurements taken from humans and animals performing behaviors, and uses those models to identify how different brain regions communicate and work together to produce behaviors. This work will identify shared and distinct features of brain-wide communication to guide new experimental studies and enable new computer models to better define brain functions. Additionally, this project promotes community engagement, diversity, and inclusion through two complementary programs: "Comp-ic Book Neuroscience," which brings research findings from computational neuroscience into under-served classrooms in New York City through the jargon-free and visually appealing medium of comics; and the Student Outreach for Neuroscience Integrated with CS (SONiC) program, an annual lab-based summer school to give NYC-area senior college and graduate students hands-on experience with visualizing and modeling brain data.<br/><br/>While rapid advances in neuroscience have catalyzed a deeper understanding of individual brain regions and their functions, these regions generally do not operate in isolation. Yet, little is known about processes regulating the brain-wide communication underlying many behavioral outputs. To reveal fundamental principles of brain-wide communication, this project will produce (1) a new, scalable, robust, and flexible class of multi-region recurrent-neural network (RNN) models with inter-area communication; and (2) analysis methods to infer the direction and magnitude of interactions within and between areas. Multi-region RNNs will be constrained with real neural data to uncover mechanisms of the real biological system, for instance, how the cooperative activity of neurons within and across brain regions gives rise to complex behaviors like decision-making. Reverse-engineering these models will reveal how multi-area brain circuits use biological plasticity to acquire a new skill. Finally, RNN modeling of human electrophysiology data will help identify inter-area communication processes that are conserved or divergent across multiple species. Wider adoption of the new models and tools will transform the understanding of how interacting brain areas function cohesively to orchestrate complex behaviors and inform future experimental paradigms. The research will also promote cross-fertilization between neuroscience and artificial intelligence/machine learning communities, and provide quantitative techniques shared in the broader neuroscience community. Furthermore, the project will foster an inclusive, welcoming environment for a diverse new generation of computational neuroscientists.<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.

05/08/2024

05/08/2024

None

Grant

47.070

1

4900

4900

2427124

{'FirstName': 'Kanaka', 'LastName': 'Rajan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kanaka Rajan', 'EmailAddress': 'kanaka.rajan@mssm.edu', 'NSF_ID': '000770941', 'StartDate': '05/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385366', 'PhoneNumber': '6174955501', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'LN53LCFJFL45', 'ORG_LGL_BUS_NAME': 'PRESIDENT AND FELLOWS OF HARVARD COLLEGE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Harvard University Medical School', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021156027', 'StreetAddress': '25 SHATTUCK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '749500', 'Text': 'Robust Intelligence'}

['2021~102265', '2022~249323']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427124.xml'}

Travel: NSF Student Travel Grant for The 2024 IEEE International Conference on Cluster Computing (Cluster 2024)

NSF

07/01/2024

06/30/2025

{'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': 'Almadena Chtchelkanova', 'PO_EMAI': 'achtchel@nsf.gov', 'PO_PHON': '7032927498'}

The IEEE International Conference on Cluster Computing (Cluster) serves as a major international forum for presenting and sharing recent accomplishments and technological developments in the field of cluster computing, as well as the use of cluster systems for scientific and commercial applications. Cluster 2024 involves participants (researchers, developers, and users) from academia, industry, laboratories, and commerce, coming together to discuss recent advances and trends. 2024 Cluster conference takes place on September 24-27, 2024 in Kobe, Japan. <br/><br/>The Student Program at Cluster provides a comprehensive means for students to improve their overall research skills. The attending students will participate in the regular conferences activities and a student program comprised of special sessions that target research presentation training, research experience and career guidance, and industry interaction. Funding provided through this grant will support the travel of eligible US students. Recipients will be able to attend the main conference, workshops, and tutorials. Travel grants will encourage the research interests and the involvement of students in the field who are not well funded and those who are just beginning their participation in the field or are interested in entering it. A special effort will be made to reach out to students from underrepresented groups. This grant will offer up to 15 – 20 NSF-sponsored student travel grants. The funding opportunity will be broadly announced, giving students ample notice and time to apply. An ad-hoc committee will review applications, and the support provided will cover student registration, travel and/or lodging expenses.<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.

06/14/2024

06/14/2024

None

Grant

47.070

1

4900

4900

2427192

{'FirstName': 'Weikuan', 'LastName': 'Yu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Weikuan Yu', 'EmailAddress': 'yuw@cs.fsu.edu', 'NSF_ID': '000492930', 'StartDate': '06/14/2024', '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': '779800', 'Text': 'Software & Hardware Foundation'}

2024~16000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427192.xml'}

GOALI: Development of Next Generation MXene-based Li-S Batteries with Practical Operating Temperatures

NSF

02/15/2024

09/30/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}

The workhorse of energy storage for transportation and personal electronics has been, and remains, the lithium-ion battery. And while that technology has proven to be quite robust and useful, one of its major drawbacks is the amount of energy they store. An alternate battery technology that has seen extensive research in the last decade is lithium-sulfur (Li-S) batteries. All else being equal and assuming some hurdles can be overcome, the Li-S battery would have 2-3 times the energy storage capacity of current lithium-ion batteries. It follows that if an electric car’s current range is 200 miles, its range if equipped with a Li-S battery would be 400-600 miles. Two important hurdles that need to be overcome for Li-S batteries are: the nature of the electrolyte between the electrodes and their rapid fade. In this project, the researchers, together with industry partners, will address both problems. Currently, most of the research in Li-S batteries make use of electrolytes (ether) that are highly volatile and pose safety risks when operated above room temperature. Moreover, additives to this electrolyte comes with serious transport regulations due to degassing safety concerns. In this project, the researchers will make use of the same electrolyte that is currently being used for Li-ion batteries, which has an excellent safety record and can be used at temperatures higher than room temperature. The second problem of the rapid fade in capacity with cycling is another challenge. To solve that problem the researchers will study new 2-dimensional materials (think sheets of paper at the atomic level) to immobilize the S, both physically and chemically, to prevent it from shuttling between the battery electrodes that leads to their fade. In terms of broader impact, the researchers, by partnering with a major battery company and an end-use heavy-duty automotive company, will ensure industrial relevance of the research. If successful, this technology could lead to longer lasting batteries, creating new jobs and ensuring that the United States becomes a major player in the energy storage field. Educational broader impact will be achieved by providing training and research opportunities for graduate students pursuing PhDs and undergraduates’ involvement in the research. <br/><br/>This fundamental GOALI project will address two key barriers for Li-S battery performance, an electrolyte that can operate at higher temperatures and mitigation of capacity loss due to polysulfide shuttling loss. The project will study a new class of materials to host sulfur, S-terminated MXenes. MXenes are two-dimensional (2D) carbides and/or nitrides discovered at Drexel in 2011 that exhibit metallic conductivity. Preliminary results have shown that MXenes are one of the few material platforms that allow both physical and chemical confinement/immobilization of S, thus reducing/minimizing the polysulfide shuttle effect. The MXenes’ metallic conductivity and “dual-immobilization” strategy will allow stable operation in carbonate electrolytes, while still enabling >70 wt.% S, with 7 mg/cm2 loadings and 83% effective S utilization (1400 mAh/g) – all necessary pre-requisites to approach the application targeted 500 Wh/kg. The cathode research on synthesis, fabrication, and study of redox activity of S-MXene cathodes will be integrated with carbonate electrolyte engineering to further suppress possible adverse polysulfide-carbonate reactions by reducing the electrophilicity. Post-mortem and in-operando spectroscopic and microscopic studies will be conducted to elucidate the quasi-solid-state redox pathways in S-terminated MXene hosts, detect the presence of polysulfides, or other undesired side products, from S-carbonate interactions. Cell-level Newman-type modeling, identifying limiting phenomena will further guide material design. The ultimate objective of this GOALI project - in collaboration with industry partners - is to develop Li-S batteries with practical S-loadings and S-utilizations that stably operate in high boiling point commercial carbonate electrolytes for application in heavy-duty battery electric vehicles.<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.

04/15/2024

05/08/2024

None

Grant

47.041

1

4900

4900

2427203

{'FirstName': 'Vibha', 'LastName': 'Kalra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Vibha Kalra', 'EmailAddress': 'vk69@cornell.edu', 'NSF_ID': '000560367', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'StateCode': 'NY', 'ZipCode': '148502820', 'StreetAddress': '341 PINE TREE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}

[{'Code': '164200', 'Text': 'Special Initiatives'}, {'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}]

2022~321634

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427203.xml'}

CAREER: Adapting the Fluid Projection Method to Model Elasto-plastic Materials

NSF

04/15/2024

06/30/2024

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Yuliya Gorb', 'PO_EMAI': 'ygorb@nsf.gov', 'PO_PHON': '7032922113'}

There are two main ways that materials deform under an applied force. The deformation can be elastic, so that when the force is removed the material recovers its original shape. Alternatively, the deformation can be plastic, whereby the material undergoes irreversible changes that may subsequently lead to breakage. Many materials of technological importance exhibit a combination of these two types of deformation depending on the applied force, and are called elasto-plastic. One example are bulk metallic glasses (BMGs), which are alloys that have an amorphous atomic arrangement in contrast to most metals. BMGs have desirable properties, such as the ability to be processed like plastics, making them attractive candidates for many applications (e.g. next-generation smartphone cases) due to considerable improvements in manufacturing efficiency. However, experimental measurements of BMG breakage properties show wide variations, limiting their usage. To overcome these limitations, it is essential to develop predictive theoretical and computational models of BMG elasto-plasticity. This project is based on a surprising similarity between the equations for elasto-plastic materials and the equations for incompressible fluids. Using this similarity, computational approaches that were originally developed for fluid flow will be translated to elasto-plasticity. These computational methods will be used in collaboration with theorists and experimentalists to study the fracture properties of BMGs. The ultimate aim is to provide a practical engineering tool for predicting when elasto-plastic materials will break, and how to best design structures using them. This work will be undertaken as part of an integrated program of research, teaching, and mentorship, and will involve outreach activities in New England, including a local library lecture series.<br/><br/>The projection method of Chorin (1968) is a well-established approach for simulating the incompressible Navier-Stokes equations for fluid flow. This proposal is based on a surprising mathematical correspondence between fluids in the incompressible limit and elasto-plastic solids in the quasi-static limit (when inertia can be neglected). In this proposal, this correspondence is harnessed to translate several modern numerical approaches derived from Chorin's projection method to quasi-static elasto-plasticity, resulting in a practical and powerful set of new simulation tools for a different class of physical problem. Compared to existing techniques, the resultant numerical methods are likely to be especially well-suited to problems involving large plastic deformations. An example type of elasto-plastic material are the bulk metallic glasses (BMGs), which are alloys with many favorable properties such as excellent strength and wear resistance. The numerical methods developed here will be used in a collaboration with theorists and experimentalists to study the fracture toughness properties of BMGs, with the aim of predicting BMG toughness over a wide range of experimental conditions. The PI plans to expand the graduate curriculum in numerical methods to address a pressing need in this area. Open source software will be released as part of this project, and the PI will train students in best practices to make software accessible to a broad 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.

04/16/2024

04/16/2024

None

Grant

47.049

1

4900

4900

2427204

{'FirstName': 'Christopher', 'LastName': 'Rycroft', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': 'Mr', 'PI_FULL_NAME': 'Christopher H Rycroft', 'EmailAddress': 'rycroft@wisc.edu', 'NSF_ID': '000656194', 'StartDate': '04/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}

{'Code': '127100', 'Text': 'COMPUTATIONAL MATHEMATICS'}

2022~23580

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427204.xml'}

PFI-TT: Scalable Thermal Spray Deposition of Surface-Engineered Washcoat Catalysts for Vehicle Emission Control Systems

NSF

03/01/2024

09/30/2024

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Samir M. Iqbal', 'PO_EMAI': 'smiqbal@nsf.gov', 'PO_PHON': '7032927529'}

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to develop an emission control prototype product with novel, surface-engineered catalysts for exhaust abatement. Clean air represents a significant societal benefit. Various mobile and stationary emission control systems are included in current solutions to reduce adverse environmental and health impacts. The adoption of support-promoted and surface-engineered catalysts with low temperature activity can have a global impact for the industrial applications in automotive catalytic converters and many industrial operations including electrical power plants, refineries and chemical plants, and surface coating facilities. Personnel involved in this project includes one graduate student and undergraduate students, who will gain innovation, technology transfer, and entrepreneurship experience. <br/><br/>This project combines a continuous thermal spray inline coating technology with surface-engineered catalytic washcoat materials to enable a 90% pollutant emission conversion rate below 150 C in automotive catalytic converters. Current emission control catalysts are relatively ineffective during the cold start period because the cold start temperature is lower than the light-off temperature of catalysts, leading to significant levels of pollutants emitted into the ambient air. By tuning the shapes and surface defects of cerium oxide (CeO2) supports and activating the metal-support interface, the surface-engineered catalysts offer low energy barriers for the formation of key intermediates and open reaction pathways as well as an increase in active sites for pollutant gas conversion at lower temperature. This project will apply the advantages of the continuous thermal spray technology to provide rapid, scalable production with high precision and controlled coating thickness, significantly reduced waste relative to conventional wet-chemical batch processes, reduction or elimination of harmful organic solvents, and fully integrated one-step production.<br/><br/>This project is jointly funded by Partnerships for Innovation (PFI) 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.

06/11/2024

06/11/2024

None

Grant

47.041, 47.083, 47.084

1

4900

4900

2427213

{'FirstName': 'Ruigang', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruigang Wang', 'EmailAddress': 'rwang@msu.edu', 'NSF_ID': '000587825', 'StartDate': '06/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': 'EAST LANSING, MI 488242600', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

[{'Code': '166200', 'Text': 'PFI-Partnrships for Innovation'}, {'Code': '915000', 'Text': 'EPSCoR Co-Funding'}]

['2021~8208', '2022~14000']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427213.xml'}

CAS-Climate: Understanding the fundamental redox chemistry and transport of chloroaluminate anions in ionic liquid electrolytes to develop earth-abundant aluminum ion battery

NSF

03/01/2024

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': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}

Rechargeable batteries are powering the rise in plug-in electric vehicles and intermittent renewable energy storage/transport/utilization in the electric grid. With double-digit annual growth expected over the next decade for production and sales of electric vehicles, cost of materials, resource availability, and supply chain will become increasingly critical factors in novel and sustainable battery technologies. In this regard, aluminum ion batteries hold great promise for large-scale energy storage applications based on their fast-charging capability, earth-abundant resources, and lower cost of raw materials. The overall objective of this project is to 1) develop novel chloroaluminate ionic liquid electrolytes with low-viscosity and highly conductive additives, and 2) elucidate microscopic conversion chemistry, transport, charge storage mechanism, and stability challenges of chloroaluminate anions in aluminum ion batteries. Such knowledge is critical to enhance the commercialization potential of earth-abundant, safer, and long-life aluminum ion batteries. This project strives to increase participation of underrepresented undergraduate and graduate students in science and engineering research in rural west Alabama. The educational benefits of the project include graduate and undergraduate researcher training in electroanalytical chemistry, materials science, battery science and engineering, microfabrication, and cell design.<br/><br/>The project’s aim is to systematically explore the effects of ionic liquid electrolyte compositions and surface engineered graphene foam electrodes on the chloroaluminate anions adsorption, conversion, intercalation, and mass transport, which will provide a fundamental understanding of effective conversion and intercalation/deintercalation chemistry of chloroaluminate anions species in aluminum ion batteries. New insights, including quantitative molecular or atomic-level structural, chemical, spectroscopic, and electrochemical characterizations, into graphene/ionic liquid electrolyte interfacial structures will provide powerful practical strategies to promote or suppress various kinds of interface phenomena. The outcome and knowledge gained from such studies will guide the design and fabrication of novel ionic liquid electrolytes and graphene-based electrodes for superior energy storage density and cycling performance of aluminum ion batteries. Such knowledge is critically needed for designing long-life electrolytes/electrodes and low-cost energy storage systems.<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.

04/15/2024

04/15/2024

None

Grant

47.041

1

4900

4900

2427215

{'FirstName': 'Ruigang', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruigang Wang', 'EmailAddress': 'rwang@msu.edu', 'NSF_ID': '000587825', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM ROAD, ROOM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

{'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}

2022~330743

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427215.xml'}

Computations in Classical and Motivic Stable Homotopy Theory

NSF

04/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Swatee Naik', 'PO_EMAI': 'snaik@nsf.gov', 'PO_PHON': '7032924876'}

Algebraic topology is a field of mathematics that involves using algebra and category theory to study properties of geometric objects that do not change when those objects are deformed. A central challenge is to classify all maps from spheres to other spheres, where two maps are considered equivalent if one can be deformed to the other. The equivalence classes of these maps are called the homotopy groups of spheres, and collectively they form one of the deepest and most central objects in the field. Historically, much important theory has arisen out of attempts to compute more homotopy groups of spheres and understand patterns within them. This project involves furthering knowledge of the homotopy groups of spheres, using old and new techniques as well as computer calculations. The project also involves studying an analogue of these groups in algebraic geometry; this falls under a relatively new and actively developed area called motivic homotopy theory, which applies techniques in algebraic topology to study algebraic geometry. The broader impacts of this project center around supporting the local mathematics community through mentoring and promoting diversity. The principal investigator will help build the nascent homotopy theory community at the university and promote women and minorities in the subject through seminar organization and mentoring.<br/> <br/>One of the main planned projects is a large-scale effort to compute the homotopy groups of spheres at the prime 3 in a range, using old and new techniques such as the Adams-Novikov spectral sequence as well as infinite descent machinery. This work will be aided by computer calculations, which short-circuits some of the technical difficulties encountered in previous attempts. Another main group of projects concerns computing the analogue of the stable homotopy groups of spheres in the world of R-motivic homotopy theory. This represents a continuation of prior work of the PI and collaborator; the plan is to supplement the techniques used in that work with computer calculations and a new tool, the slice spectral sequence. A third project concerns theory and spectral sequence computations aimed at computing the cohomology of profinite groups such as special linear groups and Morava stabilizer groups.<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.

04/09/2024

04/09/2024

None

Grant

47.049

1

4900

4900

2427220

{'FirstName': 'Eva', 'LastName': 'Belmont', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eva K Belmont', 'EmailAddress': 'eva.belmont@case.edu', 'NSF_ID': '000759142', 'StartDate': '04/09/2024', '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': '126700', 'Text': 'TOPOLOGY'}

2022~106619

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427220.xml'}

RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

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

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

This Rapid Response Research (RAPID) grant project supports research dedicated to a comprehensive and in-depth collection of data to analyze the extensive societal consequences following the Francis Scott Key Bridge collapse in Baltimore, Maryland. This bridge, being a part of the I-695 beltway, lacks convenient detour options. Thus, its collapse leads widespread disruptions in mobility that affected not just the immediate vicinity but also resonated throughout the broader DC-Maryland-Virginia region. The objective of this project is to methodically gather time-sensitive data on traffic flow and community responses in the wake of this event, providing a detailed assessment of its repercussions. Moreover, this incident also brings a major disruption to freight transportation and supply chains on the East Coast. Given the reliance of freight models on occasionally collected, often proprietary data from commodities surveys, state reports, and customs statistics, this study aims to fill these gaps through an integrated approach for critical trucking, maritime, rail, and supply-chain data collection. These efforts are essential for enhancing the resilience of transportation networks and supply chains against future disruptions. For a broader audience, all the collected data will be made publicly available while carefully following rules for privacy protection and existing data usage agreements. Through sharing detailed findings and facilitating a broader understanding of the incident’s impacts, this project aspires to foster a more informed and prepared society, capable of effectively navigating the challenges posed by major infrastructural failures and their far-reaching impacts on communities and economies.<br/><br/>The catastrophic collapse of the Francis Scott Key Bridge in Baltimore, Maryland, has precipitated significant disruptions across urban transportation networks, due to the lack of convenient alternative routes, affecting daily commutes for an estimated 34,000 individuals. Moreover, the collapse introduced considerable logistical difficulties, particularly in the Port of Baltimore, a critical national and international trade node. Research completed for this project aims to develop a comprehensive data collection methodology, incorporating data integration and enhancement through existing data platforms (e.g., augmentations in commuting, trucking, rail, and marine traffic data alongside social media analytics), comprehensive surveys (e.g., examining travel behavior, community impact, and economic repercussions), and targeted interviews (e.g., exploring governmental responses and adaptations within the logistics network). Should initial analyses indicate a necessity, the spatial and temporal scope of data collection may be expanded to evaluate the impact of the bridge collapse comprehensively. This project is dedicated to improving data transparency and utility, employing elaborate documentation and a diversified strategy for data dissemination, including the development of a dedicated project website, utilization of the NSF NHERI Data Depot for data storage and dissemination, conducting workshops to engage a wide array of stakeholders, and presenting the data architecture at major transportation, infrastructure systems, and disaster conferences.<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.

04/11/2024

04/11/2024

None

Grant

47.041

1

4900

4900

2427231

[{'FirstName': 'Gang-Len', 'LastName': 'Chang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gang-Len Chang', 'EmailAddress': 'gang@umd.edu', 'NSF_ID': '0000A03QG', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xianfeng', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xianfeng Yang', 'EmailAddress': 'xtyang@umd.edu', 'NSF_ID': '000715027', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}

[{'Code': '006Y00', 'Text': 'OE Operations Engineering'}, {'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}, {'Code': '163800', 'Text': 'HDBE-Humans, Disasters, and th'}]

2024~82500

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427231.xml'}

RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

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

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

This Rapid Response Research (RAPID) grant project is dedicated to a comprehensive and in-depth collection of data to analyze the extensive societal consequences following the Francis Scott Key Bridge collapse in Baltimore, Maryland. This bridge, being a part of the I-695 beltway, lacks convenient detour options. Thus, its collapse leads widespread disruptions in mobility that affected not just the immediate vicinity but also resonated throughout the broader DC-Maryland-Virginia region. The objective of this project is to methodically gather time-sensitive data on traffic flow and community responses in the wake of this event, providing a detailed assessment of its repercussions. Moreover, this incident also brings a major disruption to freight transportation and supply chains on the East Coast. Given the reliance of freight models on occasionally collected, often proprietary data from commodities surveys, state reports, and customs statistics, this study aims to fill these gaps through an integrated approach for critical trucking, maritime, rail, and supply-chain data collection. These efforts are essential for enhancing the resilience of transportation networks and supply chains against future disruptions. For a broader audience, all the collected data will be made publicly available while carefully following rules for privacy protection and existing data usage agreements. Through sharing detailed findings and facilitating a broader understanding of the incident’s impacts, this project aspires to foster a more informed and prepared society, capable of effectively navigating the challenges posed by major infrastructural failures and their far-reaching impacts on communities and economies.<br/><br/>The catastrophic collapse of the Francis Scott Key Bridge in Baltimore, Maryland, has precipitated significant disruptions across urban transportation networks, due to the lack of convenient alternative routes, affecting daily commutes for an estimated 34,000 individuals. Moreover, the collapse introduced considerable logistical difficulties, particularly in the Port of Baltimore, a critical national and international trade node. This project aims to develop a comprehensive data collection methodology, incorporating data integration and enhancement through existing data platforms (e.g., augmentations in commuting, trucking, rail, and marine traffic data alongside social media analytics), comprehensive surveys (e.g., examining travel behavior, community impact, and economic repercussions), and targeted interviews (e.g., exploring governmental responses and adaptations within the logistics network). Should initial analyses indicate a necessity, the spatial and temporal scope of data collection may be expanded to evaluate the impact of the bridge collapse comprehensively. This project is dedicated to improving data transparency and utility, employing elaborate documentation and a diversified strategy for data dissemination, including the development of a dedicated project website, utilization of the NSF NHERI Data Depot for data storage and dissemination, conducting workshops to engage a wide array of stakeholders, and presenting the data architecture at major transportation, infrastructure systems, and disaster conferences.<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.

04/11/2024

04/11/2024

None

Grant

47.041

1

4900

4900

2427232

[{'FirstName': 'Mansoureh', 'LastName': 'Jeihani', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mansoureh Jeihani', 'EmailAddress': 'Mansoureh.Jeihani@morgan.edu', 'NSF_ID': '000588874', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Di', 'LastName': 'Yang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Di Yang', 'EmailAddress': 'di.yang@morgan.edu', 'NSF_ID': '000922446', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Morgan State University', 'CityName': 'BALTIMORE', 'ZipCode': '212510001', 'PhoneNumber': '4438853200', 'StreetAddress': '1700 E COLD SPRING LN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'KULSKCCZJT27', 'ORG_LGL_BUS_NAME': 'MORGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'KULSKCCZJT27'}

{'Name': 'Morgan State University', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212510001', 'StreetAddress': '1700 E COLD SPRING LN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}

[{'Code': '006Y00', 'Text': 'OE Operations Engineering'}, {'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}, {'Code': '163800', 'Text': 'HDBE-Humans, Disasters, and th'}]

2024~35000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427232.xml'}

RAPID: Collaborative Research: Multifaceted Data Collection on the Aftermath of the March 26, 2024 Francis Scott Key Bridge Collapse in the DC-Maryland-Virginia Area

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

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

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

This Rapid Response Research (RAPID) grant project is dedicated to a comprehensive and in-depth collection of data to analyze the extensive societal consequences following the Francis Scott Key Bridge collapse in Baltimore, Maryland. This bridge, being a part of the I-695 beltway, lacks convenient detour options. Thus, its collapse leads widespread disruptions in mobility that affected not just the immediate vicinity but also resonated throughout the broader DC-Maryland-Virginia region. The objective of this project is to methodically gather time-sensitive data on traffic flow and community responses in the wake of this event, providing a detailed assessment of its repercussions. Moreover, this incident also brings a major disruption to freight transportation and supply chains on the East Coast. Given the reliance of freight models on occasionally collected, often proprietary data from commodities surveys, state reports, and customs statistics, this study aims to fill these gaps through an integrated approach for critical trucking, maritime, rail, and supply-chain data collection. These efforts are essential for enhancing the resilience of transportation networks and supply chains against future disruptions. For a broader audience, all the collected data will be made publicly available while carefully following rules for privacy protection and existing data usage agreements. Through sharing detailed findings and facilitating a broader understanding of the incident’s impacts, this project aspires to foster a more informed and prepared society, capable of effectively navigating the challenges posed by major infrastructural failures and their far-reaching impacts on communities and economies.<br/><br/>The catastrophic collapse of the Francis Scott Key Bridge in Baltimore, Maryland, has precipitated significant disruptions across urban transportation networks, due to the lack of convenient alternative routes, affecting daily commutes for an estimated 34,000 individuals. Moreover, the collapse introduced considerable logistical difficulties, particularly in the Port of Baltimore, a critical national and international trade node. This project aims to develop a comprehensive data collection methodology, incorporating data integration and enhancement through existing data platforms (e.g., augmentations in commuting, trucking, rail, and marine traffic data alongside social media analytics), comprehensive surveys (e.g., examining travel behavior, community impact, and economic repercussions), and targeted interviews (e.g., exploring governmental responses and adaptations within the logistics network). Should initial analyses indicate a necessity, the spatial and temporal scope of data collection may be expanded to evaluate the impact of the bridge collapse comprehensively. This project is dedicated to improving data transparency and utility, employing elaborate documentation and a diversified strategy for data dissemination, including the development of a dedicated project website, utilization of the NSF NHERI Data Depot for data storage and dissemination, conducting workshops to engage a wide array of stakeholders, and presenting the data architecture at major transportation, infrastructure systems, and disaster conferences.<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.

04/11/2024

04/11/2024

None

Grant

47.041

1

4900

4900

2427233

{'FirstName': 'Shanjiang', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shanjiang Zhu', 'EmailAddress': 'szhu3@gmu.edu', 'NSF_ID': '000644454', 'StartDate': '04/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}

[{'Code': '006Y00', 'Text': 'OE Operations Engineering'}, {'Code': '163100', 'Text': 'CIS-Civil Infrastructure Syst'}, {'Code': '163800', 'Text': 'HDBE-Humans, Disasters, and th'}]

2024~82484

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427233.xml'}

EAGER: ANT LIA: Persist or Perish: Records of Microbial Survival and Long-term Persistence from the West Antarctic Ice Sheet

NSF

02/15/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '06090300', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OPP', 'LongName': 'Office of Polar Programs (OPP)'}}

{'SignBlockName': 'William Ambrose', 'PO_EMAI': 'wambrose@nsf.gov', 'PO_PHON': '7032928048'}

Ice cores from glaciers and ice sheets provide detailed archives of past environmental conditions, furthering our understanding of Earth’s climate. Microorganisms in the West Antarctic Ice Sheet are buried over glaciological time and form a stratigraphy record providing the opportunity of analysis of the order and position of layers of geological events, with potential links to Southern Hemisphere climate. However, microbial cells that land on the ice sheet are subject to the stresses of changing habitat conditions due to burial and conditions associated with long-term isolation in ice. These processes may lead to a loss of fidelity within the stratigraphic record of microbial cells. We know little about how and if microorganisms survive burial and remain alive over glacial-interglacial time periods within an ice sheet. This analysis will identify the viable and preserved community of microorganisms and core genomic adaptation that permit cell viability, which will advance knowledge in the areas of microbiology and glaciology while increasing fidelity of ice core measurements relevant to past climate and potential future global climate impacts. This exploratory endeavor has the potential to be a transformative step toward understanding the ecology of one of the most understudied environments on Earth. The project will partner with the Museum of Science, Boston, to increase public scientific literacy via education and outreach. Additionally, this project will support two early-career scientists and two undergraduates in interdisciplinary research at the intersection of microbiology and climate science. <br/><br/>Results from this project will provide the first DNA data based on single-cell whole genomic sequencing from the Antarctic Ice Sheet and inform whether post-depositional processes impact the interpretations of paleoenvironmental conditions from microbes. The goals to determine the taxonomic identity of viable and preserved microbial cells, and decode the genetic repertoire that confers survival of burial and long-term viability within glacial ice, will be achieved by utilizing subsamples from a ~60,000 year old record of the West Antarctic Ice Sheet Divide (WD) Ice Core. WD samples will be melted using the Desert Research Institute’s ice core melting system that is optimized for glaciobiological sampling. Microbial cells from the meltwater will be sorted using fluorescence-activated cell sorting, and individually sorted cells will have their genomes sequenced. The fluorescence-based methods will discern the viable (metabolically active) cells from those cells that are non-viable but preserved in the ice (DNA-containing). The genomic analysis will identify the taxonomy of each cell, presence of known genes that confer survival in permanently frozen environments, and comparatively analyze genomes to determine the core set of genes required by viable cells to persist in an ice sheet. The outcomes of this work will expand the potential for biological measurements and contamination control from archived ice cores.<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.

04/17/2024

04/17/2024

None

Grant

47.078

1

4900

4900

2427241

{'FirstName': 'Alexander', 'LastName': 'Michaud', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alexander B Michaud', 'EmailAddress': 'amichaud@bigelow.org', 'NSF_ID': '000708413', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}

[{'Code': '511100', 'Text': 'ANT Organisms & Ecosystems'}, {'Code': '511600', 'Text': 'ANT Glaciology'}, {'Code': '529200', 'Text': 'ANT Integrated System Science'}]

2022~152502

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427241.xml'}

Surface Engineered and Highly Redox Active Polar Oxide Host Materials Immobilizing Lithium Polysulfides for Long-Life and High-Performance Li-S Batteries

NSF

03/01/2024

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': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}

Electrical energy storage is one of the most critical needs in power systems for a more sustainable future. Lithium–sulfur (Li-S) batteries are promising candidates because of their higher energy density and reduced cost due to the use of sulfur. However, a key limitation of the Li-S system is polysulfide shuttling. Shuttling occurs when polysulfide molecules from the cathode dissolve into the electrolyte and shuttle across the separator to react with the anode materials. This process is irreversible and leads to a rapidly fading capacity. This project addresses the fundamental shuttle effect of lithium polysulfides in lithium sulfur batteries with emphasis on developing surface engineered host materials for immobilizing lithium polysulfides and promoting their conversion. A series of surface engineered and shape-controlled cerium oxides will be developed and characterized to understand which structural features best limit polysulfide shutting. Such knowledge is critical for designing novel host materials and long-life energy storage systems, which will have a potentially immense impact on portable electronics, electric vehicles, and devices for intermittent renewable energy storage from solar and wind resources. The investigator will continue to support the outstanding recruitment, mentoring, and retention of minority students in STEM by providing unique research opportunities for undergraduates as early as their freshman year and with continuing scholarships to promote their retention.<br/><br/>The overall objective of this proposal is to elucidate the effect of surface engineered polar CeO2 addition as a host material via shape control (nanorods, nanocubes, and nanoctahedra with different exposed crystal planes: (110), (100) and (111)) and chemical etching treatment on the lithium polysulfides immobilization, catalytic conversion, and electrochemical performance in lithium-sulfur batteries. These findings will provide insight into a fundamental understanding of sulfur conversion chemistry and act as a guide for the future design and screening of new host materials toward achieving high sulfur loading/utilization in lithium-sulfur batteries. The investigators hypothesize that physical confinement and surface engineered polar CeO2 with distinct termination surface structures would effectively store and entrap sulfur species to prevent the dissolution and migration of intermediate lithium polysulfides avoiding the shuttle effect and capacity degradation during the electrochemical cycling. In addition, ex situ/in situ transmission electron microscopy and electron energy loss spectroscopy characterization techniques will be employed to achieve a deeper understanding of dynamic adsorption/desorption, liquid/solid and solid/solid interactions, and structural/compositional changes at the lithium polysulfides/CeO2 interface. New insights (quantitative dynamic atomic-level structural and chemical characterizations) into lithium polysulfides/CeO2 interfacial structures will provide powerful practical strategies to promote or suppress various kinds of interface phenomena. The obtained knowledge on battery chemistry of sulfur-oxide additive interaction promises long-life and high energy/power density lithium-sulfur batteries.<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.

04/15/2024

04/15/2024

None

Grant

47.041

1

4900

4900

2427263

{'FirstName': 'Ruigang', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruigang Wang', 'EmailAddress': 'rwang@msu.edu', 'NSF_ID': '000587825', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 Auditorium Rd Rm 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

{'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}

2021~296729

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427263.xml'}

Collaborative Research: Bridging the scale gap between local and regional methane and carbon dioxide isotopic fluxes in the Arctic

NSF

03/15/2024

12/31/2024

{'Value': 'Continuing Grant'}

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

{'SignBlockName': 'Roberto Delgado', 'PO_EMAI': 'robdelga@nsf.gov', 'PO_PHON': '7032922397'}

Northern latitudes are warming at twice the global mean, making carbon stored in permafrost increasingly vulnerable to thaw and decomposition by microbes, potentially leading to large increases in methane (CH4) and carbon dioxide (CO2) emissions, both important greenhouse gases. Accurate and reliable forecasts of greenhouse gas emissions are critical for the improvement of global models that predict changes to temperature and to sea level. On a local level, the data and modeling products can be used to better inform local populations of the changes happening to their environment and help predict likely changes in the future. Improvements to regional and global scale models require advancement in the current knowledge of methane and carbon dioxide flux sources to gain insight into how the net flux is expected to respond to a warming Arctic. Comparing aircraft derived fluxes to local tower measurements and land classification maps allows for the determination of which mechanisms are primarily responsible for the variation in emissions. Data, models, and analysis directly measuring the fluxes over regional scales close to the surface and measuring fluxes using inverse modeling helps to better understand the differences. Data generated from this project are important for evaluating which combination of environmental quantities and categorical quantities are best suited for predicting methane and carbon dioxide emissions to produce more accurate estimates from remotely sensed variables and will also be compared with existing carbon emissions models. The ability to define the current late summer and autumn net flux of methane and carbon dioxide from the North Slope and adjoining Arctic waters is required to establish a benchmark for quantitatively tracking the annual time series of net carbon flux from the Arctic.<br/><br/>This research provides emission measurements of CO2 and CH4 plus nitrous oxide (N2O), and water vapor (H2O) from the North Slope of Alaska on a small aircraft operating at altitudes from 10 m to 10 km, with custom-built spectroscopic sensors, an air turbulence probe, and GPS systems. This project bridges the scale gap between local studies of carbon emissions in the Arctic, such as those from flux towers, and large regional scale emissions estimates from inversion modeling. The work provides resolved emissions correlated with underlying sources; regional coverage for comprehensive analysis of carbon emissions in this part of the Arctic basin; direct coupling of the observations with other observing systems ranging from small tower measurements to satellite remote sensing; and coupling of the observations to an air transport model to compare direct emission measurements to top-down estimates of regional emissions based on profile measurements in the atmosphere. Specifically, aircraft eddy covariance measurements and vertical profiles are used to effectively scale process measurements from short eddy covariance towers to the regional scale, allowing for determining how representative certain areas are of the larger North Slope with respect to flux of the major gases that contribute to changes in radiative forcing. Observations and modeling of fluxes and concentrations of molecules that differ in their isotopic composition reveal the contributions of key source processes at local, landscape, and regional scale, a feature unique to this project. This project creates an analysis framework to allow for the combination of in situ concentrations and fluxes with regional fluxes calculated using a transport model that both is adapted for Alaska and widely applicable to other circumpolar areas.<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.

04/16/2024

04/16/2024

None

Grant

47.078

1

4900

4900

2427291

{'FirstName': 'James', 'LastName': 'Anderson', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James G Anderson', 'EmailAddress': 'anderson@huarp.harvard.edu', 'NSF_ID': '000429386', 'StartDate': '04/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385366', 'PhoneNumber': '6174955501', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'LN53LCFJFL45', 'ORG_LGL_BUS_NAME': 'PRESIDENT AND FELLOWS OF HARVARD COLLEGE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385366', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}

{'Code': '529300', 'Text': 'AON-Arctic Observing Network'}

['2020~1', '2021~1', '2022~805623']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427291.xml'}

Collaborative Research: SHF: Small: Artificial Intelligence of Things (AIoT): Theory, Architecture, and Algorithms

NSF

12/15/2023

09/30/2025

{'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': 'Almadena Chtchelkanova', 'PO_EMAI': 'achtchel@nsf.gov', 'PO_PHON': '7032927498'}

The fusion of AI and IoT creates Artificial-Intelligence-of-Things (AIoT), which is expected to not only boost the intelligence on end devices, but also unleash the power of IoT data better and faster. Given the presence of confidential and distributed IoT data in many fields, federated learning has been one promising approach to unlock the potential of AIoT by enabling collaborative intelligence without migrating private end-device data to a central server. However, the heavy burden of state-of-the-art AI on storage and computing resources stands at odds with most IoT hardware platforms that are resource-constrained, which raises daunting challenges when deploying federated intelligence in AIoT. The research team explores hardware-efficient AI techniques to support federated knowledge transfer across diverse IoT hardware platforms to expand the scope of AIoT from theory, architecture, and algorithm perspectives. The proposed research brings tangible benefits to a broad range of disciplines that employ AI and IoT technologies, promoting the fusion of AI and IoT. The project provides training opportunities for undergraduate and graduate students from underrepresented groups. The outreach efforts on AIoT topics and research findings are directed towards K-12 audiences. <br/><br/>This project provides the theoretical and empirical evidence to facilitate the deployment of hardware-efficient AI techniques in federated IoT environments, which fills a critical void - the existing approaches fail to address the widespread resource, efficiency, and privacy challenges in AIoT. This project consists of four aspects: (1) enabling hardware-efficient AI from microscope operations, neural quantization, to theoretically guide specialized quantization for federated intelligence across various IoT hardware platforms, (2) exploring another ground-breaking hardware-efficient AI technique, neural architecture pruning, to seek optimal sub-network architectures in a data-agnostic manner, (3) identifying new privacy vulnerabilities and developing defensive mechanisms for the AIoT designs to encourage broad participation, (4) establishing a general-purpose AIoT testbed. Through the architecture-algorithm-hardware co-design, the research intends to unleash the utmost potential of various IoT hardware platforms and federated intelligence to expand the scope of AIoT 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.

04/19/2024

04/19/2024

None

Grant

47.070

1

4900

4900

2427316

{'FirstName': 'Xiaoyong', 'LastName': 'Yuan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaoyong Yuan', 'EmailAddress': 'xyyuan@mtu.edu', 'NSF_ID': '000826560', 'StartDate': '04/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'ZipCode': '296340001', 'PhoneNumber': '8646562424', 'StreetAddress': '201 SIKES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'SC03', 'ORG_UEI_NUM': 'H2BMNX7DSKU8', 'ORG_LGL_BUS_NAME': 'CLEMSON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'StateCode': 'SC', 'ZipCode': '296340001', 'StreetAddress': '201 SIKES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'SC03'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

2022~386682

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427316.xml'}

I-Corps: Translation potential of metallic nanoparticles that can replace precious metal nanoparticles for catalytic applications

NSF

06/15/2024

11/30/2024

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Ruth Shuman', 'PO_EMAI': 'rshuman@nsf.gov', 'PO_PHON': '7032922160'}

The broader impact of this I-Corps project is the development of metallic nanoparticles that can replace precious metal nanoparticles for catalytic applications. Precious metal nanoparticles, such as platinum (Pt) nanoparticles, are currently used as catalysts in the energy industries even though they are expensive. This technology is designed to produce multi-metallic nanoparticles with the aim to replace or reduce noble metals used in the energy sector. The business hypothesis is that the multi-metallic nanoparticles will serve as better catalysts and electrodes than the presently used Pt nanoparticles and help energy industries such as oil and gas, fuel cells, and hydrogen production to improve cost-effectiveness, process efficiency, and reliability.<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 a laser-based technique that enables the ultrafast fabrication of a variety of multi-metallic nanoparticles. This nanosecond laser-processing technology enables the creation of multi-metallic nanoparticles of different sizes, shapes, and compositions covering a large dimensional and compositional space. The technology is based on the rapid shriveling of thin films into nanoparticles through the laser-induced melt-phase dewetting phenomenon, which subsequently accumulates in a droplet shape via thermally-driven mass transport and surface energy minimization. The approach has been tested to manufacture several monometallic noble metal (platinum, gold, and silver), non-noble metal (nickel and cobalt), bimetallic (silver-cobalt, gold-nickel, gold-cobalt, and copper-nickel), and multi-element alloy (nickel-cobalt-chromium and nickel-cobalt-chromium-iron-copper) nanoparticles. The technology produces nanoparticles that exhibit high-quality, contamination/oxidation-free characteristics that may be tailored for intended applications including improved functional properties such as shelf-life, stability, and catalytic activity.<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.

06/04/2024

06/04/2024

None

Grant

47.084

1

4900

4900

2427339

{'FirstName': 'Ritesh', 'LastName': 'Sachan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ritesh Sachan', 'EmailAddress': 'rsachan@okstate.edu', 'NSF_ID': '000813172', 'StartDate': '06/04/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'ZipCode': '740781031', 'PhoneNumber': '4057449995', 'StreetAddress': '401 WHITEHURST HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OK03', 'ORG_UEI_NUM': 'NNYDFK5FTSX9', 'ORG_LGL_BUS_NAME': 'OKLAHOMA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'StateCode': 'OK', 'ZipCode': '740781031', 'StreetAddress': '401 WHITEHURST HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OK03'}

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

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427339.xml'}

RAPID: Unraveling rates of wind erosion and potential dust emission post Smokehouse Creek Fire in Texas

NSF

06/01/2024

05/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': 'jlawrenc@nsf.gov', 'PO_PHON': '7032922425'}

This project will characterize properties of burned surface soils along a gradient of grazing intensity and conduct temporal monitoring of wind erosion rates and dust emission after the Smokehouse Creek Fire in the Texas Panhandle region. This wildfire is the largest fire ever recorded in the state’s history and burned more than 1 million acres. Previous research has shown that wildfires can trigger significant rates of soil erosion. This research project responds to the urgent need to capture the first flush of eroded materials. Erosion, redistribution, and deposition of soil resources are intimately connected to landscape recovery. Collaboration and partnership with federal agencies, including the USDA and NRCS, will aid in designing long-term management of these rangelands in the region. The project will provide training opportunity to two undergraduate students at a Hispanic Serving Institution.<br/><br/>Rangelands in arid and semi-arid regions are susceptible to enhanced rates of aeolian erosion following a wildfire. However, the impacts of wildfire extend beyond wind erosion and dust emission as vegetation recovery in these rangelands could be dependent on history of land-use and antecedent vegetation type. The project will quantify the rates of wind erosion and dust emission in rangelands (grassland, shrubland, grazed vs ungrazed sites as treatments) affected by the fire. The data will be collected with sediment samplers and a portable wind erosion simulator. This information could lead to advances in our fundamental scientific understanding of the impact of wildfire on the rate of wind erosion from sites with different vegetation types and grazing intensity and determine the recovery trajectory of these landscapes.<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.

04/17/2024

04/17/2024

None

Grant

47.050

1

4900

4900

2427344

[{'FirstName': 'Robert', 'LastName': 'Van Pelt', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert S Van Pelt', 'EmailAddress': 'scott.vanpelt@usda.gov', 'NSF_ID': '000822650', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Abinash', 'LastName': 'Bhattachan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Abinash Bhattachan', 'EmailAddress': 'abibhatt@ttu.edu', 'NSF_ID': '000858885', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Branimir', 'LastName': 'Segvic', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Branimir Segvic', 'EmailAddress': 'branimir.segvic@ttu.edu', 'NSF_ID': '000877207', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'John', 'LastName': 'Stout', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John E Stout', 'EmailAddress': 'john.stout@usda.gov', 'NSF_ID': '0000A02HK', 'StartDate': '04/17/2024', 'EndDate': None, 'RoleCode': 'Co-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': '794091035', 'StreetAddress': '2500 BROADWAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'TX19'}

[{'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]

2024~27014

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2427344.xml'}

RAPID: Organizational Decision-making and Restoration of Rural Healthcare Infrastructure and Access in Texas Smokehouse Creek Fire

NSF

04/15/2024

03/31/2025

{'Value': 'Standard Grant'}

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

{'SignBlockName': 'Daan Liang', 'PO_EMAI': 'dliang@nsf.gov', 'PO_PHON': '7032922441'}

Wildfires are extremely destructive to critical infrastructure sectors, especially in rural communities. Among them, healthcare and public health systems are frequently disrupted or destroyed. Yet, little is known about the decision-making processes that lead to prioritization of resources and efforts as community transitions from response to recovery. This Rapid Response Research (RAPID) project supports research on theoretical and practical implications of organizational behavior and decision-making processes to restore healthcare access in the wake of wildfire disasters. A key focus is on examining differences between work as planned (stipulated in emergency management plans, incident action plans, recovery plans, etc.) and the work as done (implementation of these plans) as well as their effect on vulnerable populations (e.g., persons with physical and mental health vulnerabilities) within vulnerable communities (e.g., rural, low capacity). <br/><br/>Using the recent Texas Smokehouse Creek Fire as a case study, this project explores an emerging theme of research on how decisions are made and implemented with respect to prioritizing the restoration of healthcare access as incident operations transition from response to recovery. In February 2024, nearly 1.25 M acres of the rural Texas panhandle was consumed by fire in less than two weeks. It significantly disrupted healthcare operations, access, and services in affected communities. To better understand the phenomenon, the research team collects highly ephemeral data including participant observations in planning meetings and briefings within the Emergency Operation Centers, emergency management offices, local and regional health departments, hospitals, nursing homes, and other health care facilities as well as in-person semi-structured interviews with officials across public health, emergency management and relevant public safety leaders in the communities directly impacted by the fire. They are supplemented with secondary data including incident action plans, demobilization plans, operational briefings, recovery plans, and communications with the public and media immediately preceding, during, and after the fire. Deidentified data are shared and published via NHERI DesignSafe for research community use. Through analysis of the interviews, observations, and plans and other documents, the team develops transferable knowledge critical to informing planning and decision-making for restoration of essential health services, particularly for vulnerable communities affected by wildfires and other disasters.<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.

05/08/2024

05/08/2024

None

Grant

47.041

1

4900

4900

2427345

[{'FirstName': 'Jason', 'LastName': 'Moats', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason B Moats', 'EmailAddress': 'jbmoats@tamu.edu', 'NSF_ID': '000799099', 'StartDate': '05/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Carlee', 'LastName': 'Purdum', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carlee Purdum', 'EmailAddress': 'jcarleepurdum@tamu.edu', 'NSF_ID': '000869999', 'StartDate': '05/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Benika', 'LastName': 'Dixon', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benika C Dixon', 'EmailAddress': 'benikad@tamu.edu', 'NSF_ID': '000875674', 'StartDate': '05/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tara', 'LastName': 'Goddard', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tara B Goddard', 'EmailAddress': 'goddard@tamu.edu', 'NSF_ID': '000936660', 'StartDate': '05/08/2024', '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}