Project Grant 2603672
- Federal Project Grant Award Summary The University of Central Florida Board of Trustees received a $452,933 Project Grant award from the National Science Foundation (NSF) Division of Chemistry under the Mathematical and Physical Sciences program (CFDA 47.049), effective September 1, 2026 through August 31, 2029. This collaborative research initiative will develop an integrated data-enabled hyperspectral imaging and artificial intelligence (AI) platform for advanced materials characterization....
- Federal Grant Award Summary The National Science Foundation (NSF) awarded Mississippi State University a $329,129 Project Grant on September 1, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049), funded jointly by the Division of Chemistry and the Established Program to Stimulate Competitive Research (EPSCOR). This Research Experiences for Undergraduates (REU) Site award supports the training and mentorship of 10 undergraduate students annually for 10-week summer research...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Materials Research awarded $466,668 to The University of Southern Mississippi on July 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) for collaborative research spanning U.S. and Canadian institutions. This four-year project (completion June 30, 2030) delivers a data-driven materials-by-design framework to accelerate the discovery and optimization of organic mixed ionic-electronic...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Chemistry awarded $458,820 through the Mathematical and Physical Sciences program (CFDA 47.049) to support a CAREER grant at The University of Mississippi. The award, effective January 15, 2026, through July 31, 2029, funds development of advanced analytical methodology for three-dimensional molecular characterization at the nanometric scale. The primary deliverable is a new experimental approach based on...
- Federal Grant Award Summary Mississippi State University received a $299,697 Project Grant from the National Science Foundation's Division of Chemical, Bioengineering, Environmental, and Transport Systems (Engineering program, CFDA 47.041) effective August 1, 2025, through July 31, 2028. The primary deliverable is the development of machine-learned interatomic potentials (ML-IAPs) that accurately predict atomic interactions within zeolite nanopores while maintaining computational efficiency...
- Federal Grant Award Summary Michigan State University received a $180,000 Project Grant from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) awarded August 15, 2025, with completion targeted for July 31, 2028. The research delivers statistical frameworks and theoretical foundations for adversarial training in neural networks, addressing vulnerabilities in artificial intelligence (AI) systems that can produce incorrect predictions when...
- Federal Grant Award Summary The National Science Foundation's Division of Materials Research awarded $384,233 to the University of Southern Mississippi under the Mathematical and Physical Sciences program (CFDA 47.049) effective October 1, 2025, with completion targeted for September 30, 2029. This collaborative research project, conducted in partnership with international institutions, focuses on accelerated development of polymer salogels—composite materials combining inorganic salt hydrates...
- Federal Grant Award Summary This collaborative research Project Grant, awarded October 1, 2025, by the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049), provides $519,998 in federal funding through September 30, 2029, to develop a data-driven framework for discovering and optimizing solid-state ion conductor materials. The University of California, San Diego serves as the recipient institution. The research integrates artificial intelligence...
- Federal Grant Award Summary Mississippi State University received a $363,218 Project Grant award dated September 1, 2025, from the National Science Foundation's Office of Integrative Activities under the Integrative Activities program (CFDA 47.083) to acquire and establish an advanced Scanning Electron Microscope (SEM) facility. The instrument, to be housed in an open-access imaging facility, will be fully integrated with Energy Dispersive X-Ray Spectroscopy (EDS), Electron Backscatter...
- Federal Project Grant Award Summary The National Science Foundation's Division of Chemistry is funding a collaborative research project totaling $271,435 under the Mathematical and Physical Sciences (CFDA 47.049) program, awarded on September 1, 2025, with completion targeted for August 31, 2028. Principal investigators Professor Jon Camden at the University of Notre Dame and Professor Lasse Jensen at Pennsylvania State University will conduct fundamental research combining experimental and...
Mississippi State University received a $615,927 Project Grant from the National Science Foundation (NSF) Division of Chemistry under the Mathematical and Physical Sciences program (CFDA 47.049), awarded September 1, 2026, with completion targeted for August 31, 2029. This collaborative research initiative will develop an integrated hyperspectral imaging and artificial intelligence (AI) platform designed to analyze highly concentrated particle suspensions currently unmeasurable through conventional optical methods. The project will create a unified experimental-computational-AI framework incorporating advanced optical instrumentation, computational modeling, and physics-informed machine learning to characterize nano- and micro-particle dispersions with optical densities ranging from 3 to 100, enabling real-time determination of particle size, composition, concentration, and optical properties. The deliverables include a dual-track hyperspectral imaging system capable of acquiring multidimensional, polarization-resolved image data, along with open-access datasets, software tools, and educational modules. The research will advance AI methodology by developing physics-informed machine-learning approaches for extracting scientific knowledge from large, complex, nonlinear datasets. Project outcomes will support applications across environmental monitoring, advanced manufacturing, energy technologies, biomedical diagnostics, and consumer products sectors. Additionally, the award will fund interdisciplinary training for graduate, undergraduate, and postdoctoral researchers in optics, computation, and data science, with broad dissemination of results through peer-reviewed publications and educational programming.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $615.9k | 7/14/26 |