Project Grant 2533416
- This National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) Project Grant award of $271,704 supports theoretical and computational research and education to advance Kohn-Sham density functional theory. The research aims to develop more accurate computer models of materials by improving approximations for the exchange-correlation energy, a key component of this computational approach. The project seeks to expand the predictive capabilities of density functional...
- This National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) Project Grant award to The Administrators of the Tulane Educational Fund (Tulane University) provides $112,576 in funding from February 1, 2024 to March 31, 2024 to support theoretical research, computation, and education aimed at developing more accurate and predictive density functionals for the exchange-correlation energy in quantum mechanical modeling of molecules, chemicals, and materials. The research...
- This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) provides $529,999 in funding to Purdue University from June 15, 2023 to May 31, 2026. The award supports the development of advanced theories and methods for computer simulation of electronic structure of molecules and materials, with the goal of enabling highly accurate prediction of properties and interpretation of experiments for these systems. The key products and services to be...
- This National Science Foundation project grant award of $460,884 supports research at Rutgers University, Newark from May 2022 through April 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). Professor Neepa Maitra and her research group will develop new time-dependent density functional and exact factorization methods to computationally simulate molecules in classical and quantized light fields. This includes modeling electron and ion dynamics using density functional...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program, CFDA 47.049, supports theoretical and computational research and education to enhance the accuracy and efficiency of first-principles quantum mechanical simulations for studying the electronic structure of materials. The $220,991 award aims to develop innovative machine learning-based approximations to the exact functional within density functional theory, which is critical for...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports theoretical and computational research to enhance the accuracy and efficiency of first-principles quantum mechanical simulations for understanding the electronic structure of materials. The $232,250 award to The Research Foundation for The State University of New York, operating as Stony Brook University, aims to develop innovative approximations to the exact...
- This $520,348 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development, implementation, and application of a new approach to strong electron correlation based on Natural Determinant Functional Theory (NDFT). The principal investigator, Filipp Furche of the University of California, Irvine (UCI), will advance NDFT to address limitations of existing methodology for modeling strong electron correlation,...
- This $318,775 National Science Foundation project grant supports theoretical and computational research and education activities at Lehigh University from May 2022 through April 2025. The award is part of the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which aims to advance scientific knowledge and understanding in these fields. Specifically, the principal investigator and their team will develop advanced numerical techniques to model the properties of two-dimensional quantum...
- The National Science Foundation (NSF) awarded a $629,867 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Texas at Austin. The funding supports research by Dr. Doran Bennett to develop new computational methods for simulating excited-state dynamics and nonlinear spectroscopy of molecular materials at the mesoscale (10nm - 1μm). The project aims to establish how specific materials absorb and deploy energy from light, providing essential...
- The National Science Foundation (NSF), through its Mathematical and Physical Sciences (MPS) program (CFDA 47.049), awarded a $650,000 Project Grant to Yale University to develop new computational methods for simulating light-matter interactions in complex materials. Over a 5-year period from January 1, 2024 to December 31, 2028, the research team led by Dr. Tianyu Zhu will create a reliable and efficient toolbox for modeling spectroscopic properties of solid-state materials. This will involve...
The National Science Foundation (NSF) awarded a $750,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to Tulane University researchers Adrienn Ruzsinszky, John P. Perdew, and Jianwei Sun. The grant supports the development of more accurate and computationally feasible density functional approximations on the higher rungs of the hierarchy of density functional theory. This research aims to improve the accuracy of electronic structure calculations for molecules and materials, enhancing the predictive capabilities of density functional theory in applications spanning chemistry, physics, materials science, and other scientific domains. The project's broader impacts include training graduate students and postdoctoral fellows, engaging undergraduate physics majors, and providing tools to support machine learning approaches in chemistry. The award period runs from September 1, 2025, to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 8/26/25 | ||
| Not listed | $750.0k | 8/20/25 |