This $220,991 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program 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 research team at the University of California, Irvine aims to develop innovative machine learning-based approximations to the exchange-correlation functional, a...
This $288,229 federal Project Grant awarded by the National Science Foundation (NSF) Division of Materials Research supports theory, computation, and education to advance the engineering of nanoparticle-based materials. The project aims to develop a comprehensive computational framework to predict the structure and properties of functional nanomaterials, which will be made available to the broader research community. The work will be conducted at Iowa State University and involve...
This $282,000 Project Grant awarded by the National Science Foundation (NSF) Division of Materials Research under the Mathematical and Physical Sciences (CFDA 47.049) program supports theoretical research and educational activities aimed at understanding topological materials. The project focuses on addressing outstanding challenges in the theory of topological quantum chemistry and symmetry-based indicators, with goals of: 1) studying the hydrodynamic response and defect behavior of...
This Project Grant award from the National Science Foundation (NSF) Division of Materials Research, under the Mathematical and Physical Sciences (CFDA 47.049) program, provides $500,000 in funding to the University of California, Berkeley (UC Berkeley) for theoretical and computational research and education in solid state physics and materials science. The key objectives are to use quantum theory, high-performance computing, and new concepts like topology to explain and predict the...
This $296,555 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support the development of reduced basis enhancements for neural networks and their application to quantum materials simulation. Specifically, the University of Massachusetts Dartmouth will combine traditional reduced basis methods with deep learning techniques to build an analysis-driven computational emulator for parameterized partial differential equations....
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports the development of accurate, computationally efficient, and universal computational methods for describing strongly correlated electron systems. The $142,387 award to the University of Florida, with a project period from April 1, 2025 to March 31, 2030, will enable Dr. Ramon Alain Miranda Quintana and his team to: (1) design, implement, and test new...
This $300,000 Project Grant awarded by the National Science Foundation (NSF) Division of Materials Research under the CFDA 47.049 Mathematical and Physical Sciences program supports research and education initiatives at the University of Chicago. The key products and services to be delivered include:
The development of innovative theoretical approaches and tools to better understand and predict the unusual and complex behaviors of strongly interacting metals, which exhibit remarkable...
The National Science Foundation (NSF) Division of Materials Research awarded a $346,461 project grant to North Carolina State University (NC State) under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports research and education aimed at advancing simulation and computational approaches for studying the atomic and electronic structures of materials. Key focus areas include:
Expanding the ability of quantum Monte Carlo (QMC) many-body wave function methods to...
This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences (CFDA 47.049) program provides $232,250 to support theoretical and computational research and education aimed at enhancing the accuracy and efficiency of density functional theory (DFT) simulations for studying the electronic structure of materials. The research team at Stony Brook University will develop innovative machine learning-based approximations to the exchange-correlation...
The National Science Foundation awarded a $1,039,367 Project Grant to the University of Virginia under the Mathematical and Physical Sciences program (CFDA 47.049) for work running from March 15, 2022 to February 28, 2026. The award will support the development of an artificial intelligence-driven framework for the design and discovery of complex materials, with a focus on energetic materials of strategic importance to the Department of Defense and Department of Energy. Key activities include...