This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $273,291 to the University of California, Santa Barbara to develop computational tools that combine machine learning and scientific computing for the exploration and prediction of polymer systems. The goal is to accelerate the discovery of new materials and provide a framework for computationally costly problems across various scientific domains. The research...
This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences program (CFDA 47.049) provides $150,843 to the University of Wisconsin-Madison for the development of an experimental framework to enhance large language models (LLMs) for materials science hypothesis generation. The project aims to expand the capabilities of LLMs by enabling them to ingest and learn from diverse data formats beyond just text, such as microscopy images, X-ray diffraction...
This Project Grant from the National Science Foundation's Division of Materials Research provides $186,395 to Wake Forest University under the Mathematical and Physical Sciences program (CFDA 47.049) from April 1, 2023 through March 31, 2025. The award supports computational research, software development, and education focused on investigating candidate solid state battery materials. Specifically, the recipient will employ computational methods and public domain software to examine promising...
This National Science Foundation (NSF) award under the Mathematical and Physical Sciences grant program (CFDA 47.049) provides $149,354 over three years (09/01/2024 - 08/31/2027) to develop open-source software tools for analyzing atomic structures in atomistic simulations. The project aims to create four key software packages: (1) an analyzer tool to apply machine learning-based atomic structure classifiers, (2) a machine learning tool to train and test classifiers, (3) a campaign manager to...
This $228,723 Project Grant awarded by the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) will fund the development of a coupled multi-energy-scale micro-spectroscopic analytical approach to study the solid-state electrolyte (SSE) interface in halide-based solid-state batteries. The 2-year project, which will be conducted at the University of New Mexico (UNM) in collaboration with researchers at the University of Texas at Austin, aims to fundamentally understand...
This Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) provides $509,263 to the Georgia Tech Research Corporation from August 2022 to July 2026 to advance understanding of the role of external constraint on electrochemical dealloying mechanisms in solid-state batteries. The award supports research using experimental techniques to reveal reaction processes of lithium metal alloys under mechanical constraint and relate findings to...
This $326,350 Project Grant, awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports collaborative research at the University of Delaware and Arizona State University to identify structural features of open framework materials based on silicon, germanium, and tin that can promote fast sodium-ion diffusion. The research aims to better understand the electrochemical behavior of these materials and how their structural properties...
This $106,769 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program will support the development of new methods to systematically explore and predict materials microstructures. The University of California, Davis will receive funding from September 1, 2022 through August 31, 2024 to adapt machine learning and data science techniques for materials science applications. Specifically, the university will integrate expert knowledge on physically meaningful...
This $232,250 federal 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 materials design. The research team at Stony Brook University aims to develop innovative approximations to the exact functional using advanced machine learning techniques. Key objectives include...
This $455,286 federal Project Grant awarded by the National Science Foundation (NSF) Division of Materials Research supports research at the University of New Mexico (UNM) to explore over-stoichiometric disordered rock salts as potential lithium-ion and sodium-ion battery cathode materials. The key objectives are to: 1) develop a new series of over-stoichiometric Li(Na)-Ti-Mn(Fe)-O-F-based disordered rock salts, 2) characterize their crystallographic, electronic, and vibrational properties,...