Project Grant 2231469
- 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....
- The University of Massachusetts Boston was awarded a three-year, $374,449 Project Grant from the National Science Foundation to research speed limits on pattern formation in dynamic materials. The grant is part of NSF's Engineering program (CFDA 47.041), which supports innovation and excellence in engineering research and education to improve quality of life and economic strength. Under the award, University of Massachusetts Boston researchers in the Department of Grants and Administrative...
- 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 $192,372 Project Grant from the National Science Foundation Directorate for Mathematical and Physical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports the development of new methods to systematically explore and predict material microstructures using artificial intelligence techniques. The awardee, George Mason University, will adapt leading data science and machine learning methods to discover a practical representation of microstructure state space that...
- The National Science Foundation awarded a $310,000 Project Grant to Arizona State University (ASU) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049). The grant, which runs from May 1, 2025 to April 30, 2028, supports research to develop explainable machine learning models for predicting material properties based on their microstructure. By systematically learning the key n-point correlation functions that drive material behavior, the project aims to provide both...
- This $1,060,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program aims to revolutionize the discovery of new solid-state materials for advanced energy storage, neuromorphic computing, and smart sensor applications. The project will leverage advanced artificial intelligence (AI), machine learning (ML), and automated synthesis tools to develop a transformative approach for designing solid-state ion conductors using multi-element...
- This four-year project grant from the National Science Foundation Division of Materials Research, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $1,414,494 to the University of Illinois to conduct collaborative research in machine learning algorithms for the prediction and synthesis of next-generation superhard functional materials. The research aims to advance scientific understanding and develop new materials through the use of machine learning to model material...
- 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 (CFDA 47.049) program provides $750,000 to Northeastern University to develop innovative engineered photonic materials using a data-driven deep learning approach. The research aims to accelerate the discovery, design, and implementation of new photonic metamaterials with tailored optical properties for applications in areas such as lasers, optical communications, quantum computing, and...
- The National Science Foundation (NSF) awarded a 4-year, $400,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to Trustees of Boston University for their research project titled "COLLABORATIVE RESEARCH: DMREF: CLOSED-LOOP DESIGN OF POLYMERS WITH ADAPTIVE NETWORKS FOR EXTREME MECHANICS." The project aims to develop an integrated experimental and computational platform for accelerated discovery and design of novel polymers exhibiting unprecedented...
This $250,000 National Science Foundation project grant will support research at the University of Massachusetts Boston and the University of California-Santa Barbara to advance machine learning techniques for predicting the behavior of dynamic materials. Jason Green of UMass Boston and Igor Mezic of UC Santa Barbara will combine machine learning and physical theory methods to create new approaches for designing functional materials with tailored optical, mechanical, or photonic properties on precise timescales. The research aims to (1) develop data-driven models of active hydrogels using artificial intelligence techniques, (2) apply thermodynamic speed limits as optimally predictive machine learning models, and (3) implement these speed limits as design principles to maximize yield and minimize dissipation in materials. In addition, the researchers will develop STEM curriculum integrating data science and theoretical chemistry and conduct outreach to broaden participation in these fields. Awarded on August 15, 2022 under the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049), this project aligns with the agency's mission to advance these scientific fields and strengthen the national research enterprise.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 8/2/22 |