Project Grant 2522293
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $429,646 to Purdue University to research and develop improved catalyst materials for industrial chemical production processes. The project aims to integrate advanced computer modeling with experimental tools to study how catalyst structures evolve during reactions, enabling more efficient screening and design of energy-efficient catalysts. Specific focus areas include improving the...
- The National Science Foundation (NSF) awarded a $220,614 Project Grant to the University of California, Merced (UC Merced) under the Engineering program (CFDA 47.041) for the period of October 1, 2025 to September 30, 2029. The grant will fund collaborative research aimed at accelerating the discovery and design of dynamically evolving catalyst materials that can improve the efficiency of industrial chemical processes, such as ammonia synthesis for fertilizer production. The research will...
- The National Science Foundation (NSF) awarded a $291,349 Project Grant to the University of Alabama under the Engineering program (CFDA 47.041) to develop and apply advanced machine learning force fields to simulate nanoparticle catalysts under realistic reaction conditions. The goal is to elucidate the catalytic active sites and how nanoparticle shapes evolve during catalytic processes. This research will help enable more sustainable chemical manufacturing by improving the computational...
- This $431,430 National Science Foundation project grant supports the development of machine learning-aided methods to discover synthesizable, active, and stable heterogeneous catalyst materials. Funded under the NSF Engineering program (CFDA 47.041), the three-year award to the University of Michigan involves collaborating with Wayne State University to create an open-source, computer-aided workflow and tools for predicting catalyst properties beyond just activity. The project will apply density...
- The National Science Foundation (NSF) awarded a $638,566 Project Grant under the Engineering program (CFDA 47.041) to the University of Delaware. The grant supports a collaborative research effort to develop a computational-experimental methodology using machine learning to design stable, active, and selective single-atom catalysts for industrial applications. The project aims to uncover physics-inspired descriptors to predict how the support material properties influence the stability,...
- This Project Grant from the National Science Foundation provides $1,367,545 to the University of Michigan under the Engineering program (CFDA 47.041) from October 1, 2021 to September 30, 2025. The funding supports collaborative research titled "Machine Learning-Aided Discovery of Synthesizable, Active and Stable Heterogeneous Catalysts." The Engineering program seeks to improve quality of life and economic strength through innovation and excellence in engineering research. This...
- This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) provides $643,347.00 to the University of Alabama-Tuscaloosa to develop computational tools that empower the design of efficient molecular catalysts. The key products and services to be delivered under this 5-year award include: Using high-performance computational screening to identify optimal catalyst structures, compositions, and kinetics to increase activity, selectivity, and...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) provides $165,000.00 to support a collaborative research initiative focused on developing advanced, long-lasting catalysts for critical industrial chemical processes. Led by Professor Ping Lu of Rowan University and Professor Cheng Zhang of Long Island University, the project aims to address catalyst deactivation challenges by designing innovative...
- This $599,926 federal Project Grant, awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041), supports a collaborative research effort between Northwestern University and the Fritz Haber Institute of the Max Planck Society in Germany. The project aims to develop advanced techniques for studying novel electrocatalyst materials under realistic operating conditions for electrochemical carbon dioxide (CO2) conversion. Key components include machine...
- This National Science Foundation project grant of $728,692 supports research at the University of California, Los Angeles from September 2022 through August 2025 under the Engineering program (CFDA 47.041). The university will develop machine learning methods to model the dynamic structures of platinum and nickel nanoparticles containing 20 to 200 atoms and their effects on dehydrogenation and hydrogenolysis reactions. Researchers will generate accurate interatomic potentials using neural...
This Project Grant award of $902,786.00 from the National Science Foundation's Engineering program (CFDA 47.041) aims to accelerate the discovery and design of dynamically evolving catalyst materials. The researchers will integrate advanced computer modeling, artificial intelligence, and machine learning with experimental tools to study how catalyst structures evolve during reactions, with a focus on improving catalysts for ammonia fertilizer production and using ammonia as an energy carrier. The project will construct a unified, predictive model of the dynamic restructuring of metal nanoparticles on metal-oxide supports, enabling the design of more active, stable, and "self-healing" catalytic materials. This research will be conducted at the University of Wisconsin-Madison from October 1, 2025, to September 30, 2029, and will include interdisciplinary training of graduate students as well as educational outreach efforts.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $902.8k | 8/22/25 |