Project Grant 2152767

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 networks and employ basin-hopping algorithms to explore diverse nanoparticle configurations. They will extract local structural descriptors from the configuration data and use pattern recognition to learn the statistical distribution of surface motifs. This work aims to link nanoparticle structure and reactivity in catalytic reactions. Additionally, the university will partner with the Center for Excellence in Engineering and Diversity to involve underrepresented minority undergraduate and high school students in the research and conduct a workshop for Los Angeles high school teachers to illustrate computational insights into catalytic processes.