Jason Gibson, a doctoral student in the Department of Materials Science & Engineering at the University of Florida, has been awarded a Molecular Sciences Software Institute (MolSSI) Fellowship, sponsored by the National Science Foundation.
Gibson’s research proposal to MolSSI included building an online, open database of machine learning models to help speed up the process of computing the potential energy surface and various material properties of both 2D and bulk materials.
The database, Materialsweb, would directly assist in experimental synthesis efforts and semiconductor design.
“It has the potential to expedite material simulations for countless other researchers, and could also assist in discovering new materials,” said Gibson. “Plus, the materials community currently lacks a standard location and Application Programming Interface (API) for machine learning potentials, and I think our website helps fill that void.”
Gibson graduated summa cum laude from West Virginia University with a bachelor’s degree in aerospace engineering and a minor in physics. During his undergrad, he was a NASA Space Grant scholar and a guest researcher at the Foundation of Research and Technology Hellas in Crete, Greece. He joined the lab of Richard Hennig, Ph.D., in 2019. Gibson’s current research focuses on utilizing machine learning models to accelerate density functional theory calculations.
“I was thrilled to receive this fellowship,” said Gibson. “There is something profoundly motivating about a panel of experts supporting your ideas. Our research group now hosts an online database of density functional theory calculations, and working with the software scientists at MolSSI will help us to maximize the impact of the data we provide on the site.”
The Molecular Sciences Software Institute provides funding for a set of prestigious fellowships that recognize advanced graduate students and postdocs pursuing the development of software infrastructure, middleware and frameworks that will benefit the broader field of computational molecular sciences, including biomolecular and macromolecular simulation, quantum chemistry and materials science.