Interatomic Potentials: A Framework for Generating Quantum-Accurate Material Models
Amit Samanta | 21-ERD-005
We will develop an agile, high-performance computing capability to generate interatomic potentials balancing prediction fidelity and computational cost. This capability will generate results necessary to nuclear stockpile stewardship programs and expand the application of atomistic simulations in science, including areas such as advanced materials development.
Publications, Presentations, and Patents
Kumar, S. et al. 2022. “Accurate Parameterization of the Kinetic Energy Functional.” Journal of Chemical Physics 156, 024107.
Kumar, S. et al. 2022. “Accurate Parameterization of the Kinetic Energy Functional.” Journal of Chemical Physics 156, 024110.
Sun, H. et al. “Exploring Interface Structure Between the Perovskite Oxides Using Evolutionary Structure Search and Automated Design of Deep Learning Potentials via Neural Architecture Search.” Materials Research Society Fall Meeting, Boston, MA. Nov. 27-Dec. 2, 2022.