Classical Molecular Dynamics Simulations of Nuclear Materials

Russell – University of Idaho

Research Overview

Atomistic simulations are increasingly valuable for industrial needs to predict thermodynamic and kinetic properties of systems at the nanoscale. Design and fitting of interatomic potentials for application to nuclear materials is also an area of fundamental interest. Simulation and modeling can provide understanding of mechanisms that occur far from equilibrium, which can be difficult to directly observe by experiment.

Accurate prediction of melting temperature and elastic properties at finite temperatures are challenging because interatomic potentials are typically fit to zero temperature electronic structure results. New interatomic potentials based on explainable artificial intelligence concepts are needed that combine physics based functional forms with advanced machine learning techniques to fit parameter sets.

Student Research Experience

Working in collaboration with INL’s Collaborative Computing Center, students will learn fundamentals of computational atomistic simulation and modeling. Students will obtain a user account on the NSF ACCESS cyberinfrastructure program and utilize the Bridges-2 supercomputer hosted by the Pittsburgh Supercomputing Center (PSC).

Students will learn to use high performance computers, the LAMMPS code, visualization with VMD code, scripting, and post processing techniques. They will also learn fundamentals of machine learning to fit parameters and the physics behind interatomic potential design. Advanced students may learn programming languages and parallel computing techniques.

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