Atomic-Scale Modeling for Materials and Chemistry

Abstract

Atomic and molecular modeling techniques have developed over the past 75 years into a vibrant field of computational science, used to understand and predict materials properties and phenomena in academic, industrial, and government labs. Researchers today have the benefit of decades of Moore’s law growth in computer processors, decades of algorithm and software development, experiments capable of atomic-scale characterization for validation, and a deeper understanding of the strengths, limitations, and complementary features of different computational methods. It is not surprising then that important problems in many fields—battery chemistry, drug design, mechanics of materials, biocompatibility, and catalyst design—are routinely studied using atomic-scale simulation and modeling. In this article, we first outline a brief history and background of the density functional theory and molecular dynamics methods. Next, we discuss several case studies that exemplify how scientists and engineers at the Johns Hopkins University Applied Physics Laboratory (APL) use these computational methods to attain APL’s broader goals and mission. Finally, we discuss future directions for atomic-scale modeling and calculations, such as integration with modeling methods at other scales and with artificial intelligence–enabled frameworks, to meet the next generation of sponsor challenges.