Dec. 21, 2021

Understanding materials behavior with data science (VIDEO)

Rebecca Lindsey/LLNL

Computational chemist Rebecca Lindsey, PhD, explains how machine learning and data science techniques are used to develop diagnostic tools for stockpile stewardship, such as models that predict detonator performance. Lindsey also describes how atomistic simulations improve researchers’ understanding of the microscopic phenomena that govern the chemistry in materials under extreme conditions. For example, machine learning interatomic models have recovered structure, dynamics, and other characteristics with quantum accuracy and computational efficiency, enabling researchers to work in previously inaccessible problem spaces. Watch the video on YouTube (3:35).