Discovering Patterns in Disorder: Machine Learning for Fluctuating Mesoscopic Materials

This special topic will explore the frontiers of applying machine learning to discovering and understanding materials where disorder and thermal fluctuations are important, across both the "hard" and "soft" matter boundary. We aim to highlight the application of machine learning to address questions in materials science, as well as the use of machine learning to speed up computational bottlenecks such as obtaining accurate energy and forces, and sampling from complex energy landscapes.

Guest Editors: Alpha Lee, Daan Frenkel, and Tristan Bereau