Machine learning for materials design and discovery

The Machine Learning (ML) Special Topic collection on Machine Learning for Materials Design and Discovery in the Journal of Applied Physics presents a representative sample of the latest ML related research being pursued within the broader physics and materials communities. The authors provide a brief background on various ML and statistical learning methods, as the editorial is designed for both experts and novices in the field, before going into the details of specific challenges addressed in each individual contribution. The authors have classified he contributions included in the Special Topic into four broad categories, such as materials and molecular property predictions, materials modeling and simulations, materials design, discovery, and active learning, and materials characterization and imaging applications. . For each of these groups, they survey the contributing studies while emphasizing the technical challenges addressed by each.