Machine Learning for Materials Design and Discovery

This Special Topic aims to provide a valuable and timely forum where scientists and practitioners in the field of materials informatics share their most recent findings and disruptive ideas, reveal new advances to improve the fundamental understanding of machine learning approaches for accelerated materials design and discovery, and identify challenges as well as the next critical steps going forward. Journal of Applied Physics has interest to expand in this area and aims to be the home for original and timely research reports on this important topic.

Guest Editors: Rama Vasudevan, Ghanshyam Pilania, and Prasanna V. Balachandran