Computational Materials Discovery

The spectacular advances in computational techniques for materials discovery including high-throughput screenings, data-mining, machine learning, and artificial intelligence, as well as structure prediction based calculations, have led to the in silico discovery of a plethora of targeted materials. At the same time, the structure-property relationships that have been elucidated via computations have made it possible to design compounds for specific applications. Recently, there have been a number of remarkable materials-by-design success stories, and undoubtedly many other predicted materials will be experimentally realized soon. This special issue showcases advances in methods used to discover and design new materials, and illustrate their applications towards energy, quantum, structural, and 2D materials, as well as molecular crystals, MOFs, and more.

Guest Editors: Eva Zurek, Noa Marom, and Johannes Hachmann with JCP Editors David Manolopoulos, Todd Martínez, Angelos Michaelides, and David Sherrill