Theoretical and computational methods for accelerated materials discovery

NA Zarkevich, MODERN PHYSICS LETTERS B, 35, 2130003 (2021).

DOI: 10.1142/S0217984921300039

Predicting properties of materials and phase transformation using theoretical and computational multi-scale methods involving artificial intelligence and machine learning (ML) is important and highly rewarding. We review the relevant methods and mention a few applications and examples. We demonstrate that theoretical guidance narrows the search space and accelerates materials discovery.

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