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cond-mat.mtrl-sci2022
Genetic programming-based learning of carbon interatomic potential for materials discovery
Andrew Eldridge, Alejandro Rodriguez, Ming Hu +1
Efficient and accurate interatomic potential functions are critical to computational study of materials while searching for structures with desired properties. Traditionally, poten…
cond-mat.mtrl-sci2022★ 5 cited
Physics Guided Deep Learning for Generative Design of Crystal Materials with Symmetry Constraints
Yong Zhao, Edirisuriya M. Dilanga Siriwardane, Zhenyao Wu +4
Discovering new materials is a challenging task in materials science crucial to the progress of human society. Conventional approaches based on experiments and simulations are labo…