Uncertainty-Aware Surrogate Modeling of High-Throughput DFT Data for Rapid Materials Screening

iamrp.net-GuXn-1791515266-t549787637 1791515266 Institute for Advanced Materials Research Press info@iamrp.net Institute for Advanced Materials Research Press Journal of Artificial Intelligence for Materials Science J. Artif. Intell. Mater. Sci. 3149-8957 2024 3 1 Uncertainty-Aware Surrogate Modeling of High-Throughput DFT Data for Rapid Materials Screening Daniel Fischer Laura Meier Thomas Braun 2024 10.68159/t549787637 https://iamrp.net/pub/journal/1/article/t549787637 Choudhary K, Garrity KF, Sharma V, Biacchi AJ, Hight Walker AR, Tavazza F. High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses. npj Comput Mater. 2020;6:64. Afzal MA, Browning AR, Goldberg A, Halls MD, Gavartin JL, Morisato T, et al. High-throughput molecular dynamics simulations and validation of thermophysical properties of polymers for various applications. ACS Appl Polym Mater. 2021;3:620-30. 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