Structure prediction drives materials discovery

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VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code (2019, background): “It is not only used to understand the observed behavior of solids, including the structural, mechanical, electronic, magnetic and optical properties, but increasingly more to predict characteristics of compounds that have not yet been determined experimentally [6, 7, 8, 9, 10, 11, 12].”
Crystal Diffusion Variational Autoencoder for Periodic Material Generation (2021, background): “Predicting the structure of unknown materials requires very expensive random search and QM simulations, and is considered a grand challenge in materials discovery (Oganov et al., 2019).”
A perspective on conventional high-temperature superconductors at high pressure: Methods and materials (2019, background): “studies based on structural motifs [444], inter-atomic distances, guest to host atom ratio [445, 446], valence band analysis [447], electron localization function, among others [448, 449, 51, 450, 48, 46, 47, 451].”