Crystal structure generation with autoregressive large language modeling

Abstract The generation of plausible crystal structures is often the first step in predicting the structure and properties of a material from its chemical composition. However, most current methods for crystal structure prediction are computationally expensive, slowing the pace of innovation. Seedin...

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Bibliographic Details
Main Authors: Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-54639-7
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