Formation energy prediction of crystalline compounds using deep convolutional network learning on voxel image representation

Abstract Emerging machine-learned models have enabled efficient and accurate prediction of compound formation energy, with the most prevalent models relying on graph structures for representing crystalline materials. Here, we introduce an alternative approach based on sparse voxel images of crystals...

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Bibliographic Details
Main Authors: Ali Davariashtiyani, Sara Kadkhodaei
Format: Article
Language:English
Published: Nature Portfolio 2023-12-01
Series:Communications Materials
Online Access:https://doi.org/10.1038/s43246-023-00433-9