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