A geometric-information-enhanced crystal graph network for predicting properties of materials
Graph neural networks are an accurate machine learning-based approach for property prediction. Here, a geometric-information-enhanced crystal graph neural network is demonstrated, which accurately predicts the formation energy and band gap of crystalline materials.
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-09-01
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| Series: | Communications Materials |
| Online Access: | https://doi.org/10.1038/s43246-021-00194-3 |