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Force field-inspired transformer network assisted crystal density prediction for energetic materials
Machine learning has great potential in predicting chemical information with greater precision than traditional methods. Graph neural networks (GNNs) have become increasingly popular in recent years, as they can automatically learn the features of the molecule from the graph, significantly reducing...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10355066/ https://www.ncbi.nlm.nih.gov/pubmed/37468954 http://dx.doi.org/10.1186/s13321-023-00736-6 |