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Predicting the Young’s Modulus of Silicate Glasses using High-Throughput Molecular Dynamics Simulations and Machine Learning
The application of machine learning to predict materials’ properties usually requires a large number of consistent data for training. However, experimental datasets of high quality are not always available or self-consistent. Here, as an alternative route, we combine machine learning with high-throu...
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| Publicado no: | Sci Rep |
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| Main Authors: | , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6584533/ https://ncbi.nlm.nih.gov/pubmed/31217500 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-45344-3 |
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