Element selection for crystalline inorganic solid discovery guided by unsupervised machine learning of experimentally explored chemistry
Machine learning has the potential to significantly speed-up the discovery of new materials in synthetic materials chemistry. Here the authors combine unsupervised machine learning and crystal structure prediction to predict a novel quaternary lithium solid electrolyte that is then synthesized.
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| Auteurs principaux: | , , , , , , , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/ada6eb69fea0458aa467799a13aadb44 |
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