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Materials Science in the AI age: high-throughput library generation, machine learning and a pathway from correlations to the underpinning physics
The use of advanced data analytics and applications of statistical and machine learning approaches (‘AI’) to materials science is experiencing explosive growth recently. In this prospective, we review recent work focusing on generation and application of libraries from both experiment and theoretica...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | MRS Commun |
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| Κύριοι συγγραφείς: | , , , , , , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
2019
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7067066/ https://ncbi.nlm.nih.gov/pubmed/32166045 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1557/mrc.2019.95 |
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