Prediction on mechanical properties of non-equiatomic high-entropy alloy by atomistic simulation and machine learning
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| Author: | Liang Zhang, Kun Qian, Björn W. SchullerORCiDGND, Yasushi Shibuta |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-915968 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/91596 |
| ISSN: | 2075-4701OPAC |
| Parent Title (English): | Metals |
| Publisher: | MDPI |
| Place of publication: | Basel |
| Type: | Article |
| Language: | English |
| Year of first Publication: | 2021 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2022/01/26 |
| Tag: | General Materials Science; Metals and Alloys |
| Volume: | 11 |
| Issue: | 6 |
| First Page: | 922 |
| DOI: | https://doi.org/10.3390/met11060922 |
| Institutes: | Fakultät für Angewandte Informatik |
| Fakultät für Angewandte Informatik / Institut für Informatik | |
| Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing | |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Licence (German): |  CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand) |
