Bayesian exploration of the composition space of CuZrAl metallic glasses for mechanical properties
Abstract Designing metallic glasses in silico is a major challenge in materials science given their disordered atomic structure and the vast compositional space to explore. Here, we tackle this challenge by finding optimal compositions for target mechanical properties. We apply Bayesian exploration...
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| Main Authors: | Tero Mäkinen, Anshul D. S. Parmar, Silvia Bonfanti, Mikko J. Alava |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01591-9 |
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