Materials-discovery workflow guided by symbolic regression for identifying acid-stable oxides for electrocatalysis
Abstract The efficiency of active learning (AL) approaches to identify materials with desired properties relies on the knowledge of a few parameters describing the property. However, these parameters are often unknown if the property is governed by a high intricacy of many atomistic processes. Here,...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01596-4 |
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