Machine Learning Descriptors for Data‐Driven Catalysis Study
Abstract Traditional trial‐and‐error experiments and theoretical simulations have difficulty optimizing catalytic processes and developing new, better‐performing catalysts. Machine learning (ML) provides a promising approach for accelerating catalysis research due to its powerful learning and predic...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-08-01
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| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.202301020 |