Prediction of transition state structures of gas-phase chemical reactions via machine learning
Obtaining good initial structures is the main challenge for the computational study of transition states. Here, fast and accurate predictions for transition state of gas phase reactions are achieved by machine learning based on interatomic distances.
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-36823-3 |