Deep Learning of Activation Energies
Quantitative predictions of reaction properties, such as activation energy, have been limited due to a lack of available training data. Such predictions would be useful for computer-assisted reaction mechanism generation and organic synthesis planning. We develop a template-free deep learning model...
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| Format: | Article |
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American Chemical Society (ACS)
2020
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| Online Access: | https://hdl.handle.net/1721.1/125019 |