Teaching a neural network to attach and detach electrons from molecules
Quantum mechanical calculations of molecular ionized states are computationally quite expensive. This work reports a successful extension of a previous deep-neural networks approach towards transferable neural-network models for predicting multiple properties of open shell anions and cations.
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Auteurs principaux: | Roman Zubatyuk, Justin S. Smith, Benjamin T. Nebgen, Sergei Tretiak, Olexandr Isayev |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Sujets: | |
Accès en ligne: | https://doaj.org/article/a292041c8fcb4567a97c14746760b48e |
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