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
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Q
Accès en ligne:https://doaj.org/article/a292041c8fcb4567a97c14746760b48e
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