Practical Machine Learning Strategies. 2. Accurate Prediction of ωB97X-V/6-311+G(2df,2p), ωB97M-V/6-311+G(2df,2p) and ωB97M(2)/6-311+G(2df,2p) Energies From Neural Networks Trained From ωB97X-D/6-31G* Equilibrium Geometries and Energies

Practical Machine Learning Strategies. 2. Accurate Prediction of ωB97X-V/6-311+G(2df,2p), ωB97M-V/6-311+G(2df,2p) and ωB97M(2)/6-311+G(2df,2p) Energies From Neural Networks Trained From ωB97X-D/6-31G* Equilibrium Geometries and Energies

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Détails bibliographiques
Publié dans:Journal of computational chemistry. - 1984. - 46(2025), 13 vom: 15. Mai, Seite e70129
Auteur principal: Klunzinger, Philip (Auteur)
Autres auteurs: Hehre, Thomas, Deppmeier, Bernard, Ohlinger, William, Hehre, Warren
Format: Article en ligne
Langue:English
Publié: 2025
Accès à la collection:Journal of computational chemistry
Sujets:Journal Article DFT algorithms machine learning molecule structure neural networks
Accès en ligne Volltext