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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Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 46(2025), 13 vom: 15. Mai, Seite e70129
1. Verfasser: Klunzinger, Philip (VerfasserIn)
Weitere Verfasser: Hehre, Thomas, Deppmeier, Bernard, Ohlinger, William, Hehre, Warren
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2025
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article DFT algorithms machine learning molecule structure neural networks
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