Transferable and Extensible Machine Learning-Derived Atomic Charges for Modeling Hybrid Nanoporous Materials

Nanoporous materials have attracted significant interest as an emerging platform for adsorption-related applications. The high-throughput computational screening became a standard technique to access the performance of thousands of candidates, but its accuracy is highly dependent on a partial charge...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Chemistry of materials 2020-09, Vol.32 (18), p.7822-7831
Hauptverfasser:	Korolev, Vadim V, Mitrofanov, Artem, Marchenko, Ekaterina I, Eremin, Nickolay N, Tkachenko, Valery, Kalmykov, Stepan N
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!