Chemical shifts in molecular solids by machine learning

Solid-state nuclear magnetic resonance combined with quantum chemical shift predictions is limited by high computational cost. Here, the authors use machine learning based on local atomic environments to predict experimental chemical shifts in molecular solids with accuracy similar to density functi...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Federico M. Paruzzo, Albert Hofstetter, Félix Musil, Sandip De, Michele Ceriotti, Lyndon Emsley
Format: article
Langue:EN
Publié: Nature Portfolio 2018
Sujets:
Q
Accès en ligne:https://doaj.org/article/970a2addd1a345bea23283a88747dfe7
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!