A Machine Learning Model of Chemical Shifts for Chemically and Structurally Diverse Molecular Solids.

Cordova, Manuel; Engel, Edgar A; Stefaniuk, Artur; Paruzzo, Federico; Hofstetter, Albert; Ceriotti, Michele; Emsley, Lyndon

Cordova, Manuel; Engel, Edgar A; Stefaniuk, Artur; Paruzzo, Federico; Hofstetter, Albert; Ceriotti, Michele; Emsley, Lyndon.

Afiliação

Cordova M; Laboratory of Magnetic Resonance, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
Engel EA; National Centre for Computational Design and Discovery of Novel Materials MARVEL, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
Stefaniuk A; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, J. J. Thomson Avenue, Cambridge CB3 0HE, U.K.
Paruzzo F; Laboratory of Magnetic Resonance, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
Hofstetter A; Laboratory of Magnetic Resonance, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
Ceriotti M; Laboratory of Magnetic Resonance, Institute of Chemical Sciences and Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.
Emsley L; National Centre for Computational Design and Discovery of Novel Materials MARVEL, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.

J Phys Chem C Nanomater Interfaces ; 126(39): 16710-16720, 2022 Oct 06.

Article em En | MEDLINE | ID: mdl-36237276

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Phys Chem C Nanomater Interfaces Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Suíça

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google