Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and <i>GW</i>.

Golze, Dorothea; Hirvensalo, Markus; Hernández-León, Patricia; Aarva, Anja; Etula, Jarkko; Susi, Toma; Rinke, Patrick; Laurila, Tomi; Caro, Miguel A

Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW.

Golze, Dorothea; Hirvensalo, Markus; Hernández-León, Patricia; Aarva, Anja; Etula, Jarkko; Susi, Toma; Rinke, Patrick; Laurila, Tomi; Caro, Miguel A.

Afiliação

Golze D; Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062 Dresden, Germany.
Hirvensalo M; Department of Applied Physics, Aalto University, 02150 Espoo, Finland.
Hernández-León P; Department of Applied Physics, Aalto University, 02150 Espoo, Finland.
Aarva A; Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland.
Etula J; Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland.
Susi T; Department of Chemistry and Materials Science, Aalto University, 02150 Espoo, Finland.
Rinke P; University of Vienna, Faculty of Physics, Boltzmanngasse 5, 1090 Vienna, Austria.
Laurila T; Department of Applied Physics, Aalto University, 02150 Espoo, Finland.
Caro MA; Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland.

Chem Mater ; 34(14): 6240-6254, 2022 Jul 26.

Article em En | MEDLINE | ID: mdl-35910537

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article