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

Author(s)
Dorothea Golze, Markus Hirvensalo, Patricia Hernandez-Leon, Anja Aarva, Jarkko Etula, Toma Susi, Patrick Rinke, Tomi Laurila, Miguel A. Caro
Organisation(s)
Physics of Nanostructured Materials
External organisation(s)
Aalto University, Technische Universität Dresden
Journal
Chemistry of Materials
Volume
34
Pages
6240-6254
No. of pages
15
ISSN
0897-4756
DOI
https://doi.org/10.1021/acs.chemmater.1c04279
Publication date
2021
Peer reviewed
Yes
Austrian Fields of Science 2012
104026 Spectroscopy, 103018 Materials physics
Keywords
ASJC Scopus subject areas
Materials Chemistry, Chemical Engineering(all), Chemistry(all)
Portal url
https://ucrisportal.univie.ac.at/en/publications/accurate-computational-prediction-of-coreelectron-binding-energies-in-carbonbased-materials-a-machinelearning-model-combining-densityfunctional-theory-and-gw(b5b6a1c0-0a0c-4cbf-9c07-211c70bb903f).html