Machine learning and DFT investigation of CO, CO<sub>2</sub> and CH<sub>4</sub> adsorption on pristine and defective two-dimensional magnesene

Titel:: Machine learning and DFT investigation of CO, CO₂ and CH₄ adsorption on pristine and defective two-dimensional magnesene
Dokumenttyp:: Zeitschriftenaufsatz
Autor(en):: Thomas, Siby; Mayr, Felix; Kulangara Madam, Ajith; Gagliardi, Alessio
Zeitschriftentitel:: Physical Chemistry Chemical Physics
Jahr:: 2023
Band / Volume:: 25
Heft / Issue:: 18
Seitenangaben Beitrag:: 13170-13182
Volltext / DOI:: doi:10.1039/d3cp00613a
Verlag / Institution:: Royal Society of Chemistry (RSC)
E-ISSN:: 1463-90761463-9084
Publikationsdatum:: 01.01.2023
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Machine learning and DFT investigation of CO, CO2 and CH4 adsorption on pristine and defective two-dimensional magnesene