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

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Title:: Machine learning and DFT investigation of CO, CO₂ and CH₄ adsorption on pristine and defective two-dimensional magnesene
Document type:: Zeitschriftenaufsatz
Author(s):: Thomas, Siby; Mayr, Felix; Kulangara Madam, Ajith; Gagliardi, Alessio
Journal title:: Physical Chemistry Chemical Physics
Year:: 2023
Journal volume:: 25
Journal issue:: 18
Pages contribution:: 13170-13182
Fulltext / DOI:: doi:10.1039/d3cp00613a
Publisher:: Royal Society of Chemistry (RSC)
E-ISSN:: 1463-90761463-9084
Date of publication:: 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