Decoding energy decomposition analysis : Machine-learned Insights on the impact of the density functional on the bonding analysis

© 2023 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 45(2024), 7 vom: 15. März, Seite 368-376
1. Verfasser: Oestereich, Toni (VerfasserIn)
Weitere Verfasser: Tonner-Zech, Ralf, Westermayr, Julia
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article chemical bonding density functional theory energy decomposition analysis feature importance analysis machine learning
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520 |a The concept of chemical bonding is a crucial aspect of chemistry that aids in understanding the complexity and reactivity of molecules and materials. However, the interpretation of chemical bonds can be hindered by the choice of the theoretical approach and the specific method utilized. This study aims to investigate the effect of choosing different density functionals on the interpretation of bonding achieved through energy decomposition analysis (EDA). To achieve this goal, a data set was created, representing four bonding groups and various combinations of functionals and dispersion correction schemes. The calculations showed significant variation among the different functionals for the EDA terms, with the dispersion correction terms exhibiting the highest variability. More information was extracted by using machine learning in combination with dimensionality reduction on the data set. Results indicate that, despite the differences in the EDA terms obtained from different functionals, the functional has the least significant impact, suggesting minimal influence on the bonding interpretation 
650 4 |a Journal Article 
650 4 |a chemical bonding 
650 4 |a density functional theory 
650 4 |a energy decomposition analysis 
650 4 |a feature importance analysis 
650 4 |a machine learning 
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700 1 |a Westermayr, Julia  |e verfasserin  |4 aut 
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