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Ab Initio Calculations of the Redox Potentials of Additives for Lithium-Ion Batteries and Their Prediction through Machine Learning

[Image: see text] Ab initio molecular orbital calculations were carried out to examine the redox potentials of 149 electrolyte additives for lithium-ion batteries. These potentials were employed to construct regression models using a machine learning approach. We chose simple descriptors based on th...

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Detalles Bibliográficos
Autores principales: Okamoto, Yasuharu, Kubo, Yoshimi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644342/
https://www.ncbi.nlm.nih.gov/pubmed/31458929
http://dx.doi.org/10.1021/acsomega.8b00576
Descripción
Sumario:[Image: see text] Ab initio molecular orbital calculations were carried out to examine the redox potentials of 149 electrolyte additives for lithium-ion batteries. These potentials were employed to construct regression models using a machine learning approach. We chose simple descriptors based on the chemical structure of the additive molecules. The descriptors predicted the redox potentials well, in particular, the oxidation potentials. We found that the redox potentials can be explained by a small number of features, which improve the interpretability of the results and seem to be related to the amplitude of the eigenstate of the frontier orbitals.