Predicting the Redox Potentials of Phenazine Derivatives Using DFT-Assisted Machine Learning

[Image: see text] This study investigates four machine-learning (ML) models to predict the redox potentials of phenazine derivatives in dimethoxyethane using density functional theory (DFT). A small data set of 151 phenazine derivatives having only one type of functional group per molecule (20 uniqu...

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Detalles Bibliográficos
Autores principales: Ghule, Siddharth, Dash, Soumya Ranjan, Bagchi, Sayan, Joshi, Kavita, Vanka, Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017108/
https://www.ncbi.nlm.nih.gov/pubmed/35449912
http://dx.doi.org/10.1021/acsomega.1c06856

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017108/
https://www.ncbi.nlm.nih.gov/pubmed/35449912
http://dx.doi.org/10.1021/acsomega.1c06856

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