Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials
Sign Up to like & getrecommendations! Published in 2020 at "Chemistry of Materials"
DOI: 10.1021/acs.chemmater.0c00768
Abstract: We employed density functional theory (DFT) to compute oxidation potentials of 1400 homobenzylic ether molecules to search for the ideal sustainable redoxmer design. The generated data were used to construct an active learning model based… read more here.
Keywords: active learning; quantum chemistry; chemistry; learning accelerate ... See more keywords
Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.1c01201
Abstract: Cationic cobaltocenium derivatives are promising components of the anion exchange membranes because of their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here, we present an efficient modeling approach to… read more here.
Keywords: chemistry informed; chemistry; substituted cobaltocenium; cobaltocenium ... See more keywords
Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery
Sign Up to like & getrecommendations! Published in 2023 at "ACS Central Science"
DOI: 10.1021/acscentsci.2c01123
Abstract: Solid polymer electrolytes (SPEs) have the potential to improve lithium-ion batteries by enhancing safety and enabling higher energy densities. However, SPEs suffer from significantly lower ionic conductivity than liquid and solid ceramic electrolytes, limiting their… read more here.
Keywords: chemistry informed; chemistry; model; informed machine ... See more keywords