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Filtering by: Creator TATEYAMA, Yoshitaka Visibility open

1. Machine learning prediction of coordination energies for alkali group elements in battery electrolyte solvents

Description/Abstract:: We combined a data science-driven method with quantum chemistry calculations, and applied it to the battery electrolyte problem. We perfo...
Keyword:: electrolyte, battery, and quantum chemistry
Resource Type:: Dataset
Data origin:: simulations
Author:: ISHIKAWA, Atsushi, SODEYAMA, Keitaro, IGARASHI, Yasuhiko, NAKAYAMA, Tomofumi, TATEYAMA, Yoshitaka, and OKADA, Masato
Journal:: Physical Chemistry Chemical Physics
Date Uploaded:: 24/09/2021
Date Modified:: 01/10/2021

2. Liquid electrolyte informatics using an exhaustive search with linear regression

Description/Abstract:: Exploring new liquid electrolyte materials is a fundamental target for developing new high-performance lithium-ion batteries. In contrast...
Keyword:: Gaussian09, Li-ion battery, materials informatics, molecules, organic solvents, and quantum chemistry calculations
Material/Specimen:: organic solvents
Resource Type:: Dataset
Data origin:: simulations
Author:: SODEYAMA, Keitaro, IGARASHI, Yasuhiko, NAKAYAMA, Tomofumi, TATEYAMA, Yoshitaka, and OKADA, Masato
Journal:: Physical Chemistry Chemical Physics
Date Uploaded:: 09/09/2020
Date Modified:: 30/06/2021