@article{62440aad03324f9e80e4a81f29e28a77,
title = "Li-ion conductive Li3PO4-Li3BO3-Li2SO4 mixture: Prevision through density functional molecular dynamics and machine learning",
keywords = "Li-ion conductor, Machine learning, Molecular dynamics",
author = "Masato Sumita and Ryo Tamura and Kenji Homma and Chioko Kaneta and Koji Tsuda",
note = "Funding Information: RT and KT were partially supported by the “Materials Research by Information Integration” Initiative (MI2I) project and Core Research for Evolutional Science and Technology (CREST) [Grants JPMJCR1502 and JPMJCR17J2] from the Japan Science and Technology Agency (JST). KT was also supported by a Grant-in-Aid for Scientific Research on Innovative Areas “Nano Informatics” [Grant 25106005] from the Japan Society for the Promotion of Science (JSPS) and the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) as a “Priority Issue on Post-K Computer” (Building Innovative Drug Discovery Infrastructure through Functional Control of Biomolecular Systems). The computations in this work were carried out at the supercomputer centers of NIMS and ISSP, The University of Tokyo.",
year = "2019",
doi = "10.1246/bcsj.20190041",
language = "English",
volume = "92",
pages = "1100--1106",
journal = "Bulletin of the Chemical Society of Japan",
issn = "0009-2673",
publisher = "The Chemical Society of Japan",
number = "6",
}