Exploration of organic superionic glassy conductors by process and materials informatics with lossless graph database

Kan Hatakeyama-Sato*, Momoka Umeki, Hiroki Adachi, Naoaki Kuwata, Gen Hasegawa, Kenichi Oyaizu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Data-driven material exploration is a ground-breaking research style; however, daily experimental results are difficult to record, analyze, and share. We report a data platform that losslessly describes the relationships of structures, properties, and processes as graphs in electronic laboratory notebooks. As a model project, organic superionic glassy conductors were explored by recording over 500 different experiments. Automated data analysis revealed the essential factors for a remarkable room temperature ionic conductivity of 10−4–10−3 S cm−1 and a Li+ transference number of around 0.8. In contrast to previous materials research, everyone can access all the experimental results, including graphs, raw measurement data, and data processing systems, at a public repository. Direct data sharing will improve scientific communication and accelerate integration of material knowledge.

Original languageEnglish
Article number170
Journalnpj Computational Materials
Volume8
Issue number1
DOIs
Publication statusPublished - 2022 Dec

ASJC Scopus subject areas

  • Modelling and Simulation
  • Materials Science(all)
  • Mechanics of Materials
  • Computer Science Applications

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