npj Computational Materials (Aug 2022)

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

DOI
https://doi.org/10.1038/s41524-022-00853-0
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 8

Abstract

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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.