A Capacity-Prediction Model for Exploration of Organic Anodes: Discovery of 5-Formylsalicylic Acid as a High-Performance Anode Active Material

Takumi Komura, Kosuke Sakano, Yasuhiko Igarashi, Hiromichi Numazawa, Hiroaki Imai, Yuya Oaki

研究成果: Article査読

1 被引用数 (Scopus)

抄録

Development of high-performance organic energy storage is one of the important challenges in recent materials science. Molecular design and synthesis have potential for enhancement of the performances. Efficient exploration and design of the molecules are required in a wide search space. In the present work, a capacity prediction model for organic anodes was constructed on small experimental data by sparse modeling, a method of machine learning, combined with our chemical insights. The straightforward linear regression model facilitated discovery of a high-performance active material for organic anodes in a limited number of experiments. A recommended compound, 5-formylsalicylic acid (SA-CHO), showed one of the highest performances in recent works, i.e., a specific capacity of 873 mA h g-1at 100 mA g-1(sample number: n = 3) with rate performance and cycle stability. The model can be applied to explore organic anode active materials with higher specific capacity.

本文言語English
ページ(範囲)8990-8998
ページ数9
ジャーナルACS Applied Energy Materials
5
7
DOI
出版ステータスPublished - 2022 7月 25

ASJC Scopus subject areas

  • 化学工学(その他)
  • エネルギー工学および電力技術
  • 電気化学
  • 材料化学
  • 電子工学および電気工学

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