Updated on 2025/09/26

Information

 

写真a

 
TSUJIKAWA KOTA
 
Organization
Kyushu University Platform of Inter/Transdisciplinary Energy Research Academic Researcher
Title
Academic Researcher
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Papers

  • Mitigating proton trapping in cubic perovskite oxides via ScO<sub>6</sub> octahedral networks

    Tsujikawa, K; Hyodo, J; Fujii, S; Takahashi, K; Tomita, Y; Shi, N; Murakami, Y; Kasamatsu, S; Yamazaki, Y

    NATURE MATERIALS   2025.8   ISSN:1476-1122 eISSN:1476-4660

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    Language:English   Publisher:Nature Materials  

    Advances in electrochemical devices have been primarily driven by the discovery and development of electrolyte materials. Yet the development of high-performance and chemically stable proton-conducting oxide electrolytes remains a challenge due to proton trapping and the resulting trade-offs between ionic carrier concentration and conductivity in doped oxides. Here we demonstrate that cubic perovskite oxides with heavy Sc doping can overcome these limitations. BaSn<inf>0.3</inf>Sc<inf>0.7</inf>O<inf>3–δ</inf> and BaTi<inf>0.2</inf>Sc<inf>0.8</inf>O<inf>3–δ</inf> are found to exceed the technological threshold of a total proton conductivity of 0.01 S cm<sup>−1</sup> for fuel cell electrolytes at 300 °C. The structural stability of BaSn<inf>0.3</inf>Sc<inf>0.7</inf>O<inf>3–δ</inf> is further validated under harsh chemical and fuel cell conditions. Molecular dynamics simulations using a machine learning force field illustrate rapid proton diffusion pathways along the ScO<inf>6</inf> octahedral network, effectively mitigating proton trapping, while protons are preferentially associated with Sc. Lattice softness is proposed as a primary design descriptor for increasing Sc content in perovskite oxides and developing high-performance electrolytes for electrochemical devices.

    DOI: 10.1038/s41563-025-02311-w

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Research Projects

  • 開発者と機械の相互解釈支援システム構築による材料開発の加速化

    Grant number:23K19187  2023 - 2024

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Research Activity start-up

    辻川 皓太

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    Authorship:Principal investigator  Grant type:Scientific research funding

    材料物性予測モデルの活用は、著しく材料探索を加速させる。
    しかし、予測モデル構築には訓練データ取得プロセスが必要であり、本プロセス時間を考慮して材料開発期間が短縮されたかは不明である。
    本研究では、材料物性予測モデル構築をアシストするシステムを開発し、正味の材料開発期間を短縮させる。物性予測の重要記述子を提案、予測モデルの適用範囲を効率的に広げるサンプリング方法により、材料開発者の記述子‐物性相関の解釈性を支援する。開発した支援システムをプロトン伝導性酸化物探索へ適用し、2年という短期間で高性能な予測モデルと新規高プロトン伝導体を創出し、燃料電池開発を促進する。

    CiNii Research