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Sato Ryuhei  佐藤 龍平

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佐藤 龍平  サトウ リュウヘイ

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Researcher Number 90867714
Other IDs
Affiliation (Current) 2025: 東京大学, 大学院工学系研究科(工学部), 助教
Affiliation (based on the past Project Information) *help 2025: 東京大学, 大学院工学系研究科(工学部), 助教
2023: 東北大学, 材料科学高等研究所, 特任助教
Review Section/Research Field
Principal Investigator
Basic Section 26020:Inorganic materials and properties-related
Except Principal Investigator
Medium-sized Section 26:Materials engineering and related fields
Keywords
Principal Investigator
パーシステントホモロジー / 超イオン伝導 / 協奏的な運動
Except Principal Investigator
生成AI / 分子動力学 / 材料組織予測
  • Research Projects

    (2 results)
  • Research Products

    (3 results)
  • Co-Researchers

    (1 People)
  •  Generative AI-Driven Prediction of Microstructure Formation Using Time-Accelerated Molecular Dynamics

    • Principal Investigator
      澁田 靖
    • Project Period (FY)
      2025 – 2028
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Review Section
      Medium-sized Section 26:Materials engineering and related fields
    • Research Institution
      The University of Tokyo
  •  協奏的イオン輸送機構の数理科学的解明による超イオン伝導材料の新しい指針の構築Principal Investigator

    • Principal Investigator
      佐藤 龍平
    • Project Period (FY)
      2023 – 2025
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 26020:Inorganic materials and properties-related
    • Research Institution
      Tohoku University

All 2024 2023

All Journal Article Presentation

  • [Journal Article] Data-Driven Viewpoints for Developing Next-Generation Mg-Ion Solid-State Electrolytes2024

    • Author(s)
      Fangling Yang, Ryuhei Sato, Eric Jianfeng Cheng, Kazuaki Kisu, Qian Wang, Xue Jia, Shin-ichi Orimo, and Hao Li
    • Journal Title

      Journal of Electrochemistry

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K13542
  • [Presentation] データ同化及び数理科学的手法を用いた材料解析2023

    • Author(s)
      佐藤 龍平, 赤木 和人, 高木 成幸, Sau Kartik, 木須 一彰, Li Hao, 折茂 慎一
    • Organizer
      日本MRS水素科学技術連携研究会 2023年度 前期研究会
    • Invited
    • Data Source
      KAKENHI-PROJECT-23K13542
  • [Presentation] Topological Data Analysis Based on Persistent Homology for the Superionic Conductors2023

    • Author(s)
      R. Sato, K. Akagi, S. Takagi, K. Sau, K. Kisu, H. Li, S. Orimo
    • Organizer
      Materials Research Meetings 2023
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13542
  • 1.  澁田 靖 (90401124)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results

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