Sato Ryuhei 佐藤龍平

Researcher Number	90867714
Other IDs
Affiliation (Current)	2026: 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	2024 – 2026: 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 26010:Metallic material properties-related / 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 / 協奏的な運動 / 超イオン伝導 / 協奏的な輸送 Except Principal Investigator 生成AI / 分子動力学 / 材料組織予測

機械学習ポテンシャル分子動力学計算による新規材料合成経路の理論予測Principal Investigator
- Principal Investigator
  
  佐藤龍平
- Project Period (FY)
  2026 – 2028
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 26010:Metallic material properties-related
- Research Institution
  The University of Tokyo
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
  The University of Tokyo
  Tohoku University

All 2025 2024 2023

All Journal Article Presentation

[Journal Article] Unraveling the Complexity of Divalent Hydride Electrolytes in Solid‐State Batteries via a Data‐Driven Framework with Large Language Model2025
- Author(s)
  Wang Qian、Yang Fangling、Wang Yuhang、Zhang Di、Sato Ryuhei、Zhang Linda、Cheng Eric Jianfeng、Yan Yigang、Chen Yungui、Kisu Kazuaki、Orimo Shin‐ichi、Li Hao
- Journal Title
  
  Angewandte Chemie International Edition
  
  Volume: - Issue: 25
- DOI
  10.1002/anie.202506573
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-23K13703, KAKENHI-PROJECT-23K13542, KAKENHI-PROJECT-24K23068
[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
[Journal Article] Unlocking the secrets of ideal fast ion conductors for all-solid-state batteries2024
- Author(s)
  Sau Kartik、Takagi Shigeyuki、Ikeshoji Tamio、Kisu Kazuaki、Sato Ryuhei、dos Santos Egon Campos、Li Hao、Mohtadi Rana、Orimo Shin-ichi
- Journal Title
  
  Communications Materials
  
  Volume: 5 Issue: 1
- DOI
  10.1038/s43246-024-00550-z
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-23K26372, KAKENHI-PROJECT-23K13542
[Presentation] 超イオン伝導材料解析のためのパーシステンスホモロジー解析2024
- Author(s)
  佐藤龍平
- Organizer
  固体イオニクスセミナー
- 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
2. LI HAO

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
3. 高木成幸

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Sato Ryuhei 佐藤 龍平

Research Projects

Research Products

Co-Researchers

機械学習ポテンシャル分子動力学計算による新規材料合成経路の理論予測Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Generative AI-Driven Prediction of Microstructure Formation Using Time-Accelerated Molecular Dynamics

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

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

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Unraveling the Complexity of Divalent Hydride Electrolytes in Solid‐State Batteries via a Data‐Driven Framework with Large Language Model2025

Author(s)

Journal Title

DOI

Data Source

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

Author(s)

Journal Title

Data Source

[Journal Article] Unlocking the secrets of ideal fast ion conductors for all-solid-state batteries2024

Author(s)

Journal Title

DOI

Data Source

[Presentation] 超イオン伝導材料解析のためのパーシステンスホモロジー解析2024

Author(s)

Organizer

Data Source

[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)

Organizer

Data Source

[Presentation] Topological Data Analysis Based on Persistent Homology for the Superionic Conductors2023

Author(s)

Organizer

Data Source

Sato Ryuhei 佐藤龍平