Liu Chang 劉暢

Researcher Number	30814149
Other IDs
Affiliation (Current)	2025: 統計数理研究所, 先端データサイエンス研究系, 特任助教
Affiliation (based on the past Project Information) *help	2023: 統計数理研究所, 先端データサイエンス研究系, 特任助教 2020 – 2022: 統計数理研究所, ものづくりデータ科学研究センター, 特任助教
Review Section/Research Field	Principal Investigator Basic Section 61030:Intelligent informatics-related
Keywords	Principal Investigator データベース / 無機材料 / 合成可能性 / マテリアルズ・インフォマティクス / 構造予測 / 機械学習 / 記述子データベース / 準結晶 / ハイエントロピー合金 / モデルライブラリー … More / 新規準結晶探索 / マテリアルズインフォマティクス / 結晶構造予測 / 物性予測 / スモールデータ / 転移学習 Less

Construction of an unbiased and synthesizable inorganic database from data-drivenPrincipal Investigator
- Principal Investigator
  
  劉暢
- Project Period (FY)
  2023 – 2025
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  The Institute of Statistical Mathematics
Transfer learning to predict the properties of compounds: pre-trained model libraryPrincipal Investigator
- Principal Investigator
  
  Liu Chang
- Project Period (FY)
  2020 – 2022
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  The Institute of Statistical Mathematics

All 2023 2022 2021

All Journal Article Presentation Book

[Book] マテリアルズインフォマティクス2022
- Author(s)
  伊藤聡、吉田亮、劉暢、Stephen Wu、野口瑶、山田寛尚、赤木和人、大林一平、山下智樹
- Total Pages
  202
- Publisher
  共立出版
- ISBN
  9784320072022
- Data Source
  KAKENHI-PROJECT-20K19866
[Journal Article] Quasicrystals predicted and discovered by machine learning2023
- Author(s)
  Liu Chang、Kitahara Koichi、Ishikawa Asuka、Hiroto Takanobu、Singh Alok、Fujita Erina、Katsura Yukari、Inada Yuki、Tamura Ryuji、Kimura Kaoru、Yoshida Ryo
- Journal Title
  
  Physical Review Materials
  
  Volume: 7 Issue: 9 Pages: 093805-093805
- DOI
  10.1103/physrevmaterials.7.093805
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-23K16955, KAKENHI-PLANNED-19H05818, KAKENHI-PLANNED-19H05820, KAKENHI-PROJECT-19H01132
[Journal Article] Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns2023
- Author(s)
  Uryu Hirotaka、Yamada Tsunetomo、Kitahara Koichi、Singh Alok、Iwasaki Yutaka、Kimura Kaoru、Hiroki Kanta、Miyao Naoya、Ishikawa Asuka、Tamura Ryuji、Ohhashi Satoshi、Liu Chang、Yoshida Ryo
- Journal Title
  
  Advanced Science
  
  Volume: 11 Issue: 1 Pages: 2304546-2304546
- DOI
  10.1002/advs.202304546
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-23K16955, KAKENHI-PLANNED-19H05818, KAKENHI-PLANNED-19H05820, KAKENHI-PROJECT-19H01132
[Journal Article] Descriptors of intrinsic hydrodynamic thermal transport: screening a phonon database in a machine learning approach2022
- Author(s)
  Torres Pol、Wu Stephen、Ju Shenghong、Liu Chang、Tadano Terumasa、Yoshida Ryo、Shiomi Junichiro
- Journal Title
  
  Journal of Physics: Condensed Matter
  
  Volume: 34 Issue: 13 Pages: 135702-135702
- DOI
  10.1088/1361-648x/ac49c9
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18017, KAKENHI-PROJECT-19K14902, KAKENHI-PROJECT-19H00744, KAKENHI-PROJECT-21K14675, KAKENHI-PROJECT-19H01132, KAKENHI-PROJECT-20K19866, KAKENHI-PLANNED-19H05820
[Journal Article] Exploring diamondlike lattice thermal conductivity crystals via feature-based transfer learning2021
- Author(s)
  Ju Shenghong、Yoshida Ryo、Liu Chang、Wu Stephen、Hongo Kenta、Tadano Terumasa、Shiomi Junichiro
- Journal Title
  
  Physical Review Materials
  
  Volume: 5 Issue: 5 Pages: 053801-053801
- DOI
  10.1103/physrevmaterials.5.053801
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K19866, KAKENHI-PROJECT-18K18017, KAKENHI-PROJECT-19K14902, KAKENHI-PLANNED-19H05820, KAKENHI-PROJECT-19H00744, KAKENHI-PROJECT-21K14675, KAKENHI-PROJECT-19H01132
[Journal Article] Machine learning to predict quasicrystals from chemical compositions2021
- Author(s)
  Liu, C., Fujita, E., Katsura, Y., Inada, Y., Ishikawa, A., Tamura, R., Kimura, K., Yoshida, R.
- Journal Title
  
  Advanced Materials
  
  Volume: 33 Issue: 36 Pages: 2102507-2102507
- DOI
  10.1002/adma.202102507
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PLANNED-19H05820, KAKENHI-PROJECT-20K19866, KAKENHI-PROJECT-19H01132, KAKENHI-ORGANIZER-19H05817, KAKENHI-PLANNED-19H05818
[Presentation] 反復計算を必要としない結晶構造予測2023
- Author(s)
  Chang Liu
- Organizer
  第33回日本MRS年次大会 (2023)
- Data Source
  KAKENHI-PROJECT-23K16955

1. YOSHIDA Ryo

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
2. KATSURA Yukari

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
3. Wu Stephen

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Liu Chang 劉 暢

Research Projects

Research Products

Co-Researchers

Construction of an unbiased and synthesizable inorganic database from data-drivenPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Transfer learning to predict the properties of compounds: pre-trained model libraryPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Book] マテリアルズインフォマティクス2022

Author(s)

Total Pages

Publisher

ISBN

Data Source

[Journal Article] Quasicrystals predicted and discovered by machine learning2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Deep Learning Enables Rapid Identification of a New Quasicrystal from Multiphase Powder Diffraction Patterns2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Descriptors of intrinsic hydrodynamic thermal transport: screening a phonon database in a machine learning approach2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Exploring diamondlike lattice thermal conductivity crystals via feature-based transfer learning2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Machine learning to predict quasicrystals from chemical compositions2021

Author(s)

Journal Title

DOI

Data Source

[Presentation] 反復計算を必要としない結晶構造予測2023

Author(s)

Organizer

Data Source

Liu Chang 劉暢