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Computational design of functional core using informatics approaches

Planned

Project AreaNew Materials Science on Nanoscale Structures and Functions of Crystal Defect Cores
Project/Area Number 19H05787
Research Category

Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

Allocation TypeSingle-year Grants
Review Section Science and Engineering
Research InstitutionThe University of Tokyo

Principal Investigator

溝口 照康  東京大学, 生産技術研究所, 教授 (70422334)

Co-Investigator(Kenkyū-buntansha) 世古 敦人  京都大学, 工学研究科, 准教授 (10452319)
柴田 基洋  東京大学, 生産技術研究所, 助教 (40780151)
豊浦 和明  京都大学, 工学研究科, 准教授 (60590172)
Project Period (FY) 2019-06-28 – 2024-03-31
Project Status Granted (Fiscal Year 2022)
Budget Amount *help
¥130,000,000 (Direct Cost: ¥100,000,000、Indirect Cost: ¥30,000,000)
Fiscal Year 2022: ¥24,700,000 (Direct Cost: ¥19,000,000、Indirect Cost: ¥5,700,000)
Fiscal Year 2021: ¥26,000,000 (Direct Cost: ¥20,000,000、Indirect Cost: ¥6,000,000)
Fiscal Year 2020: ¥24,050,000 (Direct Cost: ¥18,500,000、Indirect Cost: ¥5,550,000)
Fiscal Year 2019: ¥33,800,000 (Direct Cost: ¥26,000,000、Indirect Cost: ¥7,800,000)
Keywords機能コア / 界面 / 表面 / 透過型電子顕微鏡 / 機械学習 / 転位 / 情報科学 / シミュレーション / ナノ計測 / インフォマティックス
Outline of Research at the Start

本計画班では,機能コアの構造決定と原子移動経路決定に関する手法を開発する.本計画班で開発した手法を活用し,他班と連携することで機能コアの構造と物性を効率的かつ系統的に決定する.機能コアに関するすべての情報をデータベース化し解析することで,機能コアの物性設計モデルを構築する.本計画班で行う具体的な研究内容は以下のようになっている.
(1) 情報科学手法を活用した機能コア構造・物性決定法の開発
(2) 機能コア物性設計モデルの構築
以上により,「機能コアインフォマティクス」の確立を目指す.

Outline of Annual Research Achievements

これまでの研究で,機械学習を利用することにより,その計算効率を数万倍向上させることに成功している.一方で,ランダム粒界など構造決定が困難な格子欠陥も多数存在している.そこで,格子欠陥の構造決定を伴わずに界面物性を予測する手法の開発に取り組んだ.その結果,粒界構造を記述することが出来る記述子を,バルク構造から抽出することに成功した.
さらに,第一原理計算と情報科学の技法により,高精度な機械学習原子間ポテンシャル(MLIP)を構築する手法を開発し,多くの金属元素におけるMLIPの公開を開始した.また,公募班(JFCC藤井)との連携により,FCC金属やシリコンの結晶粒界における粒界エネルギーや格子熱伝導などを対象に,原子間ポテンシャルの予測が非常に高精度であることを示した.また,班内連携により,シリコン粒界における高温下構造相転移の研究も進めた.その他にも,第一原理計算と情報科学の技法を組み合わせることにより,制約を満たす結晶構造の列挙手法を開発した.
また,物性計算手法として固体内拡散の高精度かつ高効率な解析手法を開発してきた.本手法は,拡散原子のポテンシャルエネルギー曲面 (PES) を“ガウス過程に基づく統計モデル構築”と“マスター方程式に基づく拡散係数の数値解法”を結び付けることで実現した.また,サポートベクターマシンに基づく領域分割を用いて,結晶内のPE極小点を効率的に列挙する手法も別途開発した.
また,機械学習を用いることにより,計測可能なデータからの情報抽出にも取り組んでいる.これまでにA01(ア)班と“アパタイト型酸化物イオン伝導体の伝導機構解析”,A01(ア)班およびA03(オ)班と“窒化リンの高圧合成と振動解析”の連携研究を実施した. また,公募班東大八木班と連携して,”インターカレーションメカニズムの理解”に関する連携研究を実施してきた.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

現在までに,多元系を対象とする原子間ポテンシャルの手法開発を完了し,合計48種の系を対象とした原子間ポテンシャルもすでに公開している.これらを用いて機能コアに関連した系を高精度に計算することが今後可能である.また,格子欠陥構造の高速決定法の開発や,機能コアにおける構造機能相関の解明などに取り組み,成果を上げてきた.さらに,熱と界面との相互作用により生じる構造相転移シミューレションできている.
さらに,これまでの研究で固体内拡散の高精度かつ高効率な解析手法の開発を完了している.また,結晶内における安定・準安定サイトを効率的に探索するニーズに合わせて,サポートベクターマシンに基づく領域分割と勾配法による局所最適化を組み合わせた手法も別途開発している.
また,ナノ計測で取得されるデータと機械学習との連携研究も進めており,これまでに専門の研究者でも得ることが出来ない新しい情報の抽出に成功している.
機械学習を用いた新たな機能コア解析法の開発と,それらの公開,さらに計画班や公募班との機能コアに関連した連携研究も順調に進展しており,学術論文もでている.以上から研究はおおむね順調に進展しているといえる.

Strategy for Future Research Activity

今後は,界面における高温下における熱輸送現象の実験的,計算的研究を進めるとともに,表面吸着特性や,界面物性を理解するための機械学習法の開発を進める.さらに,構築済みの原子間ポテンシャルを用いた大域的構造探索の手法開発を実施する.また,より大規模な機能コア計算を目指し,高精度原子間ポテンシャルの高速化を行う.また,固体内拡散の高精度・高効率解析手法を用いて,各種電気化学デバイスの電解質材料として期待される種々イオン伝導性材料の系統的評価を行う.さらに,Decision Diagramに基づいた結晶構造の列挙手法を用いて,ある制約下での欠陥構造のパターン列挙手法の検討を行う.特に,計測データとの連携も進める.計測データを機械学習により解析し,これまで得ることが出来なかった「機能コア物性マッピング」にも取り組む.
一方で,新型コロナウィルスの状況次第では,情報収集がしにくくなったり,研究打ち合わせの減少による連携不足が予測される.これまで以上にZOOM等のオンライン会議ツールを活用し,班内・班外連携を深める計画である.また,班内や連携先とのSNSによるコミュニケーションも積極的に取り組み,Withコロナ,ポストコロナにおける新しい連携研究法の確立にも取り組む.

Report

(2 results)
  • 2020 Annual Research Report
  • 2019 Annual Research Report

Research Products

(112 results)

All 2021 2020 2019 Other

All Journal Article (31 results) (of which Peer Reviewed: 31 results,  Open Access: 20 results) Presentation (75 results) (of which Int'l Joint Research: 21 results,  Invited: 33 results) Book (3 results) Remarks (3 results)

  • [Journal Article] Revealing Spatial Distribution of Al-Coordinated Species in a Phase-Separated Aluminosilicate Glass by STEM-EELS2020

    • Author(s)
      K. Liao, A. Masuno, A. Taguchi, H. Moriwake, H. Inoue, and T. Mizoguchi
    • Journal Title

      The Journal of Physical Chemistry Letters

      Volume: 11 Pages: 9637-9642

    • DOI

      10.1021/acs.jpclett.0c02687

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Quantum Deep Field: Data-Driven Wave Function, Electron Density Generation, and Atomization Energy Prediction and Extrapolation with Machine Learning2020

    • Author(s)
      Masashi Tsubaki and Teruyasu Mizoguchi
    • Journal Title

      Physical Review Letters

      Volume: 125 Pages: 076402-076402

    • DOI

      10.1103/physrevlett.125.206401

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] In situ observation of the dynamics in the middle stage of spinodal decomposition of a silicate glass via scanning transmission electron microscopy2020

    • Author(s)
      K. Nakazawa, S. Amma, and T. Mizoguchi
    • Journal Title

      Acta Materialia

      Volume: 200 Pages: 720-726

    • DOI

      10.1016/j.actamat.2020.09.036

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Radial distribution function from X-ray absorption near edge structure with an artificial neural network2020

    • Author(s)
      S. Kiyohara and T. Mizoguchi
    • Journal Title

      J. Phys. Soc. Jpn.

      Volume: 89 Issue: 10 Pages: 103001-103001

    • DOI

      10.7566/jpsj.89.103001

    • NAID

      40022375196

    • ISSN
      0031-9015, 1347-4073
    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Local thickness and composition measurements from scanning convergent-beam electron diffraction of a binary non-crystalline material obtained by a pixelated detector2020

    • Author(s)
      K. Nakazawa, K. Shibata, K. Mitsuishi, S. Amma, and T. Mizoguchi
    • Journal Title

      Ultramicroscopy

      Volume: 217 Pages: 113077-113077

    • DOI

      10.1016/j.ultramic.2020.113077

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] EQCM analysis of intercalation species into graphite positive electrodes for Al batteries2020

    • Author(s)
      Yamagata Shingo、Takahara Izumi、Wang Mengqiao、Mizoguchi Teruyasu、Yagi Shunsuke
    • Journal Title

      J. Alloy. Compd.

      Volume: 846 Pages: 156469-156469

    • DOI

      10.1016/j.jallcom.2020.156469

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Learning excited states from ground states by using an artificial neural network2020

    • Author(s)
      Kiyohara Shin、Tsubaki Masashi、Mizoguchi Teruyasu
    • Journal Title

      npj Computational Materials

      Volume: 6 Pages: 1-6

    • DOI

      10.1038/s41524-020-0336-3

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Real-Space Mapping of Oxygen Coordination in Phase-Separated Aluminosilicate Glass: Implication for Glass Stability2020

    • Author(s)
      K. Liao, M. Haruta, A. Masuno, H. Inoue, H. Kurata, and T. Mizoguchi, Y. Ikuhara
    • Journal Title

      ACS Applied Nano Materials

      Volume: 3 Pages: 5053-5060

    • DOI

      10.1021/acsanm.0c00196

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Machine learning approaches for ELNES/XANES2020

    • Author(s)
      Mizoguchi Teruyasu、Kiyohara Shin
    • Journal Title

      Microscopy

      Volume: ー Pages: 92-109

    • DOI

      10.1093/jmicro/dfz109

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Prediction of interface and vacancy segregation energies at silver interfaces without determining interface structures2020

    • Author(s)
      R. Otani, S. Kiyohara, K. Shibata and T. Mizoguchi
    • Journal Title

      Applied Physics Express

      Volume: 13

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] データ駆動型内殻電子励起分光スペクトル(ELNES/XANES)解析2020

    • Author(s)
      溝口照康,清原慎
    • Journal Title

      日本化学会情報化学部会誌

      Volume: 38 Pages: 16-19

    • NAID

      130007960372

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] 結晶界面インフォマティクス:構造決定と構造機能相関2020

    • Author(s)
      大谷龍剣,清原慎,溝口照康
    • Journal Title

      まてりあ

      Volume: 59 Pages: 134-138

    • NAID

      130007804020

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] 機械学習を利用した結晶界面構造決定と構造機能相関2020

    • Author(s)
      溝口照康,清原慎,大谷龍剣
    • Journal Title

      触媒

      Volume: 62 Pages: 35-41

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Sampling strategy in efficient potential energy surface mapping for predicting atomic diffusivity in crystals by machine learning2020

    • Author(s)
      Toyoura Kazuaki、Fujii Takeo、Kanamori Kenta、Takeuchi Ichiro
    • Journal Title

      Physical Review B

      Volume: 101 Pages: 26823-26830

    • DOI

      10.1103/physrevb.101.184117

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Machine-learning-based sampling method for exploring local energy minima of interstitial species in a crystal2020

    • Author(s)
      Toyoura Kazuaki、Kanayama Kansei
    • Journal Title

      Physical Review B

      Volume: 102

    • DOI

      10.1103/physrevb.102.174105

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Prediction of perovskite-related structures in ACuO3-x (A = Ca, Sr, Ba, Sc, Y, La) using density functional theory and Bayesian optimization2020

    • Author(s)
      A. Seko and S. Ishiwata
    • Journal Title

      Physical Review B

      Volume: 101 Pages: 134101-134101

    • DOI

      10.1103/physrevb.101.134101

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Fast material search of lithium ion conducting oxides using a recommender system2020

    • Author(s)
      Suzuki Kota、Ohura Kosei、Seko Atsuto、Iwamizu Yudai、Zhao Guowei、Hirayama Masaaki、Tanaka Isao、Kanno Ryoji
    • Journal Title

      Journal of Materials Chemistry A

      Volume: 8 Pages: 11582-11588

    • DOI

      10.1039/d0ta02556a

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Enumeration of nonequivalent substitutional structures using advanced data structure of binary decision diagram2020

    • Author(s)
      Shinohara Kohei、Seko Atsuto、Horiyama Takashi、Ishihata Masakazu、Honda Junya、Tanaka Isao
    • Journal Title

      The Journal of Chemical Physics

      Volume: 153 Pages: 104109-104109

    • DOI

      10.1063/5.0021663

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Application of machine learning potentials to predict grain boundary properties in fcc elemental metals2020

    • Author(s)
      Takayuki Nishiyama, Atsuto Seko, and Isao Tanaka
    • Journal Title

      Phys. Rev. Materials 4, 123607 (2020)

      Volume: 4 Pages: 123607-123607

    • DOI

      10.1103/physrevmaterials.4.123607

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Machine learning potentials for multicomponent systems: The Ti-Al binary system2020

    • Author(s)
      Seko Atsuto
    • Journal Title

      Physical Review B

      Volume: 102 Pages: 174104-174104

    • DOI

      10.1103/physrevb.102.174104

    • NAID

      120006898049

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] 機械学習を用いた物質界面構造の高速決定2019

    • Author(s)
      清原慎,溝口照康
    • Journal Title

      表面と真空

      Volume: 62 Pages: 130-135

    • NAID

      130007609069

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 走査透過型電子顕微鏡法によるガラス,イオン液体,および気体の構造解析2019

    • Author(s)
      溝口照康,宮田智衆,清原慎,中澤克昭,杉森悠貴
    • Journal Title

      セラミックス

      Volume: 54 Pages: 66-71

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Vibrational Effects in X-ray Absorption Spectra of 2D Layered Materials2019

    • Author(s)
      W. Olovsson, T. Mizoguchi, M. Magnuson, S. Kontur, A. Togo, O. Hellman, I. Tanaka, and C. Draxl
    • Journal Title

      J. Phys. Chem.

      Volume: C 123

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Atomic-scale investigation of the heterogeneous structure and ionic distribution in an ionic liquid using scanning transmission electron microscopy2019

    • Author(s)
      Y. Sugimori, T. Miyata, H. Hashiguchi, E. Okunishi, and T. Mizoguchi
    • Journal Title

      RSC Advances

      Volume: 9 Pages: 10520-10527

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Quantitative estimation of properties from core-loss spectrum via neural network2019

    • Author(s)
      S. Kiyohara, M. Tsubaki, Kunyen Liao, and T. Mizoguchi
    • Journal Title

      J. Phys.: Materials

      Volume: 2

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Machine learning for structure determination and investigating the structure-property relationships of interfaces2019

    • Author(s)
      H. Oda, S. Kiyohara and T. Mizoguchi
    • Journal Title

      J. Phys.: Materials,

      Volume: 2

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 機械学習を活用した界面構造探索とスペクトル解析2019

    • Author(s)
      清原慎,溝口照康
    • Journal Title

      人工知能

      Volume: 34巻 3号 Pages: 345-350

    • NAID

      130007917611

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] EELSと第一原理計算によるエキシトン,原子振動および van derWaals 力の解析2019

    • Author(s)
      溝口照康,清原慎
    • Journal Title

      セラミックス

      Volume: 54 Pages: 456-463

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 機械学習を活用したスペクトル解析2019

    • Author(s)
      溝口照康,清原慎
    • Journal Title

      Isotope News

      Volume: 764 Pages: 20-23

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 機械学習を活用した結晶界面研究2019

    • Author(s)
      溝口照康
    • Journal Title

      応用物理学会誌

      Volume: 88 Pages: 745-749

    • NAID

      130007742920

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 機械学習を活用した結晶界面構造決定2019

    • Author(s)
      溝口照康,清原慎
    • Journal Title

      錯体学会誌

      Volume: 74 Pages: 59-62

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Presentation] 電子エネルギー損失分光法によるセラミック中熱膨張率の局所解析2021

    • Author(s)
      廖クン硯, 柴田基洋, 溝口照康
    • Organizer
      日本セラミックス協会2021年年会
    • Related Report
      2020 Annual Research Report
  • [Presentation] ダイヤモンド構造材料の対称傾角粒界における準安定構造の相転移2021

    • Author(s)
      謝耀枢, 柴田基洋, 溝口照康
    • Organizer
      日本セラミックス協会2021年年会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 炭素 K 端 ELNES/XANES を記述子とした分子物性予測2021

    • Author(s)
      菊政翔、清原慎、柴田基洋、溝口照康
    • Organizer
      日本セラミックス協会2021年年会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 結合前の電子状態から結合物性を予測する機械学習モデルの開発2021

    • Author(s)
      鈴木叡輝、柴田基洋、溝口照康
    • Organizer
      日本セラミックス協会2021年年会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 格子欠陥とアート2021

    • Author(s)
      溝口照康
    • Organizer
      インスピ #1
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] 機械学習を用いたEELSスペクトルの解析2021

    • Author(s)
      溝口照康
    • Organizer
      NIMS先端計測シンポジウム
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] Data-driven analysis of XAFS and EELS2021

    • Author(s)
      溝口照康
    • Organizer
      日本化学会春季大会
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] Prediction of Change of DOS Associated with Bond Formation Using Machine Learning2020

    • Author(s)
      E. Suzuki, K. Shibata and T. Mizogichi,
    • Organizer
      2020 MRS Fall Meetings & Exhibits
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Non-spectroscopic method for simultaneous determinations of thickness and composition of amorphous materials via 4D-STEM2020

    • Author(s)
      K. Nakazawa, K. Mitsuishi, S. Amma, K. Shibata and T. Mizoguchi,
    • Organizer
      Microscopy & Microanalysis(M&M2020)
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Probing Thermal Expansion Coefficient of SrTiO3 Grain Boundaries by In-Situ STEM-EELS2020

    • Author(s)
      K. Liao, K. Shibata, T. Mizoguchi
    • Organizer
      2020 MRS Fall Meetings & Exhibits
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Nano-meter Scale Observation of Local Network Structure in Aluminosilicate Glass via Vibrational EELS2020

    • Author(s)
      K. Liao, A. Masuno, H. Inoue, T. Mizoguchi
    • Organizer
      Microscopy and Microanalysis(M&M2020)
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Quantitative prediction of organic molecular properties from ELNES via artificial neural network2020

    • Author(s)
      K. Kikumasa, S. Kiyohara, K. Shibata and T. Mizoguchi
    • Organizer
      Microscopy & Microanalysis (M&M2020)
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Neural Network Approach for Predicting Organic Molecular Properties from core-loss spectroscopy2020

    • Author(s)
      K. Kikumasa, S. Kiyohara, K. Shibata and T. Mizoguchi
    • Organizer
      2020 MRS Fall Meetings & Exhibits
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 4D-STEMを用いた非晶質の組成・試料厚同時マッピング2020

    • Author(s)
      中澤克昭, 安間伸一, 溝口照康
    • Organizer
      公益社団法人日本顕微鏡学会第76回学術講演会
    • Related Report
      2020 Annual Research Report
  • [Presentation] ニューラルネットワークを用いた炭素K端ELNES/XANESからの物性予測2020

    • Author(s)
      菊政翔,清原慎,柴田基洋,溝口照康
    • Organizer
      第67回応用物理学会春季学術講演会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 機械学習を用いた原子結合及び状態密度の予測2020

    • Author(s)
      鈴木叡輝、柴田基洋、溝口照康
    • Organizer
      日本金属学会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 機械学習を用いた結合形成に伴う状態密度変化の予測2020

    • Author(s)
      鈴木叡輝、柴田基洋、溝口照康
    • Organizer
      第81回応用物理学会秋季学術講演会
    • Related Report
      2020 Annual Research Report
  • [Presentation] ダイヤモンド型構造における安定・準安定粒界相の探索(Determination of Stable and Meta-stable Grain Boundary Phases in Diamond-structured Materials)2020

    • Author(s)
      謝耀枢,溝口照康、柴田基洋
    • Organizer
      日本金属学会2020年秋期講演大会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 有機分子におけるスペクトル―物性相関2020

    • Author(s)
      菊政翔,清原慎,柴田基洋,溝口照康
    • Organizer
      第81回応用物理学会秋季学術講演会
    • Related Report
      2020 Annual Research Report
  • [Presentation] 4D-STEMによる非晶質材料の組成・試料厚計測2020

    • Author(s)
      中澤克昭, 三石和貴,安間伸一, 安間伸一,溝口照康
    • Organizer
      公益社団法人日本セラミックス協会, 第33回秋季シンポジウム
    • Related Report
      2020 Annual Research Report
  • [Presentation] Real-space analysis of Al and O distribution in Aluminosilicate Glass2020

    • Author(s)
      K. Liao, A. Masuno, H. Inoue, T. Mizoguchi
    • Organizer
      Fall Meeting of The Ceramic Society of Japan
    • Related Report
      2020 Annual Research Report
  • [Presentation] 第一原理計算と機械学習による原子間ポテンシャルおよび結晶構造探索2020

    • Author(s)
      世古敦人
    • Organizer
      日本セラミックス協会 第33回秋季シンポジウム
    • Related Report
      2020 Annual Research Report
  • [Presentation] 機械学習を活用したXAFSスペクトル解析2020

    • Author(s)
      溝口照康
    • Organizer
      第23回XAFS研究会
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] EELSを用いたガラスの配位数および原子振動の計測"2020

    • Author(s)
      溝口照康
    • Organizer
      第56回X線分析討論会
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] 単色化 EELS を用いたガラスの局所構造解析2020

    • Author(s)
      溝口照康
    • Organizer
      第63回日本顕微鏡学会シンポジウム
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] EELS/XAFSインフォマティクス~機械学習によるスペクトル解析の刷新~2020

    • Author(s)
      溝口照康
    • Organizer
      国際ナノテクノロジー総合展・技術会議 nanotech 2021
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] 人工知能による格子欠陥の内挿的学習2020

    • Author(s)
      溝口照康
    • Organizer
      日本物理学会格子欠陥フォーラム
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] ELNESインフォマティクス2020

    • Author(s)
      溝口照康
    • Organizer
      顕微鏡計測インフォマティクス第一回シンポジウム, 名古屋大学,愛知,1/25,2020
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習と先端電子顕微鏡によるナノ構造解析2020

    • Author(s)
      溝口照康
    • Organizer
      NIMS先端計測シンポジウム, NIMS,茨木,3/2,2020
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] Machine learning and DFT simulation for core-loss spectroscopy2020

    • Author(s)
      溝口照康
    • Organizer
      日本化学会春季大会, 東京理科大野田キャンパス,千葉,3/24,2020
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] ニューラルネットワークを用いた炭素K端ELNES/XANESからの物性予測2020

    • Author(s)
      菊政翔,清原慎,柴田基洋,溝口照康
    • Organizer
      応用物理学会春季大会, 上智大学,東京,3/14,2020
    • Related Report
      2019 Annual Research Report
  • [Presentation] 網羅的粒界構造決定アルゴリズムの開発とSi非対称粒界構造解析への利用2020

    • Author(s)
      Yaoshu Xie,柴田基洋,溝口照康
    • Organizer
      日本金属学会春季大会, 東工大,東京,3/18,2020
    • Related Report
      2019 Annual Research Report
  • [Presentation] 機械学習を用いた原子結合及び状態密度の予測2020

    • Author(s)
      鈴木叡輝,柴田基洋,溝口照康
    • Organizer
      日本金属学会春季大会, 東工大,東京,3/18,2020
    • Related Report
      2019 Annual Research Report
  • [Presentation] Machine learning and DFT simulation for XAFS/EELS2019

    • Author(s)
      Teruyasu Mizoguchi
    • Organizer
      The 1st Workshop of Reaction Infography (R-ing) Unit,June 11, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] 人工知能技術と量子化学計算を用いたスペクトルからの情報抽出2019

    • Author(s)
      溝口照康
    • Organizer
      表面真空学会実用顕微評価技術セミナー、東京,小柴ホール、6/13,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 第一原理計算および機械学習を用いたELNES/XANES解析2019

    • Author(s)
      溝口照康
    • Organizer
      顕微鏡学会学術講演会,名古屋,6/18,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] ガラスにおける相分離構造の高温その場観察2019

    • Author(s)
      中澤克昭,安間伸一,溝口照康
    • Organizer
      顕微鏡学会学術講演会,名古屋,6/17,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習,原子分解能電子顕微鏡,第一原理計算による材料分析2019

    • Author(s)
      溝口照康
    • Organizer
      東レリサーチセンター講演会,大津,滋賀,6/25,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] シミュレーションと機械学習による格子欠陥評価2019

    • Author(s)
      溝口照康
    • Organizer
      日本学術振興会第166委員会研究会,虎ノ門,東京,7/26,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習を利用した結晶界面構造決定と物性の予測2019

    • Author(s)
      溝口照康
    • Organizer
      応用数理学会2019年度年会,駒場,東京,9/5,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習を活用した機能コア解析2019

    • Author(s)
      溝口照康 (基調講演)
    • Organizer
      日本金属学会2019年度秋季大会,岡山大学,岡山,9/12,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 結晶界面インフォマティクスの最近の進展2019

    • Author(s)
      溝口照康
    • Organizer
      日本物理学会格子欠陥フォーラム,豊田工業大学,愛知,9/15,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習を用いたELNES/XANESスペクトル解析手法の開発2019

    • Author(s)
      清原慎,椿真史,溝口照康
    • Organizer
      応用物理学会2019年度秋季大会,北海道大学,北海道,9/21,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] ガラスにおける相分離現象の高温その場観察2019

    • Author(s)
      中澤克昭,溝口照康
    • Organizer
      新学術領域研究「機能コア」若手の会,浜松,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 第一原理計算計算,透過型電子顕微鏡および機械学習を活用した物質の構造解析2019

    • Author(s)
      溝口照康
    • Organizer
      豊橋技術科学大学特別講義,豊橋,愛知,10/4,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 機械学習を利用した結晶界面構造の最適化とスペクトル解析2019

    • Author(s)
      溝口照康
    • Organizer
      JSTインテリジェント計測講演会,本郷,東京,10/7,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] EELS/XAFSの第一原理計算とマテリアルズインフォマティクス2019

    • Author(s)
      溝口照康
    • Organizer
      JFEテクノリサーチ講演会,川崎,神奈川,10/9,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] 人工知能と第一原理計算による高速・高精度なデータ解析~分光法への応用~2019

    • Author(s)
      溝口照康
    • Organizer
      化学フェスタ2019,八丁堀,東京,10/17,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] Machine learning for crystalline interface and core-loss spectrum2019

    • Author(s)
      Teruyasu Mizoguchi
    • Organizer
      TSMC-UTokyo workshop,Taiwan,11/1,2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] シミュレーションと機械学習による格子欠陥評価2019

    • Author(s)
      溝口照康
    • Organizer
      日本学術振興会第161委員会講演会,名古屋,11/18,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] Bridging atomic-resolution experiment and computation using machine learning2019

    • Author(s)
      Teruyasu Mizoguchi
    • Organizer
      Materials Research Meeting (MRM) 2019, 横浜,神奈川,12/11,2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] データ駆動型XANES解析2019

    • Author(s)
      溝口照康
    • Organizer
      Photon factory (PF)研究会, つくば,茨木,12/17,2019
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] Data-Driven Approach for Crystalline Interface and Spectrum2019

    • Author(s)
      Teruyasu Mizoguchi
    • Organizer
      3rd Functional Materials Symposium (FMS) 2019, 札幌,北海道,12/19,2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] 酸化物中におけるプロトン拡散の原子論的理解2019

    • Author(s)
      豊浦 和明
    • Organizer
      第76回固体イオニクス研究会、2019/12/5
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] Observation of Single Atoms and Nano Structures in Liquid using Scanning Transmission Electron Microscopy2019

    • Author(s)
      T. Miyata and T. Mizoguchi
    • Organizer
      6th International symposium on advanced microscopy and theoretical calculations (AMTC6), Nagoya, Aichi, June 14th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] In-situ Observation of Spinodal Decomposition Process in Silicate Glass2019

    • Author(s)
      K. Nakazawa and T. Mizoguchi
    • Organizer
      6th International symposium on advanced microscopy and theoretical calculations (AMTC6), Nagoya, Aichi, June 14th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Probing Nanoscale Phase Separation in Aluminosilicate Glass with Electron Energy Loss Spectroscopy2019

    • Author(s)
      K. Liao, A. Masuno, H. Inoue, and T. Mizoguchi
    • Organizer
      6th International symposium on advanced microscopy and theoretical calculations (AMTC6), Nagoya, Aichi, June 14th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Machine learning for Core-loss spectrum: Automated interpretation via both supervised and unsupervised learning2019

    • Author(s)
      S. Kiyohara and T. Mizoguchi
    • Organizer
      6th International symposium on advanced microscopy and theoretical calculations (AMTC6), Nagoya, Aichi, June 14th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Machine Learning for Structure Property Relationship of Crystalline Interface2019

    • Author(s)
      R. Otani, S. Kiyohara, Y. Sugimori, and T. Mizoguchi
    • Organizer
      6th International symposium on advanced microscopy and theoretical calculations (AMTC6), Nagoya, Aichi, June 14th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] "Crystalline interface property prediction without the interface structure via machine learning2019

    • Author(s)
      R. Otani, S. Kiyohara, and T. Mizoguchi
    • Organizer
      Tronto University-University of Tokyo workshop, Tronto, Canada, June 27th, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Comprehension of interfacial structure and property relationship via machine learning2019

    • Author(s)
      R. Otani, S. Kiyohara, K. Shibata, and T. Mizoguchi
    • Organizer
      Pacfic Rim conference on ceramics society (PacRIM2019), Ginowan, Okinawa, Oct.28, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Nanoscale Investigation on Crack-resistant Aluminosilicate Glasses with STEM EELS2019

    • Author(s)
      Kun-Yen Liao, A. Masuno, H. Inoue, and T. Mizoguchi
    • Organizer
      Pacfic Rim conference on ceramics society (PacRIM2019), Ginowan, Okinawa, Oct.28, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Potential energy surface mapping by machine learning for characterizing atomic diffusion in crystals2019

    • Author(s)
      Kazuaki Toyoura
    • Organizer
      The 13th Pacific Rim Conference of Ceramic Societies (PACRIM13), Ginowan, Okinawa, Oct.28, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Nanoscale Investigation on Crack-resistant Aluminosilicate Glasses with STEM EELS2019

    • Author(s)
      Kun-Yen Liao, A. Masuno, H. Inoue, and T. Mizoguchi
    • Organizer
      National Taiwan University (NTU)-Univeristy of Tokyo (UT) workshop, Hongo, Tokyo, Dec.9, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Data-driven approach for core-loss spectroscopy: Prediction of spectra and Quantification of properties2019

    • Author(s)
      Shin Kiyohara, M. Tsubaki, and T. Mizoguchi
    • Organizer
      Materials Research Society (MRS 2019), Boston, USA, Dec 5, 2019
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 機械学習を用いたELNESの予測と物性定量化2019

    • Author(s)
      清原慎,椿真史,溝口照康
    • Organizer
      日本顕微鏡学会学術講演会, 名古屋国際会議場,名古屋,June18,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] プロトン伝導性BaZrO3中のキャリア間相互作用2019

    • Author(s)
      豊浦 和明, 藤井 健雄, 畑田 直行, 韓 東麟, 宇田 哲也
    • Organizer
      日本金属学会2019年秋期講演大会,2019/9/12
    • Related Report
      2019 Annual Research Report
  • [Presentation] 構造決定を伴わない粒界物性予測2019

    • Author(s)
      大谷龍剣,清原慎,柴田基洋,溝口照康
    • Organizer
      日本金属学会2019年度秋季大会, 岡山大学,岡山,9/18,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] STEM-EELS Analysis on Local Structures of Aluminosilicate Glasses2019

    • Author(s)
      Liao Kunyen,増野敦信,井上博之,溝口照康
    • Organizer
      日本金属学会2019年度秋季大会, 岡山大学,岡山,9/18,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] Database Generation and Machine Learning Application in Grain Boundary Structure and Properties2019

    • Author(s)
      Yaoshu Xie,大谷龍剣,清原慎,柴田基洋,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] Probing Cation Local Coordination and Vibration Modes at Silicate Glass with STEM EELS2019

    • Author(s)
      Liao Kunyen,増野敦信,井上博之,柴田基洋,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] 機械学習を利用した ELNES/XANES スペクトル解析2019

    • Author(s)
      菊政翔,清原慎,柴田基洋,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] 吸着反応の理解に向けた情報科学的手法による表面構造解析2019

    • Author(s)
      鈴木叡輝,清原慎,柴田基洋,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] 完全結晶の原子配列を用いた結晶界面物性の予測2019

    • Author(s)
      大谷龍剣,清原慎,柴田基洋,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Presentation] 4D-STEMを用いた相分離・結晶化過程のその場観察2019

    • Author(s)
      中澤克昭,溝口照康
    • Organizer
      新学術領域「機能コア」若手の会, 鷲津,静岡,9/24,2019
    • Related Report
      2019 Annual Research Report
  • [Book] Machine Learning in Chemistry: The Impact of Artificial Intelligence Prof. Hugh M Cartwright (Oxford Univ.) edited2020

    • Author(s)
      T.Mizoguchi
    • Publisher
      Royal Society of Chemistry publication
    • ISBN
      9781839160240
    • Related Report
      2020 Annual Research Report
  • [Book] 基礎系 化学 分析化学II:分光分析2020

    • Author(s)
      東京大学工学教程編纂委員会、馬渡 和真
    • Total Pages
      114
    • Publisher
      丸善出版
    • ISBN
      9784621304990
    • Related Report
      2020 Annual Research Report
  • [Book] Recommender Systems for Materials Discovery in “Machine Learning Meets Quantum Physics2020

    • Author(s)
      A. Seko, H. Hayashi, H. Kashima, and I. Tanaka
    • Total Pages
      467
    • Publisher
      Springer
    • ISBN
      9783030402457
    • Related Report
      2020 Annual Research Report
  • [Remarks] 東京大学生産技術研究所・ナノ物質設計工学研究室(溝口研究室)ホームページ

    • URL

      http://www.edge.iis.u-tokyo.ac.jp

    • Related Report
      2020 Annual Research Report
  • [Remarks] 機械学習ポテンシャルデータベース

    • URL

      https://sekocha.github.io/repository/index-e.html

    • Related Report
      2020 Annual Research Report
  • [Remarks] 分子動力学コード(LAMMPS)を用いた機械学習ポテンシャルの利用方法

    • URL

      https://github.com/sekocha/lammps-mlip-package

    • Related Report
      2020 Annual Research Report

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Published: 2019-07-04   Modified: 2022-07-01  

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