Updated on 2024/09/24

写真a

 
CHEN Ta-Te
 
Organization
Graduate School of Engineering Materials Design Innovation Engineering 1 Assistant Professor
Graduate School
Graduate School of Engineering
Undergraduate School
School of Engineering Materials Science and Engineering
Title
Assistant Professor
External link

Degree 1

  1. 博士(工学) ( 2022.3   筑波大学 ) 

Research Interests 3

  1. Machine learning

  2. Instrumented Indentation

  3. Finite Element Method

Research Areas 2

  1. Nanotechnology/Materials / Metallic material properties

  2. Nanotechnology/Materials / Structural materials and functional materials

Research History 4

  1. National Institute for Materials Science

    2023.7 - 2024.3

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  2. Nagoya University   Graduate School of Engineering   Assistant Professor

    2023.4

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  3. National Institute for Materials Science   NIMS Post-doctoral Researcher

    2022.4 - 2023.3

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  4. National Institute for Materials Science   NIMS Junior Researcher

    2019.4 - 2022.3

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Professional Memberships 2

  1. The Iron and Steel Institute of Japan

    2020

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  2. The Japan Society of Mechanical Engineers

    2019.10

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Awards 1

  1. Excellent presentation award

    2023.11   Data-driven estimation of plastic properties in work-hardening model combining power-law and linear hardening using instrumented indentation test

    Ta-Te Chen, Ikumu Watanabe, Dayuan Liu

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Papers 20

  1. Maximization of strength–ductility balance of dual-phase steels using generative adversarial networks and Bayesian optimization Reviewed

    Yoshihito Fukatsu, Ta-Te Chen, Toshio Ogawa, Fei Sun, Ikumu Watanabe, Mayumi Ojima, Shin Ishikawa, Yoshitaka Adachi

    Materials Today Communications     page: 110360 - 110360   2024.9

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    Authorship:Corresponding author   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.mtcomm.2024.110360

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  2. Comparative study of the experimentally observed and GAN-generated 3D microstructures in dual-phase steels Reviewed

    Ikumu Watanabe, Keiya Sugiura, Ta-Te Chen, Toshio Ogawa, Yoshitaka Adachi

    Science and Technology of Advanced Materials     2024.8

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    Publishing type:Research paper (scientific journal)   Publisher:Informa UK Limited  

    DOI: 10.1080/14686996.2024.2388501

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  3. Machine Learning-Aided Analysis of the Rolling and Recrystallization Textures of Pure Iron with Different Cold Reduction Ratios and Cold-Rolling Directions Reviewed

    Takumi Sumida, Keiya Sugiura, Toshio Ogawa, Ta-Te Chen, Fei Sun, Yoshitaka Adachi, Atsushi Yamaguchi, Yukihiro Matsubara

    Materials     2024.7

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    Language:English   Publishing type:Research paper (scientific journal)  

    <jats:p>We performed a machine learning-aided analysis of the rolling and recrystallization textures in pure iron with different cold reduction ratios and cold-rolling directions. Five types of specimens with different cold reduction ratios and cold-rolling directions were prepared. The effect of two-way cold-rolling on the rolling texture was small at cold reduction ratios different from 60%. The cold reduction ratio in each stage hardly affected the texture evolution during cold-rolling and subsequent short-term annealing. In the case of long-term annealing, although abnormal grain growth occurred, the crystal orientation of the grains varied. Moreover, the direction of cold-rolling in each stage also hardly affected the texture evolution during cold-rolling and subsequent short-term annealing. During long-term annealing, sheets with the same cold-rolling direction in the as-received state and in the first stage showed the texture evolution of conventional one-way cold-rolled pure iron. Additionally, we conducted a machine learning-aided analysis of rolling and recrystallization textures. Using cold-rolling and annealing conditions as the input data and the degree of Goss orientation development as the output data, we constructed high-accuracy regression models using artificial neural networks and XGBoost. We also revealed that the annealing temperature is the dominant factor in the nucleation of Goss grains.</jats:p>

    DOI: 10.3390/ma17143402

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  4. Analysis of the strength–ductility balance of dual-phase steel using a combination of generative adversarial networks and finite element method Reviewed

    Yoshihito Fukatsu, Ta-Te Chen, Toshio Ogawa, Fei Sun, Yoshitaka Adachi, Yuji Tanaka, Shin Ishikawa

    Computational Materials Science     2024.7

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    Authorship:Corresponding author   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.commatsci.2024.113143

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  5. Image regression analysis for linking the microstructure and property of steel Reviewed

    Kengo Sawai, Ta-Te Chen, Fei Sun, Toshio Ogawa, Yoshitaka Adachi

    Results in Materials   Vol. 21   page: 100526 - 100526   2024.3

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.rinma.2023.100526

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  6. Multi-objective topology optimization of porous microstructure in die-bonding layer of a semiconductor Reviewed

    Jiaxin Zhou, Ikumu Watanabe, Weikang Song, Keita Kambayashi, Ta-Te Chen

    Science and Technology of Advanced Materials: Methods     2024.2

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    Authorship:Last author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/27660400.2024.2320691

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  7. Deep-learning-based inverse design of three-dimensional architected cellular materials with the target porosity and stiffness using voxelized Voronoi lattices Reviewed

    Xiaoyang Zheng, Ta-Te Chen, Xiaoyu Jiang, Masanobu Naito, Ikumu Watanabe

    Science and Technology of Advanced Materials     2023.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/14686996.2022.2157682

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  8. Simulation of Abnormal Grain Growth Using the Cellular Automaton Method Reviewed

    Kenji Murata, Chihiro Fukui, Fei Sun, Ta-Te Chen, Yoshitaka Adachi

    Materials   Vol. 17 ( 1 ) page: 138 - 138   2023.12

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    The abnormal grain growth of steel, which is occurs during carburization, adversely affects properties such as heat treatment deformation and fatigue strength. This study aimed to control abnormal grain growth by controlling the materials and processes. Thus, it was necessary to investigate the effects of microstructure, precipitation, and heat treatment conditions on abnormal grain growth. We simulated abnormal grain growth using the cellular automaton (CA) method. The simulations focused on the grain boundary anisotropy and dispersion of precipitates. We considered the effect of grain boundary misorientation on boundary energy and mobility. The dispersion state of the precipitates and its pinning effect were considered, and grain growth simulations were performed. The results showed that the CA simulation reproduced abnormal grain growth by emphasizing the grain boundary mobility and the influence of the dispersion state of the precipitate on the occurrence of abnormal grain growth. The study findings show that the CA method is a potential technique for the prediction of abnormal grain growth.

    DOI: 10.3390/ma17010138

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  9. Two- and Three-Dimensional Modeling and Simulations of Grain Growth Behavior in Dual-Phase Steel Using Monte Carlo and Machine Learning Reviewed

    Fei Sun, Ayano Kita, Toshio Ogawa, Ta-Te Chen, Yoshitaka Adachi

    Materials     2023.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3390/ma16247536

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  10. Minimal-Surface-Based Multiphase Metamaterials with Highly Variable Stiffness Reviewed

    Xiaoyang Zheng, Ikumu Watanabe, Siqian Wang, Ta-Te Chen, Masanobu Naito

    Materials &amp; Design     page: 112548 - 112548   2023.12

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    DOI: 10.1016/j.matdes.2023.112548

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  11. Evaluation of Austenite–Ferrite Phase Transformation in Carbon Steel Using Bayesian Optimized Cellular Automaton Simulation Reviewed

    Fei Sun, Yoshihisa Mino, Toshio Ogawa, Ta-Te Chen, Yukinobu Natsume, Yoshitaka Adachi

    Materials     2023.10

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3390/ma16216922

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  12. Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design Reviewed

    Xiaoyang Zheng, Xubo Zhang, Ta‐Te Chen, Ikumu Watanabe

    Advanced Materials     page: e2302530   2023.6

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Wiley  

    DOI: 10.1002/adma.202302530

    PubMed

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  13. Data-driven estimation of plastic properties in work-hardening model combining power-law and linear hardening using instrumented indentation test Reviewed

    Ta-Te Chen, Ikumu Watanabe

    Science and Technology of Advanced Materials: Methods     2022.12

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/27660400.2022.2129508

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  14. Reprogrammable flexible mechanical metamaterials Reviewed

    Xiaoyang Zheng, Koichiro Uto, Wei-Hsun Hu, Ta-Te Chen, Masanobu Naito, Ikumu Watanabe

    Applied Materials Today   Vol. 29   2022.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    Mechanical metamaterials are artificial structures with structure-dependent properties. They often harness zero-energy deformation modes, e.g., a single shape change that limits their applications, resulting in the need for changeable mechanical responses. We address this limitation by using a flexible material, called light-responsive shape-memory polydimethylsiloxane (SM-PDMS), to introduce reprogrammability into flexible mechanical metamaterials. The SM-PDMS is a rubber-like functional material with shape-memory and photothermal effects. Specfically, we propose three different reprogrammable SM-PDMS metamaterials with different mechanical responses, namely, an auxetic SM-PDMS, a chiral SM-PDMS, and a buckling-induced SM-PDMS. Finally, a buckling-induced SM-PDMS was harnessed to make a soft actuator with a reprogrammable preferred locomotion direction. Despite focusing on reprogramming flexible metamaterials using the light-induced SM effect, our strategy can be easily extended to other structures and smart materials. More importantly, our strategy paves the way to change the mechanical responses for similar architectures. Furthermore, our designed flexible metamaterials have the potential for different applications, such as soft robots, actuation, adaptive safety, and sports equipment.

    DOI: 10.1016/j.apmt.2022.101662

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  15. Heterogeneous microstructure of duplex multilayer steel structure fabricated by wire and arc additive manufacturing Reviewed

    Ikumu Watanabe, Ta-Te Chen, Sachiko Taniguchi, Houichi Kitano

    MATERIALS CHARACTERIZATION   Vol. 191   2022.9

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:ELSEVIER SCIENCE INC  

    Wire and arc additive manufacturing (WAAM) is suitable for fabricating multimaterial dense structures in various additive manufacturing technologies. Watanabe et al. [1] reported that a unique two-stage stress-strain curve was observed during tensile testing of a duplex multilayer steel structure fabricated by WAAM. The material behavior was explained by the transformation-induced plasticity, which was attributed to a decrease in the austenite phase observed after testing using X-ray diffraction at three representative points of the tensile test specimen. However, the deformation mechanism was unclear from the viewpoint of the composite structure mechanics. In this study, the heterogeneous microstructure of the steel structure was investigated for the duplex layer region to infer the relationship between the material response and underlying deformation mechanism. The distributions of the phase and major alloy elements indicated that the layers melted and mixed during WAAM, and the multilayer structure subsequently changed compared to the design layout. The WAAM structure was composed of two dual-phase layers containing different volume fractions of the martensite phase. Hence, the austenite phase in the martensite-rich layer initially deformed and then transformed to the martensite phase during tensile testing. Consequently, the strength of the martensite-rich layer was recovered to the micro-mechanically estimated level and the two-stage stress-strain curve was generated. Thus, this paper presents the potential of multimaterial WAAM for controlling microscopic heterogeneities and their material responses by adjustment of the process parameters.

    DOI: 10.1016/j.matchar.2022.112159

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  16. Light-Induced Topological Patterning toward 3D Shape-Reconfigurable Origami Reviewed

    Wei-Hsun Hu, Ming Ji, Ta-Te Chen, Siqian Wang, Mizuki Tenjimbayashi, Yu Sekiguchi, Ikumu Watanabe, Chiaki Sato, Masanobu Naito

    SMALL   Vol. 18 ( 14 )   2022.4

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:WILEY-V C H VERLAG GMBH  

    Shape-reconfigurable materials are crucial in many engineering applications. However, because of their isotropic deformability, they often require complex molding equipment for shaping. A polymeric origami structure that follows predetermined deformed and non-deformed patterns at specific temperatures without molding is demonstrated. It is constructed with a heterogeneous (dynamic and static) network topology via light-induced programming. The corresponding spatio-selective thermal plasticity creates varied deformability within a single polymer. The kinematics of site-specific deformation allows guided origami deployment in response to external forces. Moreover, the self-locking origami can fix its geometry in specific states without pressurization. These features enable the development of shape-reconfigurable structures that undergo on-demand geometry changes without requiring bulky or heavy equipment. The concept enriches polymer origamis, and could be applied with other polymers having similar chemistries. Overall, it is a versatile material for artificial muscles, origami robotics, and non-volatile mechanical memory devices.

    DOI: 10.1002/smll.202107078

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  17. Topological alternation from structurally adaptable to mechanically stable crosslinked polymer Reviewed

    Wei-Hsun Hu, Ta-Te Chen, Ryo Tamura, Kei Terayama, Siqian Wang, Ikumu Watanabe, Masanobu Naito

    Science and Technology of Advanced Materials     2022.1

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Informa {UK} Limited  

    DOI: 10.1080/14686996.2021.2025426

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  18. Controllable inverse design of auxetic metamaterials using deep learning Reviewed

    Xiaoyang Zheng, Ta-Te Chen, Xiaofeng Guo, Sadaki Samitsu, Ikumu Watanabe

    Materials & Design   Vol. 211   page: 110178 - 110178   2021.12

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Elsevier {BV}  

    DOI: 10.1016/j.matdes.2021.110178

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  19. Characterization of the Strain-Rate-Dependent Plasticity of Alloys Using Instrumented Indentation Tests Reviewed

    Ta-Te Chen, Ikumu Watanabe, Tatsuya Funazuka

    Crystals     2021.10

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3390/cryst11111316

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  20. Data-driven estimation of plastic properties of alloys using neighboring indentation test Reviewed

    Ta-Te Chen, Ikumu Watanabe, Dayuan Liu, Kenta Goto

    Science and Technology of Advanced Materials: Methods   Vol. 1 ( 1 ) page: 143 - 151   2021.1

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Informa {UK} Limited  

    DOI: 10.1080/27660400.2021.1959838

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Presentations 10

  1. 敵対的生成ネットワークとベイズ最適化による二相組織鋼の強度延性バランスの最大化

    深津義士, 陳達德, 渡邊育夢, 足立吉隆, 小島真由美, 石川伸

    日本鉄鋼協会第187回春季講演大会  2024.3.15 

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    Event date: 2024.3

    Presentation type:Oral presentation (general)  

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  2. 敵対的生成ネットワークを活用した二相組織鋼の二次元断面像からの三次元組織生成

    杉浦圭哉, 陳達德, 孫飛, 足立吉隆, 小川登志男, 渡邊育夢

    日本鉄鋼協会第187回春季講演大会  2024.3.15 

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    Event date: 2024.3

    Presentation type:Oral presentation (general)  

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  3. Estimation of plastic properties of alloys using instrumented indentation test International conference

    Ta-Te Chen, Ikumu Watanabe, Dayuan Liu, Goro Miyamoto

    SMS2023&GIMRT User Meeting 2023  2023.11.21 

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    Event date: 2023.11

    Presentation type:Poster presentation  

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  4. Data-driven estimation of plastic properties in work-hardening model combining power-law and linear hardening using instrumented indentation test

    Ta-Te Chen, Ikumu Watanabe, Dayuan Liu

    2023.9.28 

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    Event date: 2023.9

    Language:English   Presentation type:Oral presentation (general)  

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  5. SliceGANを用いて金属材料の3D組織再構築とその定量評価

    杉浦圭哉, 足立吉隆, 小川登志男, 孫飛, 陳達德

    日本鉄鋼協会第186回秋季講演大会  2023.9.22 

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    Event date: 2023.9

    Presentation type:Oral presentation (general)  

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  6. 敵対的生成ネットワークを活用した二相組織鋼の強度延性バランスの向上

    深津義士, 陳達德, 小川登志男, 足立吉隆, 田中裕二, 石川伸

    日本鉄鋼協会第186回秋季講演大会  2023.9.22 

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    Event date: 2023.9

    Presentation type:Oral presentation (general)  

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  7. Data-driven estimation of plastic properties of alloys using neighboring indentation test

    Ta-Te Chen, Ikumu Watanabe

    The 186th ISIJ meeting  2023.9.22 

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    Event date: 2023.9

    Language:English   Presentation type:Oral presentation (general)  

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  8. 条件付き敵対的生成ネットワークによるプロセスを反映したDual Phase鋼の画像生成

    形川龍市, 足立吉隆, 小川登志男, 田中裕二, 石川伸, 陳達德

    日本鉄鋼協会第186回秋季講演大会  2023.9.22 

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    Event date: 2023.9

    Presentation type:Oral presentation (general)  

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  9. Characterization of mechanical properties of alloys using instrumented indentation test Invited International conference

    Ikumu Watanabe, Ta-Te Chen, Dayuan Liu

    XVII International Conference on Computational Plasticity  2023.9.5 

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    Event date: 2023.9

    Language:English   Presentation type:Oral presentation (keynote)  

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  10. Characterization of mechanical properties using instrumented indentation test Invited International conference

    Ikumu Watanabe, Ta-Te Chen, Dayuan Liu

    International Conference on Processing and Manufacturing of Advanced Materials  2023.7.4 

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    Event date: 2023.7

    Language:English   Presentation type:Oral presentation (invited, special)  

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Teaching Experience (On-campus) 3

  1. 学生実験2

    2023

  2. 学生実験1

    2023

  3. マテリアル工学概論

    2023

 

Media Coverage 2

  1. Cracking the metal code Internet

    https://www.asiaresearchnews.com/content/cracking-metal-code  2024.2

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  2. New data extracted from old for materials databases Internet

    https://www.asiaresearchnews.com/content/new-data-extracted-old-materials-databases  2022.11

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Academic Activities 1

  1. M&M2023 材料力学カンファレンス

    Role(s):Panel moderator, session chair, etc., Review, evaluation

    日本機械学会  2023.9

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    Type:Academic society, research group, etc. 

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