HOME > Profile > KOYAMA, Toshiyuki
- Specially Appointed Researcher, Research Center for Structural Materials
- DXMag Principal Investigator, Computational Materials Science Group, Digital Transformation Initiative Center for Magnetic Materials, Research Center for Magnetic and Spintronic Materials
- Group Leader, Computational Microstructure Design Group, Materials Evaluation Field, Research Center for Structural Materials
- Address
- 305-0047 1-2-1 Sengen Tsukuba Ibaraki JAPAN [Access]
Research
- Keywords
構造・機能材料
PublicationsNIMS affiliated publications since 2004.
Research papers
- Toshiyuki Koyama, Yusuke Matsuoka, Akimitsu Ishii. Simple implementation examples of agent AI on free energy calculation and phase-field simulation. Science and Technology of Advanced Materials: Methods. (2025) 2601436 10.1080/27660400.2025.2601436 Open Access
- Akimitsu Ishii, Toshiyuki Koyama, Taichi Abe, Machiko Ode. Phase-field simulation coupled with a CALPHAD database for analyzing microstructural evolution during liquid-phase sintering of Nd–Fe–B magnets. Journal of Alloys and Compounds. 1025 (2025) 180266 10.1016/j.jallcom.2025.180266
- Yusuke Matsuoka, Machiko Ode, Taichi Abe, Toshiyuki Koyama, Yukiko K. Takahashi. Phase-field modeling of microstructure formation in FePt-C nanogranular films sputtered on MgO. Materials & Design. 261 (2026) 115314 10.1016/j.matdes.2025.115314 Open Access
Books
- KOYAMA, Toshiyuki. Computational Physical Metallurgy of Phase-Field Method. Physical Metallurgy. Elsevier, 2026, 103.
- KOYAMA, Toshiyuki. Chapter 21 "Phase Field". Springer Handbook of Materials Measurement Methods. , 2006, 1031-1055.
- 小山 敏幸. ナノシミュレーション技術ハンドブック. ナノシミュレーション技術ハンドブック(共立出版). , 2006, 84-89.
Proceedings
- 小山敏幸. Phase-field法に基づく3D組織形成シミュレーションと実験的3D解析との連係. シンポジウム資料「階層的3D/4D解析によるミクロ組織の多様性の解明」. (2009) 119-122
- KOYAMA, Toshiyuki, ONODERA, Hidehiro. Calculation of Stress-Strain Curve of Two-Phase Microstructure on the Basis of the Extended Secant Method. MATERIALS SCIENCE FORUM. (2010) 3325-3330
- KOYAMA, Toshiyuki. Phase Field Simulation of Precipitation Relevant to Imperfection of Crystal. International Journal of Advanced Microscopy and Theoretical Calculations. (2008) 178-179
Presentations
- 小山 敏幸. 材料組織生成AIとエージェントAIによる新材料デザイン. 日本学術会議 公開シンポジウム「地球再興を見据えた新材料デザイン」. 2025
- KOYAMA, Toshiyuki. Microstructure design accelerated by phase-field method, image-based property calculations, and generative AI techniques. Materials Research Meeting 2025 (MRM 2025). 2025 Invited
- 小山 敏幸. フェーズフィールド法と材料組織生成AIに基づく次世代材料設計. 日本機械学会 第38回計算力学講演会(CMD2025). 2025
Misc
- 小山敏幸. フェーズフィールド法と鉄鋼材料学. ふぇらむ: 日本鉄鋼協会会報. 30 [7] (2025) 474-479 Open Access
- 小山 敏幸. フェーズフィールド法の発展史と最近の話題. 金属. 80 [2] (2010) 92-98
- 小山 敏幸. 相変態シミュレーションを利用した自己組織形成の解析. 日本金属学会会報「まてりあ」. 42 [6] (2003) 470-474
Research Center for Structural Materials
Simple implementation examples of agent AI on free energy calculation and phase-field simulation
generative AI, LLM, Gibbs energy, Phase-field method, Jarzynski equality
Overview
With the development of an environment that equips large language models with tools, chat-type artificial intelligence (AI) is currently shifting to agent-type AI. Although building an agent AI with complex behavior is an important issue, a method for easily implementing simple agent AI is also useful in materials research. The objectives of this study are to demonstrate the usefulness of simple agent AI codes, and to distribute them as supplemental materials. The key points are summarized as follows. (1) Using Gibbs energy calculations as an example, we demonstrated a simple method for constructing agent AI, including explanation and distribution of the python code. (2) We applied this method to a scratch code development of phase-field simulation, and the template python code was also distributed. (3) Using the simple agent AI technique, we were able to easily verify that the Jarzynski equality is applicable for the diffusion behavior in diffusion couple, which provides a new approach for directly evaluating free energy change from diffusion flux information.
Novelty and originality
Using Gibbs energy calculations and diffusion simulations as examples, we demonstrated the implementation method and usefulness of simple agent AI, where sample python codes are distributed as supplemental materials. Research applying the Jarzinski equality to diffusion couple is likely the first attempt.
Details
Summary
For further details on this topic, please refer to the following paper.
Toshiyuki Koyama, Yusuke Matsuoka, Akimitsu Ishii. ”Simple implementation examples of agent AI on free energy calculation and phase-field simulation," Science and Technology of Advanced Materials: Methods, (2025) 2601436.
DOI: 10.1080/27660400.2025.2601436
The original python codes explained in the article are available online at https://doi.org/10.1080/27660400.2025.
The same python codes can also be downloaded from GitHub homepage of https://github.com/ts-koyama/. The key point is that anyone can build AI agents relatively easily in their own research environment, without needing a specialized computing environment.


