MEMBERS

Suzuki, M., Muramatsu, M., Reese, S., Prume, E., “Efficient evaluation of mechanical properties for two-phase materials using a direct data-driven approach”, Materials & Design, Vol. 259, 114946, pp. 1-10, (2025).https://doi.org/10.1016/j.matdes.2025.114946

Achievement of Arisa Ikeda

Paper

  1. Ikeda, A., Higuchi, R., Yokozeki, T., Endo, K., Kojima, Y., Suzuki, M., Muramatsu, M., “Conditional diffusion model for inverse prediction of process parameters and dendritic microstructures from mechanical properties”, Scientific Reports, Vol. 15, 37147, pp. 1-20, (2025).https://doi.org/10.1038/s41598-025-22942-y

International conference

  1. Ikeda, A.*,Higuchi, R., Yokozeki, T., Endo, K., Kojima, Y., Suzuki, M., Muramatsu, M., “Prediction of Microstructures of Dendrite Crystals and Process Parameters for Thermoplastic Resin Based on Mechanical Properties Using The Conditional Diffusion Model”, 16th World Congress on Computation Mechanics & 4th Pan American Congress on Computational Mechanics (WCCM-PANACM2024), Canada (2024), MS1807, W241892.

Domestic conference

  1. 池田有沙*, 櫻井彰忠, 村松眞由「Quantum extreme reservoir computingにおけるポリマーアロイ相分離構造の分類性能の評価」, 第38回日本機械学会計算力学講演会, OS6-4, (2025).
  2. 池田有沙*, 櫻井彰忠, 村松眞由「ポリマーアロイ相分離構造に対する量子機械学習適用の検討」, 第37回日本機械学会計算力学講演会, OS-1006, (2024).
  3. 池⽥有沙*, 樋⼝諒, 横関智弘, 遠藤克浩, 児嶋佑太, 鈴⽊美智, 村松眞由「Conditional Diffusionモデルを⽤いた⼒学特性に基づく熱可塑性樹脂のデンドライト結晶および加⼯温度の予測」, 第29回計算工学講演会, A-08-04 (6 pages), (2024).
Back to MEMBERS INDEX