Suzuki, M., Shizawa, K., Muramatsu, M., “Deep learning-aided inverse analysis framework to accelerate the exploration of DP steel microstructures”, Materials Today Communications, Vol. 41, pp. 110557 1-17, (2024).
カテゴリー: Artificial Intelligence for Experiments of Microstructures
Kojima, Y., Hirayama, K., Harada, Y., Muramatsu, M., “Discussion on infrared stress measurements based on finite element analysis of transient heat conduction”, Bulletin of the JSME, ID23-00571, pp. 1-12, (2024).
Hiraide, K., Oya, Y., Hirayama, K., Endo, K., Muramatsu, M., ” Development of deep learning model for phase separation structure of diblock copolymer based on self-consistent field analysis”, Advanced Composite Materials, Vol. 00, pp. 00 1-14, Accepted (2024).
Hiraide, K., Oya, Y., Suzuki, M., Muramatsu, M., “Inverse design of polymer alloys using deep learning based on self-consistent field analysis and finite element analysis”, Materials Today Communications, Vol. 37, pp. 107233, 1-14, (2023).
Sasaki, K., Hirayama, K., Endo, K., Muramatsu, M., Murayama, M., “Nanoscale Defect Evaluation Framework Combining Real-Time Transmission Electron Microscopy and Integrated Machine Learning-Particle Filter Estimation”, Scientific Reports, Vol. 12, pp. 10525, 1-10, (2022).