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Journal of Materials Informatics

           C O NT E NT S






           Topic: Exploring Materials Informatics: Emerging Technologies Inspired by the 2024
           Nobel Prize

           1       Large language models enabled intelligent microstructure optimization and defects classification of welded
                    titanium alloys
                    Suyang Zhang, William Yi Wang, Xinzhao Wang, Gaonan Li, Yong Ren, Xingyu Gao, Feng Sun, Bin Tang,
                    Haifeng Song, Jinshan Li
                    J. Mater. Inf. 2024, 4, 34  http://dx.doi.org/10.20517/jmi.2024.64

           2       High-throughput screening of phosphide compounds for potassium-ion conductive cathode application
                    Yawen Li, Natalia A. Kabanova, Vladislav A. Blatov, Junjie Wang
                    J. Mater. Inf. 2025, 5, 21  http://dx.doi.org/10.20517/jmi.2024.87


           3       Application of self-supervised learning in steel surface defect detection
                    Shiyu Hu, Xudong Ma, Yuqi Zhang, Wei Xu
                    J. Mater. Inf. 2025, 5, 44  http://dx.doi.org/10.20517/jmi.2025.21


           4       RF-NSGA-II framework for inverse design of high-performance Mg-Gd-based magnesium alloys
                    Yunchuan Cheng, Lei Wang, Zhihua Dong, Zengyong Zheng, Zhihong Xia, Shengwen Bai, Jiangfeng Song,
                    Bin Jiang
                    J. Mater. Inf. 2025, 5, 53  http://dx.doi.org/10.20517/jmi.2025.61


           5       The synergy of geometric tolerance factor and machine learning in discovering stable materials
                    Zhilong Wang, Fengqi You
                    J. Mater. Inf. 2026, 6, 1  http://dx.doi.org/10.20517/jmi.2025.41

           6       Accelerating materials discovery via AI-Agent integration of large language models and simulation tools
                    Xian Wang, Qun Zeng, Dong-Hui Xu, Li Zhang, Gang Jiang, Mingli Yang
                    J. Mater. Inf. 2026, 6, 9  http://dx.doi.org/10.20517/jmi.2025.69


           7       Agentic material science
                    Chengbo Li, Nian Ran, Jianjun Liu
                    J. Mater. Inf. 2026, 6, 10  http://dx.doi.org/10.20517/jmi.2025.87

           8       A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate
                    oxides for thermal barrier coatings
                    Ying Zhang, William Yi Wang, Ke Ren, Zhou Wang, Xingyu Gao, Yiguang Wang, Keke Zhang, Haifeng Song,
                    Xiubing Liang, Jinshan Li
                    J. Mater. Inf. 2026, 6, 11  http://dx.doi.org/10.20517/jmi.2025.71


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