Presentation Information
[7p-S202-2]Application of a Material Structural Similarity Map to Materials Process Exploration
〇Yusuke Hashimoto1, Xue Jia2, Hao Li2, Tomai Takaaki1 (1.FRIS, Tohoku Univ., 2.AIMR, Tohoku Univ.)
Keywords:
Materials informatics,Thermoelectric materials,Machine learning
Materials informatics, which integrates data science with materials science, is attracting growing attention. While screening studies that propose optimal materials using accumulated big data and data-driven methodologies have advanced, the synthesis of the proposed materials still largely depends on researchers’ experience and intuition. This study leverages a previously developed material structure similarity map to explore material processing conditions. Materials with similar structures tend to be synthesizable using similar equipment and process parameters. By efficiently identifying structurally similar materials through the similarity map, we aim to streamline the exploration of material processing methods.