Pre-KEIO TECHNO-MALL 2022 (1st)

This lecture was held from 13:00 to 17:00 on Saturday, October 15, 2022.

If a "model" can be created that outputs the properties of a material by inputting information about it (such as molecular species and synthesis conditions), it becomes possible to predict the properties of untested materials—in other words, to perform high-throughput screening on a computer. The research field dedicated to creating such "models" for materials using machine learning and applying them to material discovery and design is called Materials Informatics (MI). This tutorial provides an overview, through lectures and exercises, of the basics of machine learning and its application to materials chemistry, targeting researchers in chemistry and materials-related fields. In addition, we will feature lectures from instructors who are advancing materials development using MI and those who are considering incorporating it in the future, followed by a discussion on the outlook for MI.