[3E1] [General Session] 13. AI Application

[3E1-02] Material discovery by AI

〇Seiji Takeda¹, Hsiang Han Hsu¹, Toshiyuki Hama¹, Toshiyuki Yamane¹, Koji Masuda¹, Daiju Nakano¹ (1. IBM Research - Tokyo)

Keywords:Cheminformatics, feature engineering, graph generation

Discovering new materials that possess on-demand properties is the central demand in every industrial domain. We constructed the first full-stack material discovery system consisting of several technical pieces; feature encoding, regression, solution search, and structure generation. Those pieces are coordinated to coherently work by newly defining two kinds of feature vectors; data-driven feature and pre-defined feature, and developing an algorithm to generate molecular structures by using those feature vectors. The capability of the system to discovery new molecules is demonstrated by a public dataset of commercial drugs.