[17p-A401-1~15] 23.1 Joint Session N "Informatics"

△ [17p-A401-11] Prediction of optical properties in AI-assisted molecular design system

〇(B)Ren Sasaki¹, Tomoharu Okada¹, Yuki Mochizuki¹, Hiroyuki Matsui¹ (1.ROEL, Yamagata Univ.)

Keywords:material informatics, machine learning, organic semiconductors

In recent years, materials informatics, which utilizes machine learning and other techniques to develop materials, is expected to reduce the time and cost of materials development. Therefore, we are aiming to improve the efficiency of molecular design by developing a molecular design application that incorporates machine learning models to instantly predict the physical properties of drawn molecules. We have so far succeeded in predicting HOMO and LUMO energies in the application. In this study, we develop a new machine learning model to predict absorption and emission spectra.