Formation of machine learning models of high-refractive index organic materials through high-throughput quantum chemical calculations

Abstract

We studied the machine learning models for high-refractive organic compounds, based on literature data. Although, the prediction data by the model were well toward common organic compounds, that of the high-refractive compounds were not accord with experimental data, due to the few literature data of high-refractive compounds. Therefore, we created data for 62 high-refractive compounds using high-throughput quantum chemical calculations and performed the transfer learning based on the literature data model. The obtained transfer learning model showed well results for selected high-refractive organic compounds.