Computational Approach for Molecular Design of Small Organic Molecules with High Hole Mobilities in Amorphous Phase Using Random Forest Technique and Computer Simulation Method

Abstract

Abstract A molecular design system of small organic molecules was developed to realize high hole mobility in the amorphous phase by using the random forest (RF) technique and a computer simulation method. Since there was no accessible datasets of the hole mobilities in the amorphous phase, we have constructed a datasets of experimental hole mobilities for 321 organic molecules with calculated MO energies to utilize machine learning techniques for molecular design procedures. RF was applied to the machine learning technique using the constructed datasets. The optimized RF exhibited correlation coefficients of 0.885 and 0.764 for the training and testing datasets, respectively. The modified ChemTS to use optimized RF was adapted to design molecules with high hole mobilities. The successive conduction (SC) model that uses ab initio molecular orbital (MO) calculations and the Marcus theory was adapted to ensure the predicted mobilities. The generated molecules were verified to have high calculated hole mobility (the order of 10−2 cm2/Vs) owing to the highest transfer integral and lowest reorganization energy by the theoretical successive conduction (SC) model. The datasets and programs used in this work were publicly released on GitHub.