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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 initiomolecular 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 10−2cm2/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.A molecular design system using machine learning method was successfully constructed for hole transport materials with high hole mobilities in the amorphous phase. The first useful molecular dataset was constructed by collecting experimental hole mobilities of 321 molecules with MO eigenvalues. The easily machine accessible datasets and molecular design system used in this work were publicly released at GitHub.

The electro-oxidative polymerization of benzene in the presence of strong acids yields poly(p-phenylene) efficiently. A strong protonic acid such as trifluoromethanesulfonic acid or Lewis acid such as an aluminum trichloride forms a complex with benzene and reduces the oxidation potential of benzene to 1.7 V, which brings about the high current efficiency. The acids act both as an electrolyte and as a catalyst in this polymerization of benzene.