芳香族?キノイド性およびドナー?アクセプター性を用いた狭バンドギャップπ共役系高分子予測モデルの構築

摘要

A band gap prediction model of π-conjugated polymers was constructed using aromatic/quinoid, donor/acceptor, and torsion properties to predict quantitatively the band gap of π-conjugated polymers from properties of monomers. Quinoid stabilization energy (QSE), energy difference between HOMO of donor and LUMO of acceptor, torsion angle in homo-dimer of monomers were used as descriptors of aromatic/quinoid, donor/acceptor, and torsion properties. The neural network, which was constructed by 2 hidden layers with 5 neurons per layer, quantitatively predicts (RMSD = 0.207 eV, R~(2) = 0.885) the band gap of the π-conjugated polymers from descriptors of monomers.