Papers citing Prediction of Intramolecular Reorganization Energy Using Machine Learning
Artificial intelligence in the discovery and design of molecular semiconductors: a systematic review
Digital Discovery · 2026-01-01
Malin Zollner, Yashar Moshfeghi, Tahereh Nematiaram
Read original paper ↗ ·Learning the limits: how data, diversity, and representation control machine-learning predictions of reorganisation energy
Journal of Materials Chemistry C · 2026-01-01
Malin Zollner, Yashar Moshfeghi, Tahereh Nematiaram
Read original paper ↗ ·Data-Driven Design of Organic Semiconductors Exhibiting Low Reorganization Energy via Hierarchical Variational Autoencoders, Gaussian Mixture Regression, and Bayesian Optimization
Journal of Chemical Information and Modeling · 2026-06-04
Yamato Nakanishi, T. Ando, Nobuyuki Matsuzawa, Hiroyuki Maeshima, Hiromasa Kaneko
Read original paper ↗ ·Informatics-Guided Computational Design of Polyaromatic Hydrocarbons Suitable for Use as Hole Transport Materials
Journal of Chemical Information and Modeling · 2026-06-15
Ruicheng Li, Sergei Manzhos, Keisuke Kameda, Sergei Manzhos, Sergei Manzhos
Read original paper ↗ ·