[School of Science and Technology] A research paper from the Data Chemical Engineering Laboratory (Prof. KANEKO Hiromasa) has been featured on the cover of the international journal "Journal of Chemical Information and Modeling"
[School of Science and Technology] A research paper from the Data Chemical Engineering Laboratory (Prof. KANEKO Hiromasa) has been featured on the cover of the international journal "Journal of Chemical Information and Modeling"
A paper from the Laboratory of Data and Chemical Engineering (Professor KANEKO Hiromasa) graced the cover of Volume 66, Issue 12 (2026) of the international academic journal "Journal of Chemical Information and Modeling."
Organic semiconductors require both high carrier mobility and structural diversity, but direct first-principles evaluation is costly and brute-force exploration of chemical space is infeasible. We propose a data-driven framework that combines a hierarchical variational autoencoder (HVAE), Gaussian mixture regression (GMR), and Bayesian optimization to design small molecules exhibiting low reorganization energy and high carrier mobility.
