Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search
This work addresses the problem of designing synthetic-accessible organic optoelectronic materials for applications like night-vision and biomedical imaging, representing an incremental advance in molecular engineering.
The paper tackled the challenge of systematically designing low-bandgap molecules with targeted optoelectronic properties by using a symmetry-aware fragment decomposition and Monte Carlo Tree Search generator, resulting in generated candidates that exhibited red-shifted absorption as validated by TD-DFT calculations.
Organic optoelectronic materials are a promising avenue for next-generation electronic devices due to their solution processability, mechanical flexibility, and tunable electronic properties. In particular, near-infrared (NIR) sensitive molecules have unique applications in night-vision equipment and biomedical imaging. Molecular engineering has played a crucial role in developing non-fullerene acceptors (NFAs) such as the Y-series molecules, which have significantly improved the power conversion efficiency (PCE) of solar cells and enhanced spectral coverage in the NIR region. However, systematically designing molecules with targeted optoelectronic properties while ensuring synthetic accessibility remains a challenge. To address this, we leverage structural priors from domain-focused, patent-mined datasets of organic electronic molecules using a symmetry-aware fragment decomposition algorithm and a fragment-constrained Monte Carlo Tree Search (MCTS) generator. Our approach generates candidates that retain symmetry constraints from the patent dataset, while also exhibiting red-shifted absorption, as validated by TD-DFT calculations.