FAST AND FLEXIBLE 3D MOLECULE DESIGN FRAMEWORK FOR NOVEL ORGANIC OPTOELECTRONIC MATERIALS

Organic optoelectronic materials (OOMs) are pivotal for advancing technologies such as organic photovoltaics and light-emitting diodes. Traditional methods for discovering new OOMs are inefficient and limited by chemical space exploration. We introduce O2-GEN, a novel framework leveraging a 3D pretraining backbone trained on a diverse dataset of over ten million molecules, enabling comprehensive exploration of chemical space. O2-GEN excels in generating fused-ring systems and conjugated fragment assemblies, achieving nearly 100% validity and novelty. It significantly outperforms existing models in speed and chemical structural validity, particularly for larger molecules. The framework supports both global and local generation modes, allowing for the creation of new molecules or modifications of existing structures. Additionally, O2-GEN integrates a property selector finetuned with density functional theory data, enabling precise multi-property screening. This framework offers a powerful tool for rational design and high-throughput screening of OOMs, with potential applications to drug discovery and energy materials.