Organic Chemistry

Organic chemistry research is undergoing a transformation driven by the integration of artificial intelligence and automation, aiming to accelerate discovery and improve efficiency in tasks such as molecular design, synthesis planning, and property prediction. Current research heavily utilizes large language models (LLMs), graph neural networks (GNNs), and Bayesian optimization methods, often incorporating multimodal data from various spectroscopic techniques to enhance model performance and interpretability. This shift promises to significantly impact drug discovery, materials science, and other fields by automating laborious processes, improving the accuracy of predictions, and providing deeper insights into structure-property relationships.