Images about automated mechanistic insights, bayesian optimization for experimental planning, closed-loop experimentation, data augmentation and transfer learning, density functional theory acceleration, graph neural networks gnns and molecular representations, green chemistry and sustainability goals, high-throughput virtual screening, integration with automated synthesis platforms, inverse design approaches, literature mining and knowledge extraction, multi-objective optimization, predictive modeling of activity and selectivity, rational ligand and support selection, reaction condition optimization, reinforcement learning for iterative improvement, scale-up predictions, stability and lifetime predictions, surrogate modeling for expensive computations, and targeted design of active sites.