In total, we successfully identified the best combination of electrocatalyst, electrolyte, and concentration for reaction (Figure ) from 1,250 possible combinations within 10 iterations for each of the 8 chemicals, amounting to a 10,000-reaction space. We note that each compound was independently optimized from the same search space (Table ). The optimization results demonstrated that all substrates achieved yields comparable to those obtained through human-level optimization, without initial input from a chemist. Interestingly, while some optimal conditions mirrored those reported in the literature, others revealed new, efficient combinations not driven by traditional chemical intuition (Tables ). This balance between exploitation (fine-tuning in specific regions) and exploration (testing novel combinations) underscored the robustness of the LLM-ML approach.