#llm-molecular-design News & Analysis

Closing the Prior-Posterior Loop: Self-Reflective Molecular Design with Analysis-Driven LLM Iteration

Researchers demonstrate that large language models can design molecules with chemist-level precision by replacing simple numerical feedback with detailed physicochemical analysis. The approach couples retrieval-augmented generation with self-reflection modules that feed orbital energies and atomic charges back into design iterations, achieving near-perfect accuracy on HOMO-LUMO gap targets and 100% success rates on moderate molecular design tasks.