Molecular Understanding of Free-Energy Landscapes

Free-energy surfaces (FESs) offer a unifying framework for understanding molecular-level structures, transformations, and thermodynamic stability. They distill the complexity of atomistic simulations into interpretable landscapes of metastable states, bridging molecular-level detail with macroscopic observables. This review provides researchers in molecular simulations, computational physical chemistry, and chemical engineering with a conceptual and practical guide to computing and interpreting FESs, from their statistical–mechanical foundations to modern machine learning approaches that are transforming the sampling, representation, and analysis of molecular systems.