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Molecular Understanding of Free Energy Landscapes

Authors
Affiliations
Department of Chemical Engineering, University College London
Department of Chemical Engineering, University College London

Abstract

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.

Keywords:Molecular ThermodynamicsFree Energy SurfacesComputational Physical ChemistryReaction CoordinatesMachine LearningArtificial Intelligence

Acknowledgments

MSa gratefully acknowledges the HT-MATTER UKRI Frontier Research Guarantee Grant (EP/X033139/1) for funding, and all the members of the Molecular Modelling and Engineering group who offered feedback on earlier versions of this manuscript, in particular Aaron Finney, Matteo Paloni, and Florian M. Dietrich.

Molecular Understanding of Free Energy Landscapes
Introduction