Generalizable, efficient free energy methods are key for studying surface reactions that exhibit appreciable entropic effects to reaction energies, such as those involving large adsorbates, solvent-electrolyte species, and soft or porous surfaces such as MOFs. Machine learning-assisted enhanced sampling approaches, such as CFF-AIMD, can discover and elucidate the reaction mechanisms for these complex systems.