Due to the computational expense associated with calculating and sampling the large number of solvent degrees of freedom at the QM level, implicit solvation methods, such as polarizable continuum models (PCM), remain by far the most popular approach. Such PCM approaches (e.g. VASPSol and Environ ) are now integrated into common plane-wave density functional theory (DFT) codes and provide a computationally-efficient description for solvation effects at interfaces. Nonetheless, several recent works demonstrate the fundamental limitations of such a continuum approach when applied to the metal/water interface. Beyond the neglect of local heterogeneity (e.g., local electric field fluctuations) that is intrinsic to an implicit model, it was also shown that the electrolyte distribution can be unphysically close to the surface. Moreover, Heenen et al. found via comparison with AIMD that the solvation contribution from the implicit solvation can be as poor as simply ignoring the overall solvation. More recently, Eggert et al. attempted to address some of the limitations of continuum models by accounting for the energy of cavity formation at a metal-water interface. More sophisticated solvation models, such as the reference interaction site model (RISM), partially account for the solvent structure via an integral equation approach, even without sampling. However, most RISM implementations utilize only simply Lennard-Jones functional forms, which exhibit qualitatively incorrect descriptions of the metal-water interactions (for example, incorrectly predicting hollow sites vs. atop site as the most stable water binding site). Given these limitations, AIMD calculations provide a robust, accurate (but computationally expensive) alternative to simulating metal/water interfaces. For example, Liu et al. studied the adsorption of furfural at a metal/water interface and found that the adsorption at the metal/water interfaces becomes much weaker vs. gas-phase adsorption. They explain the origin of this weaker binding in terms of the required displacement of pre-adsorbed water molecules on the surface during furfural adsorption, and demonstrate that the OH* binding energy can be used as a descriptor for this solvation contribution. Similarly, Kristoffersen et al. showed that the adsorption free energy of catechol at TiO2/water interfaces can be approximated by adding the energy cost of removing 2 water molecules to the gas-phase adsorption energy based on the AIMD simulations. Both of these prior AIMD studies, as well as earlier experimental data for organic adsorption on Pt electrodes, emphasize the importance of properly accounting for the competitive role of water in surface adsorption.