Several challenges must be overcome for many catalytic systems to reach commercial feasibility. One of the direct causes is the significant overpotential at the catalyst surface due to the complex reaction mechanisms involved. To design the next generation of catalysts, it is crucial to obtain accurate microscopic properties such as free energies of adsorption, free energies of solvation, activation energies and surface charges. These properties undergo important variations due to operational conditions, including the presence of a solvent and electrolytes. Possible insights on these variations using experimental techniques are restricted by both technical and physical limitations, and often computational techniques are required. Analogously, there are important limitations in computational modelling preventing a fully accurate description of the electrochemical interface. In order to obtain thermally integrated properties for electrochemical systems it is necessary to sample the phase space at constant potential. Explicit sampling of the solvent and electrolytes is required to accurately describe the interface but is still computationally unfeasible. Furthermore, because the Fermi energy is a bulk property, simulations involving finite-sized electrodes will require larger simulation cells to minimize fluctuations of this quantity. To address this problem, the solvent is often replaced by a dielectric medium which aims to reproduce electrostatic features of the solvent. In the same fashion, electrolytes are often replaced by a continuous charge density using Poisson-Boltzmann models. In combination, the potential of the simulation cell can be fixed using recent approaches such as Grand-Canonical DFT, allowing the total number of electrons to change while keeping the Fermi energy constant. Alternative approaches include combining explicit water and implicit solvation along with exploring various charge screening methods. For instance, capacitor-based approaches, which rely on simple but effective thermodynamic assumptions, have been successful in accurately describing both reaction and activation energies of the Oxygen Reduction Reaction (ORR). In these models, the double layer is formed by one or more water layers with added or removed protons.