First-principles methods are required to accurately describe bond formation and bond breaking occurring during electrochemical reactions at the interface. Recent advances in computational infrastructures and software development allow the broad use of ab-initio molecular dynamics (AIMD) as a method for achieving a precise understanding of reaction processes and pathways in electrochemistry. AIMD samples dynamic trajectories at finite temperatures, where forces are computed "on the fly" from density functional theory, enabling an electronic-structure-level description of the systems. However, performing AIMD simulations at appropriate time-scales are challenging due to their high computational demand compared to other simulation methods, as well as the complexity of treating the interface system under an applied potential. The computational burden of simulations limits the size of the simulated system or also the treatment of the liquid in the electrolyte. Various approaches exist for describing the liquid phase at different levels of coarse-graining. These range from simplifying the electrolyte using a polarizable continuum model (implicit description), employing spatial distributions or correlation functions, representing molecules with force fields or interatomic potentials, to adopting a fully explicit quantum mechanical description. Currently, there are several methods to simulate the applied potential by charging the electrode in the periodic simulation-cell of an AIMD simulation. Because interfaces are extended systems, the charge added to the electrode must be screened by countercharges to avoid divergence of the Hartree energy of the system. One way to study a system at different electrode potentials is adding alkali metals or an extra hydrogen atom into the interface, which spontaneously split into a cation in the solvent and an electron in the electrode. However, the small supercell size typically employed prevents gradual control of the potential and surface charge when ions are added or removed. Additionally, when these ions participate in electrochemical reactions, the potential difference across the interface will vary along the reaction coordinate, which is undesirable, because this potential difference is part of the driving force for the reaction. Better control of the surface charge can be obtained by introducing atoms with artificial non-integer charges. Furthermore, there are many molecular simulation tools for constraining the potential given a certain charge or adjusting at each step the instantaneous changes of the charge and the potential given a target potential. As aforementioned, one can use a fully explicit description of the solution or a hybrid solvation method. Both kinds of methods can be implemented using classical force fields, e.g., in LAMMPS, or DFT-based approaches. In explicit-solvent DFT methods, one treats the atoms in the electrolyte at the interface and places a countercharge in an implicit-solvation cavity to make the overall simulation cell charge-neutral.