In MD, Newton's equations of motion are adopted to evolve atom positions in time . Here, chemical bonds are typically approximated as classical 'springs' whose displacement from an equilibrium bond distance is modelled using Hooke's law. Similar simple functions can be used to approximate bond and dihedral angle rotation to capture the forces associated with intramolecular degrees of freedom. Intermolecular interactions can be approximated using simple, classical interpretations of Van der Waals forces and Coulombic forces for point-charged atoms. Importantly, all molecular species are assumed to be in their electronic ground state. As such, MD adopting classical, semi-empirical force fields are not well-suited to simulate chemical reactions and dynamical changes to chemical speciation, though reactive force fields and the advent of machine learning methods to force field design make this a possibility. Particularly in the case of ionic systems, polarisability can be simulated using a relatively cheap treatment of charge displacement from atomic nuclei, e.g., using springs. By assigning a velocity (sampled from a Maxwell-Boltzmann distribution at a defined temperature) to atoms at the beginning of a simulation, the Hamiltonian dynamics of the system can be propagated according to a fixed temperature and the force field. This time integration is performed iteratively using a small time step, typically on the order of 1 fs, to capture the fastest atomic displacements in the system, usually molecular bond vibration.