In this approach, electrons are explicitly considered, and the interatomic interactions are either based on pre-computed potential energy surfaces or computed "on-the-fly". The pre-computing approach has the advantage that very high accuracy methods can be used, but the same drawback as force fields that a potential for every pair of atoms is needed. Thus, most AIMD approaches use efficient electronic structure methods (nearly exclusively DFT) to compute the electronic structure at each timestep (or apply some tricks to do it every few timesteps). This approach allows us to investigate chemical reactions relevant for AS-ALD since bond formation processes can be described. The most relevant parameter here is the simulation temperature (for the most often used canonical ensemble where N, V and T are constant). This temperature cannot directly be connected to an experimental temperature but instead scales the velocities of the atoms higher temperature means higher kinetic energy. At low temperatures, typically only chemical changes without bond breaking are observed, e.g., conformational changes. The reason is that only reaction barriers of the order of 𝑘 B 𝑇 (ca. 2.5 kJ•mol -1 for 𝑇 = 298 K, 𝑘 B being the Boltzmann constant) can be overcome in MD simulations. High simulation temperatures lead to the observation of reactions with higher reaction barriers in the MD run. However, at very high temperatures the kinetic energy of the system is so large that unphysical atomic movements can result. The main issue here is that in a simplified view on TST the internal energy of the system must rearrange to focus enough of this energy into the "productive" vibrational mode which is connected to the transition state of the reaction. From experiment, this process is known to take picoseconds or longer. Thus, the probability of observing the crossing of a reaction barrier in a picosecond-long trajectory is quite low. Yet, the solution of generating many trajectories is impeded by AIMD's biggest drawback: the immense computational cost due to the many necessary DFT computations. This limits the system size (100s of atoms) and the simulation time (picoseconds) and still requires major high-performance computing (HPC) systems to be used for a few, short (10 ps) trajectories. Also, the low number of achievable trajectories usually prevents statistically meaningful statements (i.e., "the probability ratio of these two reactions is 12% vs. 88%") or the use of techniques like autocorrelation functions to derive properties (e.g., vibrational spectra).