Then, similar to the MC simulations, several cycles of kMC runs are carried out, and using a random factor in the algorithm, the product distribution is derived as a function of time. For example, in the Bortz-Kalos-Lebowitz (BKL) algorithm, the time steps are derived from the total rate constants of all currently possible events and a random number 𝜊 2 (eq. 2.14). The complexity of the model can be improved by further chemical interactions like the repulsion of adsorbed species towards incoming molecules. The advantageous description of surface processes by kMC is through their consideration of reaction barriers in addition to the adsorption processes from the stochastic modeling. This makes it a very promising method to evaluate the AS-ALD process beyond the nucleation stage. The added complexity, however, makes the computations much more demanding than simple MC simulations but still much less complex than DFT computations. The major drawback is that the DFT modeling of the relevant chemical reactions in the deposition must be complete. If one crucial reaction barrier is missing, the kMC algorithm will convey the wrong picture. Accordingly, only very few studies are found in the literature.