This approach uses simplified models to represent the molecules, for example the sum of their atomic van-der-Waals radii or even simple geometric shapes like ellipsoids or circles. The substrate is reduced to a regular 2D lattice sometimes even without PBC. The algorithm then determines an adsorption spot for sequentially incoming molecules considering a random factor (which gives the method its name). In case no overlap with a neighboring molecule is present at the selected lattice point, the incoming molecule is placed at this spot and the algorithm is repeated. Usually, the judgment on the overlap is based on the 2D shape of the considered molecules. This algorithm has a history in other fields and has recently been adapted to AS-ALD. For AS-ALD, the main goal of an RSA simulation is to derive surface coverage, hole size and density, as well as inhibitor density. These insights can help to judge inhibitor blocking efficiency and mechanisms: Good selectivity in combination with a high surface coverage is hinting towards steric blocking while good selectivity with a high inhibitor density is hinting towards chemical passivation as the major blocking mechanism. Still, both effects are contributing to the overall blocking efficiency. For conducting reasonable RSA simulation, the technical parameters of the simulation cell size, boundary conditions, and rotational degrees of freedom of incoming molecules must be sampled, as they considerably impact the final surface coverage. While RSA simulations are extremely fast, the main downside is their limited accuracy, which is caused by the strong approximations of neglecting any reaction events such as conformer changes beyond rotations, desorption, diffusion or reactions as well as neglecting inter-molecular interactions beyond steric blocking.