Simulations of the organic-molecular ordering on the solid surfaces using pair potentials

Organic molecules on a flat, unreactive, periodical surface self-assemble to ordered superstructures. The superstructures can be used to selectively tune the properties of the surface. This problem can be studied using quantum mechanical models, such as Density functional theory (DFT). The use of those models for problems with hundreds of atoms and thousand of iterations is, however, due to their complexity, computationally impractical. In this thesis we extend and test an existing algorithm developed by the advisor of this thesis. The algorithm sacrifices accuracy for a quicker simulation time by using the method of paired potentials. This method simplifies the quantum mechanical description of an atom by considering a point source of change and replaces the complex interaction between atoms with pair parametrized forces. This method is incorporated into a Monte Carlo simulation which, from a given superstructure obtained from exper- imental data, predicts the position and deformation of the molecules that minimize the total potential energy. We test the algorithm on two real-world problem sets. The algo- rithm gives results comparable to that of DFT when tested on already studied problems, yet converges to the solution much faster. It can be used as a standalone program or as an initialization to the DFT..