First-principles kinetic Monte Carlo simulations for heterogeneous catalysis, applied to the CO oxidation at RuO2(110)

We describe a first-principles statistical mechanics approach enabling us to simulate the steady-state situation of heterogeneous catalysis. In a first step density-functional theory together with transition-state theory is employed to obtain the energetics of all relevant elementary processes. Subsequently the statistical mechanics problem is solved by the kinetic Monte Carlo method, which fully accounts for the correlations, fluctuations, and spatial distributions of the chemicals at the surface of the catalyst under steady-state conditions. Applying this approach to the catalytic oxidation of CO at RuO2(110), we determine the surface atomic structure and composition in reactive environments ranging from ultra-high vacuum (UHV) to technologically relevant conditions, i.e. up to pressures of several atmospheres and elevated temperatures. We also compute the CO2 formation rates (turnover frequencies). The results are in quantitative agreement with all existing experimental data. We find that the high catalytic activity of this system is intimately connected with a disordered, dynamic surface ``phase'' with significant compositional fluctuations. In this active state the catalytic function results from a self-regulating interplay of several elementary processes.Comment: 18 pages including 9 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

An Efficient Hybrid Ant Colony System for the Generalized Traveling Salesman Problem

The Generalized Traveling Salesman Problem (GTSP) is an extension of the well-known Traveling Salesman Problem (TSP), where the node set is partitioned into clusters, and the objective is to find the shortest cycle visiting each cluster exactly once. In this paper, we present a new hybrid Ant Colony System (ACS) algorithm for the symmetric GTSP. The proposed algorithm is a modification of a simple ACS for the TSP improved by an efficient GTSP-specific local search procedure. Our extensive computational experiments show that the use of the local search procedure dramatically improves the performance of the ACS algorithm, making it one of the most successful GTSP metaheuristics to date.Comment: 7 page