caa a22 4500 606217118 CHVBK 20210128101106.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s10598-015-9276-z doi (NATIONALLICENCE)springer-10.1007/s10598-015-9276-z Hybrid Modeling of Associative Thermal Desorption [Elektronische Daten] [A. Makeev, N. Semendyaeva] The article examines a hybrid multi-scale numerical algorithm that models surface reactions in the framework of the lattice gas model allowing for lateral interaction between adsorbed particles. The model is called Quasi-Equilibrium Kinetic Monte-Carlo (QE-KMC) algorithm. QE-KMC combines stochastic Monte-Carlo calculations (the Metropolis algorithm) with standard numerical methods for deterministic ordinary differential equations (ODE). QE-KMC assumes "infinitely fast” diffusion of absorbed particles on the lattice, which permits describing the macroscopic dynamics of the system by ODE for mean concentrations. These equations are not specified explicitly, but we can nevertheless evaluate their right-hand sides with prescribed accuracy by the Metropolis method. In the present article, QE-KMC is applied to generate associative thermal desorption spectra (TDS). TDS are presented for typical parameter values of lateral interactions on a square and hexagonal lattices. The QE-KMC results are compared with standard Kinetic Monte Carlo (KMC) results for lattice systems. We show that QE-KMC and KMC methods produce identical results if KMC allows for very fast surface diffusion. Yet QE-KMC requires much less computing time. Springer Science+Business Media New York, 2015 multi-scale modeling nationallicence master equation nationallicence Monte Carlo method nationallicence Metropolis algorithm nationallicence lattice gas model nationallicence Makeev A. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut Semendyaeva N. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut Computational Mathematics and Modeling Springer US; http://www.springer-ny.com 26/3(2015-07-01), 346-357 1046-283X 26:3<346 2015 26 10598 https://doi.org/10.1007/s10598-015-9276-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10598-015-9276-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Makeev A. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut NATIONALLICENCE 700 1- Semendyaeva N. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut NATIONALLICENCE 773 0- Computational Mathematics and Modeling Springer US; http://www.springer-ny.com 26/3(2015-07-01), 346-357 1046-283X 26:3<346 2015 26 10598