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Frontiers of Chemical Science and Engineering

ISSN 2095-0179

ISSN 2095-0187(Online)

CN 11-5981/TQ

Postal Subscription Code 80-969

2018 Impact Factor: 2.809

Front. Chem. Sci. Eng.    2019, Vol. 13 Issue (4) : 815-822    https://doi.org/10.1007/s11705-019-1837-9
RESEARCH ARTICLE
Kinetic Monte Carlo simulations of plasma-surface reactions on heterogeneous surfaces
Daniil Marinov()
IMEC, 3001 Leuven, Belgium
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Abstract

Reactions of atoms and molecules on chamber walls in contact with low temperature plasmas are important in various technological applications. Plasma-surface interactions are complex and relatively poorly understood. Experiments performed over the last decade by several groups prove that interactions of reactive species with relevant plasma-facing materials are characterized by distributions of adsorption energy and reactivity. In this paper, we develop a kinetic Monte Carlo (KMC) model that can effectively handle chemical kinetics on such heterogenous surfaces. Using this model, we analyse published adsorption-desorption kinetics of chlorine molecules and recombination of oxygen atoms on rotating substrates as a test case for the KMC model.

Keywords plasma-surface interaction      kinetic Monte Carlo      plasma nano technology     
Corresponding Author(s): Daniil Marinov   
Just Accepted Date: 24 June 2019   Online First Date: 27 August 2019    Issue Date: 04 December 2019
 Cite this article:   
Daniil Marinov. Kinetic Monte Carlo simulations of plasma-surface reactions on heterogeneous surfaces[J]. Front. Chem. Sci. Eng., 2019, 13(4): 815-822.
 URL:  
https://academic.hep.com.cn/fcse/EN/10.1007/s11705-019-1837-9
https://academic.hep.com.cn/fcse/EN/Y2019/V13/I4/815
Fig.1  Desorption flux of Cl2 from rotating anodized alumina substrate as a function of the rotation (delay) time. Experimental data from [23] measured at different Cl2 gas pressures are depicted with open symbols. Results of KMC simulations are shown with solid lines.
Fig.2  Assumed Gaussian distribution of adsorption site density over binding energy (left y-axis) and the corresponding characteristic desorption time as a function of the binding energy (right y-axis). The hatched area indicates the interval of characteristic desorption times that can be covered by the spinning wall technique. The part of the distribution that contributes to experimentally measured desorption fluxes is highlighted in red.
Fig.3  Desorption flux of O2 formed by recombination of oxygen atoms on silica-coated rotating substrate. Experimental data are taken from [31], PO2= 1.5 mTorr, 400 W plasma power. KMC simulations were performed assuming the delayed desorption mechanism with two types of active sites (with O2 desorption energies 0.798 and 0.715 eV).
Fig.4  Recombination probability of atomic oxygen on silica as a function of the reciprocal substrate temperature calculated using KMC with the standard model [16] and assuming the delayed desorption mechanism with two types of active sites.
Fig.5  KMC calculation of recombination probability of atomic oxygen on a model surface with an assumed Gaussian distribution of energy barriers for recombination (ER) centered at 0.18 eV. Different curves correspond to different FWHM of the Gaussian distribution.
Fig.6  Distributions of recombination events among chemisorption sites caused by a distribution of energy barriers for recombination ER. The assumed Gaussian distribution (FWHM= 0.06 eV) of surface site density over ER is shown with a dotted line.
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