Authors M. N. Grigoryev, N. K. Plugotarenko, T. A. Bednaya
Month, Year 02, 2018 @en
Index UDC 51–74
DOI 10.23683/2311-3103-2018-2-94-104
Abstract The simulation of the growth process of doped silicon-carbon films was described herein. Existing models of the structure of thin films of silicon-carbon compounds are considered. Modeling was based on a fractal clusters model of silicon-carbon compounds. Monte Carlo method, the algorithm Wang-Landau model, the diffusion-limited Witten-Sander model, the "cluster-cluster" aggregation model, the Hoshen-Kopelman method for determining the percolation cluster characteristic have been used for modeling the reasech structures. The Monte Carlo method was used to implement a random walk process describing the structure of the obtained fractals of silicon-carbon compounds. pH of the medium was considered during the modeling. Modeling of the structure was carried out in the MatLab software environment. Сonvenient interface for input the necessary data and display the resulting structure of doped silicon-carbon films was created with using the standard MatLab tools. Structures with different substrate dimensions, a different number of particles in the initial matrix, and a different number of particles of the doping component was obtained with the help of the created program in MatLab. Moment of the percolation transition and the percolation threshold was determined by algorithm of Hoshen-Kopelman. The dependence of the structure of fractal clusters and the dependence of the onset of percolation on the pH of the medium are established. It is found that for the same number of particles, the cluster size is larger under ideal conditions than in fractal structures obtained by modeling with the pH factor in mind. It is determined that the concentration of the alloying component of 0.2 mol% is sufficient to form a percolation cluster. The data obtained with the help of modeling can be used for processes of doping of silicon-carbon films.

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Keywords Silicon - carbon films; the Monte Carlo method; nanocomposites; fractal clusters.
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