Investigation of nucleation and grain growth in 2-dimensional systems by using generalized Monte Carlo simulations

Hakan Cetinel, Ozhan Kayacan and Demet Ozaydin

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 18, 4121-4126

Abstract: In this study, nucleation and grain growth was studied by using 2-dimensional generalized Monte Carlo simulations and experiments. As an attempt to improve the JMAK model, we proposed a new differential equation to be able to model nucleation and growth phenomena using nonextensive thermostatistics. One of the reasons that we would like to perform generalized Monte Carlo simulations in studying of nucleation and grain growth phenomena is that the generalized Monte Carlo algorithm was shown to be more effective than the standard Monte Carlo algorithm and also than the standard Molecular Dynamic algorithm in locating the minimum energy configuration. Therefore, for a given temperature, the fact that a configuration of the system with lower energy could be obtained by using the generalized Monte Carlo simulation means that a different textural configuration of grain growth could be also expected. In this respect, it is possible to say that the nonextensive statistics might be an appropriate tool in studying of nucleation and growth phenomena.

Keywords: Tsallis thermostatistics; Phase transformation; Kinetics; Computer simulation (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:18:p:4121-4126

DOI: 10.1016/j.physa.2013.04.040

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