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A morphological study of vicinal surface growth based on a hybrid algorithm

机译:基于混合算法的邻近表面生长的形态学研究

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A hybrid algorithm that combines a phase-field model and a lattice gas model evolving according to a kinetic Monte-Carlo (KMC) simulation scheme is used to investigate the dynamics of vicinal surface growth during vapor phase epitaxy. The algorithm is computationally far more efficient than pure KMC schemes, and this gain in efficiency does not correspond to a loss in information on the kinetics of individual atoms. We present numerical studies on the temperature dependence of macroscopic properties of the growing surface, evaluating the relevant stochastic processes (attachment, detachment, diffusion and island dynamics) as a function of their rates. We show that the temperature at which step flow is replaced by island nucleation depends on incoming flux, diffusion parameters and interstep distance. Moreover, we validate these finding by comparison to experiments and by analytical investigations.
机译:混合算法结合了根据动力学蒙特卡洛(KMC)模拟方案发展的相场模型和晶格气体模型,用于研究气相外延过程中邻近表面生长的动力学。该算法在计算上比纯KMC方案有效得多,并且效率的提高并不对应于单个原子动力学信息的损失。我们目前对生长表面的宏观特性对温度的依赖性进行数值研究,评估相关随机过程(附着,脱离,扩散和岛动力学)作为其速率的函数。我们表明,由岛形核代替步进流动的温度取决于入射通量,扩散参数和步距。此外,我们通过与实验进行比较以及通过分析研究来验证这些发现。

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