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A kinetic Monte Carlo approach to diffusion-controlled thermal desorption spectroscopy

机译:动力学蒙特卡罗方法的扩散控制热解吸光谱

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摘要

Atomistic simulations of thermal desorption spectra for effusion from bulk materials to characterize binding or trapping sites are a challenging task as large system sizes as well as extended time scales are required. Here, we introduce an approach where we combine kinetic Monte Carlo with an analytic approximation of the superbasins within the framework of absorbing Markov chains. We apply our approach to the effusion of hydrogen from BCC iron, where the diffusion within bulk grains is coarse grained using absorbing Markov chains, which provide an exact solution of the dynamics within a superbasin. Our analytic approximation to the superbasin is transferable with respect to grain size and elliptical shapes and can be applied in simulations with constant temperature as well as constant heating rate. The resulting thermal desorption spectra are in close agreement with direct kinetic Monte Carlo simulations, but the calculations are computationally much more efficient. Our approach is thus applicable to much larger system sizes and provides a first step towards an atomistic understanding of the influence of structural features on the position and shape of peaks in thermal desorption spectra.This article is part of the themed issue ‘The challenges of hydrogen and metals’.
机译:热解吸光谱的原子模拟,以分析散装物料的渗出,以表征结合位点或捕获位点是一项艰巨的任务,因为需要大型系统尺寸和较长的时间范围。在这里,我们介绍一种在吸收马尔可夫链的框架内将动力学蒙特卡洛与超盆地的解析近似结合起来的方法。我们将我们的方法应用于BCC铁中的氢渗出,其中散装颗粒内的扩散使用吸收性马尔可夫链进行粗粒化,这为超级流域内的动力学提供了精确的解决方案。我们对超级流域的解析近似在晶粒尺寸和椭圆形状方面是可以转移的,并且可以在恒定温度和恒定加热速率的模拟中应用。产生的热脱附光谱与直接动力学蒙特卡洛模拟非常吻合,但计算效率更高。因此,我们的方法适用于更大的系统尺寸,为朝原子学上了解结构特征对热脱附光谱中峰的位置和形状的影响迈出了第一步。本文是主题``氢的挑战''的一部分和金属”。

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