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通过蒙特卡罗树搜索搜索晶界处的稳定偏析构型。

Searching the stable segregation configuration at the grain boundary by a Monte Carlo tree search.

机构信息

Institute of Industrial Science, University of Tokyo, 153-8505 Tokyo, Japan.

出版信息

J Chem Phys. 2018 Jun 28;148(24):241741. doi: 10.1063/1.5023139.

DOI:10.1063/1.5023139
PMID:29960339
Abstract

Non-stoichiometric structure localized at the grain boundary, namely, segregations of impurities, dopants, and vacancies, has an important effect on a broad variety of material properties. An understanding of this behavior is therefore indispensable for further material development. Although molecular dynamics simulation and a simulation combined with randomly swapping atoms and vacancies have usually been used to investigate the segregation structures, they require more than ten thousand structures and energy calculations to reach the stable configuration. Although several mathematical or informatics approaches, for example, genetic algorithm and Bayesian optimization, have been proposed to solve such combination optimization problems, they required some hyper parameters which crucially affect efficiency and huge computations to tune these parameters. Furthermore, a parallelization of the computation task is often impossible in molecular dynamics simulation and Bayesian optimization because their structures are related to each other before and after the time or simulation steps. Here, we develop a Monte Carlo tree search algorithm for grain boundary segregation and apply it to determine the stable segregation configuration of copper Σ5[001]/(210) and Σ37[001]/(750) with silver impurities. We achieved a determination of the stable configuration by searching only 1% of all possible configurations. Furthermore, we found that the search path and the number of playouts at the branch provide important insight to comprehend the background of the search. In the present case, the search path was identical to the sites with the spatially larger sites.

摘要

非化学计量结构定位于晶界,即杂质、掺杂剂和空位的偏析,对广泛的材料性能有重要影响。因此,为了进一步的材料开发,理解这种行为是必不可少的。虽然分子动力学模拟和与随机交换原子和空位相结合的模拟通常用于研究偏析结构,但它们需要超过一万个结构和能量计算才能达到稳定配置。尽管已经提出了几种数学或信息学方法,例如遗传算法和贝叶斯优化,来解决这种组合优化问题,但它们需要一些超参数,这些参数对于效率和大量计算的调整至关重要。此外,由于分子动力学模拟和贝叶斯优化的结构在时间或模拟步骤前后相互关联,因此通常不可能并行化计算任务。在这里,我们开发了一种用于晶界偏析的蒙特卡罗树搜索算法,并将其应用于确定铜 Σ5[001]/(210)和 Σ37[001]/(750)与银杂质的稳定偏析配置。我们只搜索了所有可能配置的 1%,就确定了稳定的配置。此外,我们发现分支处的搜索路径和走步数为理解搜索的背景提供了重要的线索。在目前的情况下,搜索路径与空间上较大的位置的位置相同。

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