论文标题

难治性高熵合金中订单级过渡的蒙特卡洛模拟:一种数据驱动方法

Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: a data-driven approach

论文作者

Liu, Xianglin, Zhang, Jiaxin, Yin, Junqi, Bi, Sirui, Eisenbach, Markus, Wang, Yang

论文摘要

高熵合金(HEAS)是一系列新型材料,这些材料表现出许多非凡的机械性能。要了解这些有吸引力的特性的起源,重要的是研究热力学并阐明各种化学阶段的演变。在这项工作中,我们引入了一种数据驱动的方法来构建有效的哈密顿量,并通过规范的蒙特卡洛模拟研究HEAS的热力学。我们方法的主要特征是使用原子之间的成对相互作用作为特征,并使用蒙特卡洛模拟中的样本系统地提高数据集的代表性。我们发现这种方法产生了高度鲁棒和准确的有效汉密尔顿人,对于所有三种难治性HEAS的测试误差少于0.1 mry测试误差:monbtaw,monbtavw和monbtatiw。使用副本交换来加快MC模拟,我们计算了在广泛温度下的特定热量和短程顺序参数。对于所有研究的材料,我们发现分别在$ t_1 $和$ t_2 $的情况下分别进行了两个主要的订单转换,其中$ t_1 $在室温接近室温,但$ t_2 $要高得多。我们进一步证明,$ t_1 $的过渡是由w和nb引起的,而$ t_2 $的转换是由其他元素引起的。通过与实验进行比较,{\ color {black}结果提供了有关化学有序在HEAS强度和延展性中的作用的见解。

High entropy alloys (HEAs) are a series of novel materials that demonstrate many exceptional mechanical properties. To understand the origin of these attractive properties, it is important to investigate the thermodynamics and elucidate the evolution of various chemical phases. In this work, we introduce a data-driven approach to construct the effective Hamiltonian and study the thermodynamics of HEAs through canonical Monte Carlo simulation. The main characteristic of our method is to use pairwise interactions between atoms as features and systematically improve the representativeness of the dataset using samples from Monte Carlo simulation. We find this method produces highly robust and accurate effective Hamiltonians that give less than 0.1 mRy test error for all the three refractory HEAs: MoNbTaW, MoNbTaVW, and MoNbTaTiW. Using replica exchange to speed up the MC simulation, we calculated the specific heats and short-range order parameters in a wide range of temperatures. For all the studied materials, we find there are two major order-disorder transitions occurring respectively at $T_1$ and $T_2$, where $T_1$ is near room temperature but $T_2$ is much higher. We further demonstrate that the transition at $T_1$ is caused by W and Nb while the one at $T_2$ is caused by the other elements. By comparing with experiments, {\color{black} the results provide insight into the role of chemical ordering in the strength and ductility of HEAs.

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