High entropy alloys (HEA) represent a class of materials with promising properties, such as high strength and ductility, radiation damage tolerance, etc. At the same time, a combinatorially large variety of compositions and a complex structure render them quite hard to study using conventional methods. In this work, we present a computationally efficient methodology based on ab initio calculations within the coherent potential approximation. To make the methodology predictive, we apply an exchange-correlation correction to the equation of state and take into account thermal effects on the magnetic state and the equilibrium volume. The approach shows good agreement with available experimental data on bulk properties of solid solutions. As a particular case, the workflow is applied to a series of iron-group HEA to investigate their solid solution strengthening within a parameter-free model based on the effective medium representation of an alloy. The results reveal intricate interactions between alloy components, which we analyze by means of a simple model of local bonding. Thanks to its computational efficiency, the methodology can be used as a basis for an adaptive learning workflow for optimal design of HEA.

中文翻译：

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高熵合金中固溶强化的精确从头算模型

高熵合金（HEA）代表了一类具有前景的材料，如高强度和延展性、辐射损伤耐受性等。同时，组合的种类繁多、结构复杂，使得它们很难用常规方法。在这项工作中，我们提出了一种计算有效的方法，该方法基于相干势近似内的从头算计算。为了使该方法具有预测性，我们对状态方程应用交换相关校正，并考虑对磁态和平衡体积的热效应。该方法与关于固溶体整体性质的可用实验数据显示出良好的一致性。作为一个特例，该工作流程应用于一系列铁基 HEA，以在基于合金有效介质表示的无参数模型中研究它们的固溶强化。结果揭示了合金成分之间复杂的相互作用，我们通过一个简单的局部键合模型对其进行了分析。由于其计算效率，该方法可以用作自适应学习工作流程的基础，以优化 HEA 设计。