High entropy diborides are new categories of ultra-high temperature ceramics, which are believed promising candidates for applications in hypersonic vehicles. However, knowledge on high temperature thermal and mechanical properties of high entropy diborides is still lacking unit now. In this work, variations of thermal and elastic properties of high entropy (Ti_0.2Zr_0.2Hf_0.2Nb_0.2Ta_0.2)B₂ with respect to temperature were predicted by molecular dynamics simulations. Firstly, a deep learning potential for Ti-Zr-Hf-Nb-Ta-B diboride system was fitted with its prediction error in energy and force respectively being 9.2 meV/atom and 208 meV/Å, in comparison with first-principles calculations. Then, temperature dependent lattice constants, anisotropic thermal expansions, anisotropic phonon thermal conductivities, and elastic properties of high entropy (Ti_0.2Zr_0.2Hf_0.2Nb_0.2Ta_0.2)B₂ from 0 °C to 2400 °C were evaluated, where the predicted room temperature values agree well with experimental measurements. In addition, intrinsic lattice distortions of (Ti_0.2Zr_0.2Hf_0.2Nb_0.2Ta_0.2)B₂ were analyzed by displacements of atoms from their ideal positions, which are in an order of 10^-3 Å and one order of magnitude smaller than those in (Ti_0.2Zr_0.2Hf_0.2Nb_0.2Ta_0.2)C. It indicates that lattice distortions in (Ti_0.2Zr_0.2Hf_0.2Nb_0.2Ta_0.2)B₂ is not so severe as expected. With the new paradigm of machine learning potential, deep insight into high entropy materials can be achieved in the future, since the chemical and structural complexly in high entropy materials can be well handled by machine learning potential.

高熵二硼化物是超高温陶瓷的新类别，据信它们有望用于高超音速飞行器。但是，现在仍然缺乏有关高熵二硼化物的高温热和机械性能的知识。在这项工作中，高熵（Ti _0.2 Zr _0.2 Hf _0.2 Nb _0.2 Ta _0.2）B ₂的热和弹性性质的变化通过分子动力学模拟预测温度。首先，与第一原理计算相比，Ti-Zr-Hf-Nb-Ta-B二硼化物系统的深度学习潜力被拟合，其能量和力的预测误差分别为9.2 meV /原子和208 meV /Å。然后，评估了从0°C到2400°C的温度依赖性晶格常数，各向异性热膨胀，各向异性声子热导率和高熵（Ti _0.2 Zr _0.2 Hf _0.2 Nb _0.2 Ta _0.2）B _2的弹性，室温值与实验测量值非常吻合。另外，（Ti _0.2的固有晶格畸变的Zr _0.2的Hf _0.2的Nb _0.2的Ta _0.2）乙₂是由原子的位移从自己的理想位置，这是在10的顺序分析^-3埃和幅度比在（TI小一个顺序_0.2的Zr _0.2的Hf _0.2的Nb _0.2 Ta _0.2 ℃。表明（Ti _0.2 Zr _0.2 Hf _0.2 Nb _0.2 Ta _0.2）B ₂中的晶格畸变没有预期的那么严重。借助机器学习潜力的新范例，将来可以实现对高熵材料的深入了解，因为机器学习潜力可以很好地处理高熵材料中复杂的化学和结构。