KCl–CaCl₂ molten salt has emerged as a potential candidate which can be used for heat transfer and thermal energy storage in the next concentrating solar power generation. In this work, deep potential molecular dynamics (DPMD) simulations, based on a many-body potential and interatomic forces generated by a deep neural network trained with the first-principles simulation results, were carried out to predict the local structure and thermophysical properties of KCl–CaCl₂ molten salt at 1100 K. It was found that the steric hindrance effect became more and more intense as the network structure forming and growing with the addition of CaCl₂, but the increase of CaCl₂ made the coordination shell of Ca²⁺ more dynamic and active, and the two reactions constantly compete. Afterwards, thermophysical properties like shear viscosity, heat capacity and thermal conductivity were calculated from DPMD simulations. DPMD simulations could balance the proper description of complex atomic interactions to overcome the challenge of missing potential parameters in classical molecular simulations and become more efficient than first-principles molecular dynamics simulations. Our work based on deep potentials development will provide a promising alternative way to explore more molten eutectic salts for the next concentrating solar power generation.

KCl-CaCl ₂熔盐已成为潜在的候选者，可用于下一次聚光太阳能发电的传热和热能储存。在这项工作中，基于由第一性原理模拟结果训练的深度神经网络产生的多体势和原子间力，进行了深势分子动力学（DPMD）模拟，以预测局部结构和热物理性质。 KCL-的CaCl ₂在1100 K.它熔盐发现，空间位阻效应成为作为网络结构中形成并通过加入氯化钙的越来越大，越来越强烈₂，但是氯化钙的增加₂制成Ca的协调壳^{2 +}更有活力和主动性，两种反应不断竞争。然后，根据 DPMD 模拟计算剪切粘度、热容量和热导率等热物理特性。DPMD 模拟可以平衡复杂原子相互作用的正确描述，以克服经典分子模拟中缺少潜在参数的挑战，并且比第一性原理分子动力学模拟更有效。我们基于深部电位开发的工作将为探索更多熔融共晶盐以用于下一次聚光太阳能发电提供一种有前途的替代方法。