Zhang Chunyi, Yue Shuwen, Panagiotopoulos Athanassios Z, Klein Michael L, Wu Xifan
Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA.
Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA.
Phys Rev Lett. 2023 Aug 18;131(7):076801. doi: 10.1103/PhysRevLett.131.076801.
The dielectric permittivity of salt water decreases on dissolving more salt. For nearly a century, this phenomenon has been explained by invoking saturation in the dielectric response of the solvent water molecules. Herein, we employ an advanced deep neural network (DNN), built using data from density functional theory, to study the dielectric permittivity of sodium chloride solutions. Notably, the decrease in the dielectric permittivity as a function of concentration, computed using the DNN approach, agrees well with experiments. Detailed analysis of the computations reveals that the dominant effect, caused by the intrusion of ionic hydration shells into the solvent hydrogen-bond network, is the disruption of dipolar correlations among water molecules. Accordingly, the observed decrease in the dielectric permittivity is mostly due to increasing suppression of the collective response of solvent waters.
随着盐溶解量增加，盐水的介电常数会降低。近一个世纪以来，这种现象一直通过溶剂水分子介电响应的饱和度来解释。在此，我们利用基于密度泛函理论数据构建的先进深度神经网络（DNN）来研究氯化钠溶液的介电常数。值得注意的是，使用DNN方法计算得到的介电常数随浓度的降低与实验结果吻合良好。对计算结果的详细分析表明，离子水化层侵入溶剂氢键网络所产生的主要影响是水分子间偶极相关性的破坏。因此，观察到的介电常数降低主要是由于溶剂水集体响应受到越来越大的抑制。
