标题： 多价电解质混合物饱和多孔介质中的扩散泳现象 显示英文标题

标题： Diffusiophoresis in porous media saturated with a mixture of electrolytes

摘要： 当前关于多孔介质中扩散泳的理论仅限于饱和有价对称电解质的多孔介质。 对于饱和有价不对称电解质或价对称和不对称电解质的一般混合物的多孔介质中的扩散泳，缺乏预测模型。 为填补这一知识空白，本文我们开发了一个数学模型，该模型基于常规摄动方法和数值积分，用于计算饱和有电解质一般混合物的多孔介质中胶体的扩散泳迁移率。 我们使用泊松-能斯特-普朗克方程来模拟电动力学，使用布林克曼方程结合电体力来模拟多孔介质中的流体传输。 我们报告了三个新的关键发现。 首先，我们证明在相同的电解质浓度梯度下，降低多孔介质的渗透率可以显著减弱胶体的扩散泳运动。 其次，我们表明，令人惊讶的是，使用价不对称电解质，胶体在更致密的多孔介质中的扩散泳运动可能比在较不致密的多孔介质中饱和有对称电解质时更强。 第三，我们证明改变电解质混合物的组成不仅会极大地改变胶体扩散泳运动的强度，还会定性地改变其方向。 本研究开发的模型可用于理解并预测诸如细胞内运输等自然现象，以及设计增强石油开采、纳米粒子药物输送和胶体物种分离等技术应用。 显示英文摘要

摘要： Current theories of diffusiophoresis in porous media are limited to a porous medium saturated with a valence symmetric electrolyte. A predictive model for diffusiophoresis in porous media saturated with a valence asymmetric electrolyte, or a general mixture of valence symmetric and asymmetric electrolytes, is lacking. To close this knowledge gap, in this work we develop a mathematical model, based upon the regular perturbation method and numerical integration, to compute the diffusiophoretic mobility of a colloid in porous media saturated with a general mixture of electrolytes. We model the electrokinetics using the Poisson-Nernst-Planck equations and the fluid transport in porous media using the Brinkman equation with an electric body force. We report three novel key findings. First, we demonstrate that, in the same electrolyte concentration gradient, lowering the permeability of the porous medium can significantly weaken the colloid diffusiophoretic motion. Second, we show that, surprisingly, by using a valence asymmetric electrolyte the colloid diffusiophoretic motion in a denser porous medium can be stronger than that in a less dense porous medium saturated with a symmetric electrolyte. Third, we demonstrate that varying the composition of an electrolyte mixture does not only change the strength of the colloid diffusiophoretic motion drastically, but also qualitatively its direction. The model developed from this work can be used to understand and predict natural phenomena such as intracellular transport, as well as design technological applications such as enhanced oil recovery, nanoparticle drug delivery, and colloidal species separation.