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冲击电渗析理论I:水离解与电渗涡旋

Theory of shock electrodialysis I: Water dissociation and electrosmotic vortices.

作者信息

Tian Huanhuan, Alkhadra Mohammad A, Bazant Martin Z

机构信息

Department of Chemical Engineering, Massachusetts Institute of Technology, MA 02139, USA.

Department of Chemical Engineering, Massachusetts Institute of Technology, MA 02139, USA; Department of Mathematics, Massachusetts Institute of Technology. MA 02139, USA.

出版信息

J Colloid Interface Sci. 2021 May;589:605-615. doi: 10.1016/j.jcis.2020.12.125. Epub 2021 Jan 28.

Abstract

Shock electrodialysis (shock ED), an emerging electrokinetic process for water purification, leverages the new physics of deionization shock waves in porous media. In previous work, a simple leaky membrane model with surface conduction can explain the propagation of deionization shocks in a shock ED system, but it cannot quantitatively predict the deionization and conductance (which determines the energy consumption), and it cannot explain the selective removal of ions in experiments. This two-part series of work establishes a more comprehensive model for shock ED, which applies to multicomponent electrolytes and any electrical double layer thickness, captures the phenomena of electroosmosis, diffusioosmosis, and water dissociation, and incorporates more realistic boundary conditions. In this paper, we will present the model details and show that hydronium transport and electroosmotic vortices (at the inlet and outlet) play important roles in determining the deionization and conductance in shock ED. We also find that the results are quantitatively consistent with experimental data in the literature. Finally, the model is used to investigate design strategies for scale up and optimization.

摘要

冲击电渗析(shock ED)是一种新兴的用于水净化的电动过程,它利用了多孔介质中去离子化冲击波的新物理原理。在之前的工作中,一个具有表面传导的简单漏电膜模型可以解释冲击电渗析系统中去离子化冲击波的传播,但它无法定量预测去离子化和电导率(电导率决定了能量消耗),也无法解释实验中离子的选择性去除。这一分为两部分的系列工作为冲击电渗析建立了一个更全面的模型,该模型适用于多组分电解质和任何双电层厚度,捕捉了电渗析、扩散渗透和水离解现象,并纳入了更现实的边界条件。在本文中,我们将展示模型细节,并表明水合氢离子传输和电渗涡流(在入口和出口处)在确定冲击电渗析中的去离子化和电导率方面起着重要作用。我们还发现结果与文献中的实验数据在数量上是一致的。最后,该模型用于研究放大和优化的设计策略。

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