An Electrodiffusion Model Coupled with Fluid-Flow Effects for an On-Chip Electromembrane Extraction System

被引:0
|
作者
Roshanak Dolatabadi
Ziba Gharehnazifam
Fatemeh Moraffah
Ali Mohammadi
Mostafa Baghani
机构
[1] Tehran University of Medical Sciences,Department of Drug and Food Control, Faculty of Pharmacy
[2] University of Tehran,School of Mechanical Engineering, College of Engineering
[3] Tehran University of Medical Sciences,Department of Pharmaceutics, Faculty of Pharmacy
来源
Transport in Porous Media | 2022年 / 142卷
关键词
On-chip EME; Ionic drugs; Computational model; Nernst–Planck; Poisson; Navier–Stokes equations; FEM;
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学科分类号
摘要
This paper proposes the first computational modeling of a miniaturized version of an electromembrane extraction (EME) setup to a chip format, where the donor solution is delivered by a syringe pump to the sample reservoir. This system can be used for extraction of different analytes e.g., ionic drugs in wastewater. To design, analyze and optimize the entire process of extraction, a deep understanding of the mechanisms responsible for the analyte transport plays a key role. However, the interplay between the passive diffusion, fluid flow (convective diffusion), and electrokinetically driven SLM transfer may result in different mass transport patterns. A two-dimensional numerical model is developed to study the mass transport as well as the recovery in this on-chip EME. In order to simulate the mass transport of different analyte species, the electric field distribution, and the fluid flow, we made use of the Nernst–Planck, Poisson and Navier–Stokes equations, respectively. For all three mentioned fields (mass transport, electric field and fluid flow), appropriate boundary conditions are assigned to the setup borders to mathematically represent the real conditions of the device. The governing equations are solved by finite element method. It was revealed that at higher sample flow rates, a lower system recovery is predicted, e.g., from 80 to 60%, while higher voltages (smaller than a critical voltage) amplifies the recovery up to e.g., 75%. The presented model can predict the impact of different factors, e.g., sample flow rate, applied voltage, and extraction time on the system recovery, which are qualitatively in agreement with experimental results.
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页码:317 / 331
页数:14
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