Electroosmotic Flow Research Articles

Quantitative performance analysis of anion-exchange membrane fuel cells with in-plane and through-plane water transport

Effective water management is crucial in anion-exchange membrane fuel cells (AEMFCs) due to water's dual role as a reactant during alkaline oxygen reduction and a product of alkaline hydroxide oxidation. Meanwhile, both hydroxide conduction and water transport in polymer electrolytes are highly dependent on the hydration level. Therefore, a three-dimensional multi-physics model is developed to investigate the critical role of ionic and water transport parameters of the electrolyte on AEMFC performance. Additionally, detailed water distribution analysis is used to reveal its fundamental mechanism. The results reveal that extremely inhomogeneous water distribution and cathode water starvation are the main causes of the poor cell performance. Moreover, increasing membrane water diffusivity, water conversion, and decreasing the electro-osmotic drag coefficient all contribute to better cell performance through improved water balance and cathode water supply. Among these, cell performance is most sensitive to membrane water diffusivity, with a 40 % increase in peak power density when it is increased from 10−10 m2 s−1 to 10−9 m2 s−1. Although high ionic conductivity improves cell performance by directly reducing ohmic impedance, it also results in a more inhomogeneous distribution of water in the whole cell, so that a four-fold increase in ionic conductivity only yields a 62 % increase in peak power density.

Electromagnetohydrodynamic flow and thermal performance in a rotating rough surface microchannel

Rough surfaces in microchannels effectively enhance liquid mixing, thermal performance, and chemical reactions in electrically actuated microfluidic devices. Rotation of the microchannel with surface roughness intensifies this enhancement. We investigate the combined effects of electromagnetohydrodynamics and surface roughness on transient rotating flow in microchannels. We present a mathematical model considering the variable zeta potential, heat transfer characteristics, and entropy generation within the microchannel. We obtain analytical solutions using the separation of variables method and Fourier series expansion. The surface roughness of the microchannel, when combined with rotation, impacts the temperature enhancement. Higher rotation rates result in the formation of multiple vortices. The secondary flow pushes the primary velocity toward the boundary layer, which affects the flow pattern. Surface roughness and electroosmotic flow significantly affect secondary flow, resulting in complex flow patterns and reversals. The interaction between centrifugal and viscous forces results in maximum velocities at the boundary layers. Higher roughness and electromagnetic effects enhance temperature by intensifying fluid-solid friction and joule heating. Surface roughness causes an increase in wall shear stress and friction factor, resulting in a higher Poiseuille number. Moreover, surface roughness increases entropy production by enhancing fluid mixing and internal friction despite improved heat transfer. Higher rotation also elevates entropy generation due to additional vortices induced by secondary flow.

Bilaterally Aligned Electroosmotic Flow Generated by Porous Microneedle Device for Dual‐Mode Delivery (Adv. Healthcare Mater. 22/2024)

Bilaterally Aligned Electroosmotic Flow Generated by Porous Microneedle Device for Dual‐Mode Delivery (Adv. Healthcare Mater. 22/2024)

Parametric study of PEM water electrolyzer performance

AbstractGreen hydrogen can contribute significantly to combating climate change by helping to establish an energy economy that is both sustainable and carbon-free. One pathway to obtaining green hydrogen is by water electrolysis powered by renewable energy. Proton exchange membrane water electrolysis (PEMWE) is a promising option owing to its high current density at high efficiency. Here, we report on experimental results from a parametric investigation of PEMWE. We have examined the effect of water flow rate at 80 °C using a 5 cm2 PEM electrolyzer cell hardware and lab-fabricated membrane electrode assemblies. The results showed that a water flow rate of 0.08 ml cm−2 min−1 was sufficient to meet the water consumption by electrochemical reactions at the anode as well as water depletion by diffusion and electroosmotic drag. We then employed this optimal flow rate to examine the effect of various operating parameters on PEMWE performance and efficiency such as operating temperature, membrane thickness, flow field channel configuration, and porous transport layers as a function of the applied voltage. The results provide useful insights into the operating conditions for optimal PEMWE performance. Graphical abstract

A simple and efficient approach for preparing cationic coating with tunable electroosmotic flow for capillary zone electrophoresis-mass spectrometry-based top-down proteomics

BackgroundCapillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has become a valuable analytical technique in top-down proteomics (TDP). CZE-MS/MS-based TDP typically employs separation capillaries with neutral coatings (i.e., linear polyacrylamide, LPA). However, issues related to separation resolution and reproducibility remain with the LPA-coated capillaries due to the unavoidable non-specific protein adsorption onto the capillary wall. Cationic coatings can be critical alternatives to LPA coating for CZE-MS/MS-based TDP due to the electrostatic repulsion between the positively charged capillary inner wall and proteoform molecules in the acidic separation buffer. Unfortunately, there are only very few studies using cationic coating-based CZE-MS/MS for TDP studies. ResultsIn this work, we aimed to develop a simple and efficient approach for preparing separation capillaries with a cationic coating, i.e., poly (acrylamide-co-(3-acrylamidopropyl) trimethylammonium chloride [PAMAPTAC]) for CZE-MS/MS-based TDP. The PAMAPTAC coating-based CZE-MS produced significantly better separation resolution of proteoforms compared to the traditionally used LPA-coated approach. It achieved reproducible separation and measurement of a simple proteoform mixture and a complex proteome sample (i.e., a yeast cell lysate) regarding migration time, proteoform intensity, and the number of proteoform identifications. The PAMAPTAC coating-based CZE-MS enabled the detection of large proteoforms (≥30 kDa) from the yeast cell lysate reproducibly without any size-based prefractionation. Interestingly, the mobility of proteoforms using the PAMAPTAC coating can be predicted accurately using a simple semi-empirical model. SignificanceThe results render the PAMAPTAC coating as a valuable alternative to the LPA coating to advance CZE-MS-based TDP towards high-resolution separation and highly reproducible measurement of proteoforms in complex samples.

Single-Molecule Identification and Quantification of Steviol Glycosides with a Deep Learning-Powered Nanopore Sensor.

Steviol glycosides (SGs) are a class of high-potency noncalorie natural sweeteners made up of a common diterpenoid core and varying glycans. Thus, the diversity of glycans in composition, linkage, and isomerism results in the tremendous structural complexity of the SG family, which poses challenges for the precise identification and leads to the fact that SGs are frequently used in mixtures and their variances in biological activity remain largely unexplored. Here we show that a wild-type aerolysin nanopore can detect and discriminate diverse SG species through the modulable electro-osmotic flow effect at varied applied voltages. At low voltages, the neutral SG molecule was drawn and stuck in the pore entrance due to an energy barrier around R220 sites. The ensuing binding events enable the identification of the majority of SG species. Increasing the voltage can break the barrier and cause translocation events, allowing for the unambiguous identification of several pairs of SGs differing by only one hydroxyl group through recognition accumulation from multiple sensing regions and sites. Based on nanopore data of 15 SGs, a deep learning-based artificial intelligence (AI) model was created to process the individual blockage events, achieving the rapid, automated, and precise single-molecule identification and quantification of SGs in real samples. This work highlights the value of nanopore sensing for precise structural analysis of complex glycans-containing glycosides, as well as the potential for sensitive and rapid quality assurance analysis of glycoside products with the use of AI.

Applied Electric Field Effects on Diffusivity and Electrical Double-Layer Thickness.

This study utilizes molecular dynamics (MD) simulations and continuum frameworks to explore electroosmotic flow (EOF) in nanoconfined aqueous electrolytes, offering a promising alternative to conventional micro-/nanofluidic systems. Although osmotic behavior in these environments is deeply linked to local fluid properties and interfacial dynamics between the fluid and electrolyte solutions, achieving a complete molecular-level understanding has remained challenging. The findings establish a linear relationship between electric field strength and fluid velocity, uncovering two distinct transport regimes separated by a critical threshold, with a markedly intensified flow in the second regime. It is demonstrated that rising electric field strengths significantly enhance water diffusion coefficients, supported by a detailed analysis of fluid hydration structures, the potential of mean force (PMF), and local stress tensors. Due to the applied electric field strength, the motion of ions and water accelerates, leading to the redistribution of ions and intensification of electrostatic forces. This expands the thickness of the electric double layer (EDL) and amplifies fluid diffusivity, thereby enhancing nanoscale fluid activity. These insights enhance the molecular-level understanding of EOF and define the stability of flow regimes, providing valuable guidelines for advancing nanofluidic technologies, such as drug delivery systems and lab-on-a-chip devices.

Combination of on-line sample preconcentration by large-volume dual preconcentration by isotachophoresis and stacking (LDIS) with field-amplified sample injection (FASI) on Y-channel microchips.

In our previous study, the combination of two on-line sample preconcentration techniques, large-volume sample stacking with an electroosmotic flow (EOF) pump (LVSEP) and transient isotachophoresis (tITP), in microchip electrophoresis (MCE) was developed, which was named large-volume dual preconcentration by isotachophoresis and stacking (LDIS). LDIS was apparently effective for improving the sensitivity and the peak shape. In LDIS, however, there was a limit to the improvement of the sensitivity enhancement factor (SEF) since the amount of analytes to be concentrated was limited to the channel volume. To overcome this issue, in the present article, LDIS was coupled with field-amplified sample injection (FASI) technique on Y-shaped channel microchips. The use of a Y-channel in LDIS-FASI allowed consecutive LVSEP, FASI and tITP enrichments with a simple voltage control. In conventional LVSEP and LDIS analyses of a standard analyte, the SEFs were evaluated to be 2630 and 13,100, respectively, whereas in LDIS-FASI that was increased to 27,900 even at the FASI injection time of 0s. To achieve higher SEFs, furthermore, the FASI injection time was increased to 150s, resulting in the best SEF of 58,500. It should be emphasized that the peak width in LDIS-FASI was quite narrow, only 0.3-3.1s, while in normal LVSEP that was 13s. Furthermore, the LDIS-FASI technique was applied to the analysis of oligosaccharide mixture. Due to the focusing effect by LDIS-FASI, the resolutions were improved from 0.97-1.57 to 2.08-2.73.

Combined electroosmotic and pressure driven flow through soft nanochannel grafted with partially ion-penetrable polyelectrolyte layers

ABSTRACT This study explores the coupled effects of pressure-driven and electroosmotic flows in a soft nanochannel filled with non-Newtonian ionised liquid, where the inner walls are coated with a polymer layer. The ion partitioning effect occurs due to the Born energy, arising from the dielectric permittivity difference between the polyelectrolyte medium and the ionised liquid. The model incorporates the nonlinear Poisson-Boltzmann equation, the modified Darcy-Brinkman equation in the polyelectrolyte layer (PEL), the Cauchy momentum equation in the electrolyte domains and the continuity equation for incompressible fluids. Using the Debye-Hückel approximation for analytical results, the study validates numerical findings. The study considers the no-slip boundary condition on the walls and examines the impact of volume charge density of PEL, bulk electrolyte concentration, non-Newtonian fluid rheology and polymer layer characteristics and applied pressure gradient on flow modulation and ionic transport in the nanochannel. We provide rigorous mathematical results showing how electrohydrodynamic factors like charged PEL, flow behaviour index, EDL thickness, ion partitioning parameters, Debye-Hückel parameter and softness parameters influence the strength of the potential and the total flow modulation. We illustrate ion selectivity in the soft nanochannel and the friction factor across its walls, considering ion partitioning effects.

Effect of magnetic field and hydrodynamic slippage on electro-osmotic Brinkman flow through patterned zeta potential microchannel

Effect of magnetic field and hydrodynamic slippage on electro-osmotic Brinkman flow through patterned zeta potential microchannel

Optimizing heat transfer with electro-osmotic ciliated propulsion in a non-uniform canals with Cu-blood characteristics considering thermal casson nano fluid

Electroosmosis peristaltic flows find promising applications in electro-fluid thrusters in space propulsion, polymer injection systems, ion exchange membrane designs, microbe fuel cells, biochip fabrication and fossil fuel energy process. In light of this, the current work aims to investigate blood based electroosmotic peristaltic flow in a ciliated, non-uniform propagation channel when copper nanoparticles are present. For that purpose, mathematical modeling is done in two dimensional frame and then governing partial differential equations are simplified and converted in ordinary differential equations using dimensionless quantities and long wave length and low Reynolds number approximations. In result we got coupled nonlinear boundary value problem that is solved numerically using three-stage Lobatto IIIa formula known as bvp4c invoking shooting technique. Peristaltic ciliated waves are thought to pass along the channel wall. The properties of both fluid phase and particle phase flow are modeled and investigated. Plotting against various parameters, streamline contours, temperature contours, concentration and temperature profiles, and pressure rise graphs are examined in-depth from a physical perspective. The obtained results revealed that concentration profile α upsurges for rising values of Casson fluid parameter β, nanoparticle volume fraction ϕ and flow rate Q while it drops with an increase in particulate volumetric fraction C, Eckert number Ec, Soret number Sr, Schmidt number Sc and viscosity constant. A decrease in temperature is also caused by an increase in the volumetric percentage of nanoparticles. In the pumping portion, there is a decrease in pressure rise; however, this decrease changes to an increase in the increased pumping zone.

The effect of asymmetric zeta potentials on the electro-osmotic flow of a generalized Phan–Thien–Tanner fluid

Electrokinetic flows driven by electro-osmotic forces are especially relevant in micro and nano-devices, presenting specific applications in medicine, biochemistry, and miniaturized industrial processes. In this work, we integrate analytical solutions with numerical methodologies to explore the fluid dynamics of viscoelastic electro-osmotic/pressure-driven fluid flows (described by the generalized Phan–Thien–Tanner (gPTT) constitutive equation) in a microchannel under asymmetric zeta potential conditions. The constitutive equation incorporates the Mittag–Leffler function with two parameters (α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document} and β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta $$\\end{document}), which regulate the rate of destruction of junctions in a network model. We analyze the impact of the various model parameters on the velocity profile and observe that our newly proposed model provides a more comprehensive depiction of flow behavior compared to traditional models, rendering it suitable for modeling complex viscoelastic flows.

Development of cyclodextrin-electrokinetic chromatography-based strategies for the separation of ketorolac enantiomers

The development of analytical strategies enabling the chiral separation of ketorolac by electrokinetic chromatography is presented in this work. This anti-inflammatory drug is commercialised as racemic mixture but its physiological activity resides in the S-enantiomer. Different experimental conditions were investigated at acidic and neutral pH, including the use of cyclodextrins (CD) or amino acid-based ionic liquids (AAILs) ([TMA][L-Cit], [TMA][L-Arg], [TMA][L-Harg], [TBA][L-Cit], [TBA][L-Arg], and [TBA][L-Harg]) as the sole chiral selectors or the combination of a CD with AAILs or their cationic components (tetramethylammonium (TMA-OH) or tetrabutylammonium (TBA-OH)). The best conditions in terms of migration times and enantiomeric resolutions were obtained using 2 mM heptakis(2,3,6-tri-O-methyl)-β-CD (TM-β-CD) in 50 mM phosphate buffer at pH 7.0 or 2 mM TM-β-CD with 60 mM TMA-OH in 50 mM formate buffer at pH 3.0. The presence of TMA-OH in the separation medium affected considerably the electroosmotic flow (EOF) mobility which, in turn, significantly shortened the migration times for ketorolac enantiomers at pH 3.0 due to an inversion in the EOF. The multivariate optimization of the experimental conditions for the single system and for the combined system with TMA-OH enabled to obtain the separation of ketorolac enantiomers in less than 11 min with enantiomeric resolutions of 2.5 and 1.9, respectively. The single system was selected to evaluate its analytical characteristics in terms of limits of detection/quantification, accuracy, and precision, according to the International Council for Harmonization (ICH) guidelines, which resulted adequate to be applied to the analysis of pharmaceutical formulations.

Modeling Water Transport in Polymer Electrolyte Membrane Electrolyzers Using a One-Dimensional Transport Model

In this work, we present a water transport model to quantify the movement of water across Nafion® membranes in a proton exchange membrane electrolyzer as a function of varying operating conditions and membrane parameters. This physics-based model is based on the three main water transport mechanisms: diffusion, electro-osmotic drag, and pressure-driven flow. Three sets of equations are obtained to model the movement of water on the cathode side – I. Material balances for hydrogen and water in the flow channel (z-direction), II. Water movement across the membrane in the x-direction, and III. Expressions for variable membrane properties to serve as model inputs. The condensation of water at the cathode is also modeled to understand the respective transport contributions from the vapor and liquid phases. The coupled equation sets are solved numerically with appropriate boundary conditions. An analytical solution is also obtained for the governing differential equation for the mole fraction of water in the vapor phase. This study is perhaps the first effort for a detailed physics-based transport model to predict the water transport in the electrolyzer in one dimension using the actual measured values for the physical parameters of the system. The model results are compared with the experimental data available for water transport, and a good agreement is observed over the wide range of current, temperature and pressure differentials. Further, with the help of this simple transport model, the numerical analysis is performed to delineate the effect of electrolyzer operating conditions on the net water transport across the membrane, water condensation at the cathode, individual contribution of the transport fluxes, and electrolyzer design. Finally, the model is exercised to simulate the dependence of water transport as a function of membrane thickness. This confirms the validity of the current approach of using thin reinforced membranes by electrolyzer fabricators. Figure 1

Influence of Different Operating Conditions on Iridium Dissolution in a Proton Exchange Membrane Water Electrolyzer

Polymer electrolyte membrane (PEM) water electrolysis plays a key role in the global decarbonization scheme by coupling the intermittent renewable energy sources to the production of high-purity hydrogen. Its deployment onto a GW scale, however, is hindered by the cost and availability of the precious metal catalysts utilized in today’s commercial systems, primarily by that of Ir used as the anode catalyst for the oxygen evolution reaction (OER). With the continuous increase in the demand for carbon-free hydrogen, drastic reductions from the current Ir loading of 1 – 2 mgIr cm-2 by at least an order of magnitude, without compromising the overall electrolyzer performance, are of crucial importance.1 In the recent years, significant efforts have been focused on understanding PEM electrolyzer degradation mechanisms and developing the necessary mitigation strategies, with a special focus being placed on the anode catalyst layer (CL).2-4 Recent results from our group showed that there are two main pathways for Ir to be removed from the anode CL: dissolution into the anode water line and transport through the membrane and the cathode CL.5 In the present work, we aim to shed light onto the effects influencing Ir dissolution under intermittent operation by quantitative analysis of the main Ir sinks within an electrolyzer and the determination of the charge of the dissolved Ir species.5, 6 Various accelerated stress tests with square-wave configuration aimed at accelerating Ir-based anode CL degradation were performed and the results were compared to those obtained during steady-state operation of the electrolyzer cell, which was used as a reference point. The influence of electro-diffusion, electroosmotic drag and Ir redeposition back to the ACL onto Ir dissolution were analyzed in detail to obtain deeper understanding on the Ir degradation processes. M. Clapp, C. M. Zalitis, M. Ryan, Perspectives on current and future iridium demand and iridium oxide catalysts for PEM water electrolysis. Catal Today 420, (2023). S. M. Alia et al., Electrolyzer Performance Loss from Accelerated Stress Tests and Corresponding Changes to Catalyst Layers and Interfaces. J Electrochem Soc 169, (2022). Z. Q. Zeng et al., Degradation Mechanisms in Advanced MEAs for PEM Water Electrolyzers Fabricated by Reactive Spray Deposition Technology. J Electrochem Soc 169, (2022). A. Weiss et al., Impact of Intermittent Operation on Lifetime and Performance of a PEM Water Electrolyzer. J Electrochem Soc 166, F487-F497 (2019). M. Milosevic et al., In Search of Lost Iridium: Quantification of Anode Catalyst Layer Dissolution in Proton Exchange Membrane Water Electrolyzers. Acs Energy Lett 8, 2682-2688 (2023). A. P. Dam, B. Y. A. Abuthaher, G. Papakonstantinou, K. Sundmacher, Insights into the Path-Dependent Charge of Iridium Dissolution Products and Stability of Electrocatalytic Water Splitting. J Electrochem Soc 170, (2023).

(Invited) Advances in Modeling Ion Transport in Micropores and Charging Behavior of Porous Electrodes: Merging Molecular Insights with Machine Learning for Energy Storage

Electric double layer (EDL) charging is a complex process coupling electro-osmotic flow, surface reactions, and ion concentration gradients. The charging dynamics depends on the properties of electrolyte and electrode structure, as well as initial and boundary conditions. While molecular dynamics (MD) simulations and first-principles calculations can encompass all factors, their computational demands are substantial even for simple electrochemical systems such as electrolytes near a planar surface. This presentation explores recent advancements in modeling ion transport in micropores and the charging behavior of porous electrodes with different theoretical and simulation methods. Illustrative examples will be discussed on the integration of molecular modeling and machine-learning techniques to enhance our understanding of complex electrochemical processes and improve the design of energy storage devices.

Mathematical and artificial neural network modeling to predict the heat transfer of mixed convective electroosmotic nanofluid flow with Helmholtz-Smoluchowski velocity and multiple slip effects: An application of soft computing

The growing popularity of artificial neural networks (ANNs) is due to their exceptional capability in handling complex and highly nonlinear mathematical problems. ANNs provide a flexible computational framework that is extremely useful in complex fields such as biological computation, fluid dynamics, and biotechnology. Consequently, this study utilizes machine learning techniques to examine the heat transfer in mixed convective Electroosmotic Nanofluid flow, considering Helmholtz-Smoluchowski velocity and multiple slip effects on an exponentially stretching surface. Different influential factors, including, thermal radiation, viscous dissipation, joule heating, linear thermal heat source/sink and exponential thermal heat source/sink are considered in this investigation. In the current study, graphene oxide and magnesium oxide are used as nanomaterials, with ethylene glycol serving as the base fluid. The bvp4c solver in Matlab is employed to solve nonlinear versions of established mathematical problems, including those related to the skin friction coefficient, heat transfer rates, velocity, and temperature. The artificial neural network model is structured to handle several tasks: data selection, network construction, network training, and evaluating performance employing the mean square error metric. The significance of parameter on subjective profiles is demonstrated though tables and graphical representation. The Numerical results and artificial neural network results have been compared. The results showed that there is excellent validation between numerical results and artificial neural network results.

Effect analysis of copper and brass electrodes on the electroosmotic flow in high saline soil

Effect analysis of copper and brass electrodes on the electroosmotic flow in high saline soil

Electrokinetic Remediation of Cu- and Zn-Contaminated Soft Clay with Electrolytes Situated above Soil Surfaces.

Electrokinetic remediation (EKR) has shown great potential for the remediation of in situ contaminated soils. For heavy metal-contaminated soft clay with high moisture content and low permeability, an electrokinetic remediation method with electrolytes placed above the ground surface is used to avoid issues such as electrolyte leakage and secondary contamination that may arise from directly injecting electrolytes into the soil. In this context, using this novel experimental device, a set of citric acid (CA)-enhanced EKR tests were conducted to investigate the optimal design parameters for Cu- and Zn-contaminated soft clay. The average removal rates of heavy metals Cu and Zn in these tests were in the range of 27.9-85.5% and 63.9-83.5%, respectively. The results indicate that the Zn removal was efficient. This was determined by the migration intensity of the electro-osmotic flow, particularly the volume reduction of the anolyte. The main factors affecting the Cu removal efficiency in sequence were the effective electric potential of the contaminated soft clay and the electrolyte concentration. Designing experimental parameters based on these parameters will help remove Cu and Zn. Moreover, the shear strength of the contaminated soil was improved; however, the degree of improvement was limited. Low-concentration CA can effectively control the contact resistance between the anode and soil, the contact resistance between the cathode and soil, and the soil resistance by increasing the amount of electrolyte and the contact area between the electrolyte and soil.

Non-isothermal electroosmotic flow of a viscoelastic fluid through a porous medium in a microchannel

The influence of the temperature-dependent viscosity on the electroosmotic flow through a porous medium in a microchannel of parallel flat plates. At the end, an imposed electric field induces Joule heating and temperature gradients, modifying the viscosity of the fluid. The Phan-Thien–Tanner and Darcy–Forchheimer models describe the viscoelastic fluid through the porous media. Consequently, the electric double layer (EDL) overlaps at the center plane of the microchannel, causing an electrically charged porous matrix and modifying the zeta potential along the microchannel walls. Therefore, we define a zeta potential ratio of the porous matrix and that at the microchannel walls. Unlike similar investigations, the boundary condition for the zeta potential varies locally due to the temperature field, modifying the interaction among hydrodynamics, electrical, viscoelastic, thermal and porosity effects. A modified Péclet number is defined as a function of the porosity and thermal conductivity of the fluid and an effective charge density is determined based on the Poisson–Boltzmann equation, accounting for the pore size and the zeta potential ratio. The set of equations are solved numerically considering the lubrication approximation theory. We found that the influence of the temperature-dependent viscosity increases the shear stresses at the EDL region, particularly where the temperature rises to maximum values. Also, the overlapping of the EDL occurs mainly for low values of permeability. Finally, the pressure gradient involved in the Darcy law can be altered through the zeta potential ratio.