Numerical Simulation for efficient mixing of Newtonian and non-Newtonian fluids in an electro-osmotic micro-mixer

Shamloo, Amir; Mirzakhanloo, Mehdi; Dabirzadeh, Mohammad Reza

doi:10.1016/j.cep.2016.06.003

Cited by 46 publications

(14 citation statements)

References 25 publications

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“…The current lines were parallel to the longitudinal axis and the flow was fully developed. However, when the electric field was applied, we see that certain circular vortices appeared, which increased the mixing quality significantly (see Figure 2b), as shown in previous work [34]. This figure also gives us information that the vortices were close to the wall of the electrodes and depended on their positions.…”

Section: Electroosmotic Flowsupporting

confidence: 84%

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AC Electroosmosis Effect on Microfluidic Heterogeneous Immunoassay Efficiency

Selmi

Belmabrouk

2020

Micromachines

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A heterogeneous immunoassay is an efficient biomedical test. It aims to detect the presence of an analyte or to measure its concentration. It has many applications, such as manipulating particles and separating cancer cells from blood. The enhanced performance of immunosensors comes down to capturing more antigens with greater efficiency by antibodies in a short time. In this work, we report an efficient investigation of the effects of alternating current (AC) electrokinetic forces such as AC electroosmosis (ACEO), which arise when the fluid absorbs energy from an applied electric field, on the kinetics of the antigen–antibody binding in a flow system. The force can produce swirling structures in the fluid and, thus, improve the transport of the analyte toward the reaction surface of the immunosensor device. A numerical simulation is adequate for this purpose and may provide valuable information. The convection–diffusion phenomenon is coupled with the first-order Langmuir model. The governing equations are solved using the finite element method (FEM). The impact of AC electroosmosis on the binding reaction kinetics, the fluid flow stream modification, the analyte concentration diffusion, and the detection time of the biosensor under AC electroosmosis are analyzed.

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Section: Electroosmotic Flowsupporting

confidence: 84%

“…The fluid slip velocity on the electrode was deduced from the Helmholtz-Smoluchowski relationship, which links the electroosmotic velocity to the tangential component of the applied electric field [34][35][36][37][38].…”

Section: Electroosmotic Flow Modelingmentioning

confidence: 99%

AC Electroosmosis Effect on Microfluidic Heterogeneous Immunoassay Efficiency

Selmi

Belmabrouk

2020

Micromachines

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“…Optimal meshing sample (a) (I) passive micromixer and (II) pure active micromixer; (b) comparison of concentration profile line plot near at the outlet of the micromixer and published work 30. The current study model validated quantitatively.…”

mentioning

confidence: 75%

“…For the validation of current paper simulation model, first qualitative and quantitative comparison of the current model results are carried out with already published work. 30 Accordingly, identical geometry designed, meshed in COMSOL 5.3 with similar boundary conditions is applied at inlets and outlets of micromixer. The comparison of results quantitatively is shown in Figure 2.…”

Section: Validation Of Modelmentioning

confidence: 99%

Optimal parametric mixing analysis of active and passive micromixers using Taguchi method

Shah

Jeon

Ali

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part E:

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Mixing of fluids flowing through channels and chambers is a crucial step in chemical and biochemical reactions inside microfluidic devices due to laminar flow because of small size channel and chamber dimensions. Mixing can be enhanced by passive or active mechanism which makes convection dominant over diffusion. To address this challenge, the study proposes three novel mixing designs: passive mixer, active mixer and a combination of active and passive mixing. These designs mixing performance has been studied by numerical simulation using COMSOL 5.3. According to the preliminary results of the study, pure active micromixer design has superior mixing ability. The mixing ability was proved by concentration line plots, concentration contours and videos. In order to further optimize the mixing index of the pure active micromixer, Taguchi method is applied against various input parametric values for micromixer such as frequency, voltage and velocity. The velocity is required for two fluids to flow, while frequency and voltages are for providing an external energy for active mixing. A total of nine cases were analyzed; the two best cases out of nine were selected for comparing mixing index line plots. The result of the study conclude that pure active micro-mixer at an optimal set of parameters, frequency of 10 Hz, velocity of 0.05 mm s–1 and voltage of 0.5 V achieved 99.6% mixing index at t = 0.2 s.

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“…In the past, the importance of micromixers was poorly understood, and only a few research groups focused on this area [11,12]. Recently, many new micromixer studies have been published [13][14][15][16][17]. Saygili et al produced microfluidic molds using the 3D printing method.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a Laminar Diffusion-Based Micromixer with Microfluidic Chip

Ülkir

Girit

Ertugrul

2021

Journal of Nanomaterials

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This study aims to perform optimizatione to achieve the best diffusion control between the channels by designing and analysing a microfluidic-based micromixer. The design and analysis of the micromixer were made with the COMSOL Multiphysics program. Some input and output parameters must be defined for diffusion control of the micromixer. Among these parameters, inputs are the diffusion coefficient and inlet flow rate, while outputs are velocity, pressure, and concentration. Each input parameter in the microfluidic chip affects the output of the system. To make the diffusion control in the most optimum way, the data were obtained by making much analysis. The data obtained from this program was also provided with the Fuzzy Logic method to optimize the microfluidic chip. The diffusion coefficient value (5E-11 m2/s) should be given to the channels to achieve the optimum diffusion between the micromixer channels, if the inlet flow rate value (15E-15 m3/s) is the output value of the system, the velocity is 0.09 mm/s. The pressure is 2 Pa, and the concentration is 0.45 mol/m3. These values are the optimum values obtained from the analysis without damaging the liquid’s microfluidic channels supplied to the micromixer’s inlet.

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Numerical Simulation for efficient mixing of Newtonian and non-Newtonian fluids in an electro-osmotic micro-mixer

Cited by 46 publications

References 25 publications

AC Electroosmosis Effect on Microfluidic Heterogeneous Immunoassay Efficiency

AC Electroosmosis Effect on Microfluidic Heterogeneous Immunoassay Efficiency

Optimal parametric mixing analysis of active and passive micromixers using Taguchi method

Design and Analysis of a Laminar Diffusion-Based Micromixer with Microfluidic Chip

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