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Volume 151, Issue 4, April 2013
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Sensors & Transducers Journal (ISSN 2306-8515) is a peer review international journal published monthly online by International Frequency Sensor Association (IFSA). Available in both: print and electronic (printable pdf) formats. Copyright © 2013 by International Frequency Sensor Association.
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Volume 151 Issue 4 April 2013
www.sensorsportal.com ISSN 1726-5479
Research Articles
10 Top Reasons to Publish your Article in Sensors & Transducers (Editorial) S. Y. Yurish ................................................................................................................................ I Fast Field Calibration of MEMS-based IMU for Quadrotor's Applications J. F. Zhang, J. P. Bai, J. B. Wu, Y. Zeng and X. S. Lai ............................................................. 1 Analysis of Pulse-Echo Response Based on Linear MEMS Ultrasonic Transducer Array Wang Hongliang, Wang Xiangjun, He Changde, Xue Chen Yang ............................................ 10 Performance Enhancement of Silicon MEMS Microspeaker Alexandre Houdouin, Iman Shahosseini, Hervé Bertin, Nourdin Yaakoubi, Elie Lefeuvre, Emile Martincic, Yves Auregan, Stéphane Durand.................................................................... 18 Fluid Structure Coupling Analysis of Boundary Layer Streaming Driving Micropump Changzhi Wei, Shoushui Wei, Feifei Liu.................................................................................... 24 Numerical Simulation of Mixing Process in Tortuous Microchannel Reza Hadjiaghaie Vafaie, Mahnaz Mahdipour, Hadi Mirzajani, Habib Badri Ghavifekr ........................ 30 A Molecular Imprinting TNT Sensitive Detection Sensor Based on Film Bulk Acoustic Resonator Qimeng Lv, Guangmin Wu, Jianming Chen, He Qun Chu, Mai John D. .................................. 36 Design and Simulation of a MEMS-based Large Traveling Linear Motor for Near Infrared Fourier Transform Spectrometer Ehsan Atashzaban, Mahdi Nasiri, Hadi Mirzajani, Hamed Demaghsi, Habib Badri Ghavifekr .................................................................................................................................... 41 A Large Stroke MEMS-based Linear Motor for Fourier Transform Spectrometer Applications Ehsan Atashzaban, Hadi Mirzajani, Mahdi Nasiri, Milad Sangsefidi ......................................... 47 Design and Experiment of a Parallel Six-axis Heavy Force Sensor Based on Stewart Structure Wei Liu, Qi Li, Zhenyuan Jia, Erdong Jiang............................................................................... 54 Development of System for Alumina Clinker Quality Real-time Monitoring based on Sound Sensor Qing Tian, En-Cheng Wang, Chang-Nian Zhang and Jin-Hong Li ............................................ 63 Characterization of Defects in Non-ferromagnetic Material Using an Electromagnetic Acoustic Transducer Sadiq Thomas, Evans Ashigwuike, Wamadeva Balachandran, Salah Obayya. ....................... 70
Photodiode Array for Detecting Laser Pointer Applied in Shooting Simulator Aryuanto Soetedjo, Eko Nurcahyo, Fiqih Prawida..................................................................... 78 Study on Sensing Properties and Mechanism of Pd-doped SnO2 Sensor for Hydrogen and Carbon Monoxide Qu Zhou, Weigen Chen, Lingna Xu, Shudi Peng ...................................................................... 84 Three-dimensional Node Localization Algorithm for Wireless Sensor Networks Zhang Ye, Zhang Feng. ............................................................................................................. 90 A New Time Synchronization Algorithm for Wireless Sensor Networks Based on Internet of Things Zhang Yong-Heng, Zhang Feng. ............................................................................................... 95 Wireless Sensor Traceability Algorithm Based on Internet of Things in the Area of Agriculture JI Yan, Zhang Feng, DONG Jian-Gang, You Fei ...................................................................... 101 Development of Noise Measurements. Part 2. Random Error Zenoviy Kolodiy, Bohdan Stadnyk, Svyatoslav Yatsyshyn. ....................................................... 107 An Optimised Electronic System for in-vivo Stability Evaluation of Prostheses in Total Hip and Knee Arthroplasty Shiying Hao and John Taylor ..................................................................................................... 113
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© 2013 by IFSAhttp://www.sensorsportal.com
Numerical Simulation of Mixing Process in Tortuous Microchannel
Reza Hadjiaghaie Vafaie, Mahnaz Mahdipour, Hadi Mirzajani,
Habib Badri Ghavifekr Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran,
E-mail: {R_Vafaie, M_Mahdipour, H_Mirzajani, Badri}@sut.ac.ir
Received: 25 October 2012 /Accepted: 18 April 2013 /Published: 30 April 2013 Abstract: Low Reynolds number flow is one of the main challenges in Lab-On-a-Chip’s components like micromixers. In such scale, we need to turn viscose effects into the dominate factors. This study proposes a MEMS-based electroosmotic micromixer, the idea is to perform the mixing operation in curvature of the conventional Lab-On-a-Chip microchannels. The results revealed a high performance mixer, with mixing efficiency of above 90 % for two mixing unit. The frequency response demonstrated the ability of the mixer to produce chaotic mixing associated with stretching, folding and breaking the fluid up, for the frequency range of 2-10 [Hz]. High voltages cause strong electric field gradient in the microchannel. The frequency effect is more significant than the effect of voltage amplitude. Copyright © 2013 IFSA. Keywords: Lab-On-a-Chip, MEMS-based, Low Reynolds number flow, Micromixer, Electroosmotic flow. 1. Introduction
Recently, advances in microfluidic devices have been employed in chemical and biological applications. Lab-On-a-Chip (LOC) devices integrate a number of microfluidic components, such as mixers, pumps, valves, separators, reactors and detectors in a single chip. These devices offer the ability to smaller fluid volumes, shorter analysis time, low cost and in the range of several to hundreds of micron. Micro-scale turns the viscous effects into the dominate factors [1, 2]. Micromixer is an important component of the microfluidic for chemical and biological analysis. Reducing the channel dimensions to the micron scale results in a laminar flow, characterized by low Reynolds number:
hdU
Re , (1)
where Re is the dimension less Reynolds number, U is the average flow velocity, dh is the hydraulic diameter of the channel and ν is the kinematic viscosity of the liquid [2, 3]. Due to small scale and lack of turbulent flow, molecular diffusion is the main transport phenomena in such scale. Micromixers can be classified into passive and active types. A passive mixer usually contains irregular channel geometry to perturb flow streamlines, such as zigzag shaped micromixer [4], enhance mixing process by obstacles [5] and so on. In contrast to the passive mixers, active mixer achieving a mixing effect by inducing external driving force to enhance the mixing effect, including acoustic vibration [6], thermal [7], magnetic [8] and electrokinetic [9, 10]. An effective mixing in low Reynolds number flow regimes can be obtained by the chaotic mechanism and generate s significant increase in the interfacial contact area. In the most literatures, chaotic regime is used to mix fluids in laminar flows, associated with stretching and
Article number P_1171
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31
folding. Electroosmotic force shows considerable promise for application in micropumps and micromixers. In order to mix small reagents and overcome the viscous resistance of fluid flow in microchannels, generating chaos regime can be so helpful. Electroosmotic force is the excellent solution and it is more efficient force in such scale. In this case, ionized liquid moves relative to the stationary charged surface by action of the applied electric field [11].
This paper investigates mixing operation in curvature of conventional Lab-On-a-Chip microchannels. For this purpose, firstly the design of the mixer will describe in section 2. The theory and boundary conditions of the electroosmotic micromixer are aimed to be described in section 3. Section 4 will perform a set of simulations to investigate the interaction between the primary stead flow and induced secondary electroosmotic flow, species concentration distribution, chaotic regime and the corresponding mixing efficiency. Also, the effect of excitation parameters (such as: voltage amplitude and frequency) will be investigated. 2. Design Consideration
In this study, the mixing channel is to be designed with a meander shape. Actually, we use a miniaturized tortuous two-dimensional microchannel. The value of geometrical parameters of the mixer were assigned in accordance with Table 1 and also shown in Fig. 1. It takes two fluid from inlets A and B, and combines them into a single microchannel. Electrosmotic force is induced by actuating the electrodes. As shown in Fig. 1, it assumes the pumping process occurs with AC electroosmotic pump in straight walls and the mixing process will occur by electroosmotic force.
Fig. 1. Schematic view of a meander shape microchannel.
Table 1. Geometrical parameters of a mixer unit.
Symbol Description Value (μm)
R1 Internal radius of a mixing unit
30
R2 External radius of a mixing unit
60
W Channel width 30 d Size of the electrodes 8
3. Theory and Boundary Conditions
The equations governing incompressible liquid flow are the Navier-Stokes equation (Equation 2) and continuity equation (Equation 3) [12], Including external electric field and electrical driving force terms. Electrical driving force represents interaction between electrical double layer (EDL) and excess ions [13].
Eupuut
ue
2
(2)
0u , (3) where is the fluid density, u
is the bulk
electroosmotic flow velocity ,)juiuu( yx
p is
the pressure in the microchannel, is the fluid
viscosity, e is the net electric charge density, and
E
is the local electric field strength can then be expressed as:
eE , (4)
where e is the electric potential. If a tangential
electric field is applied to an electrolyte solution, the charge in the electrical double layer (EDL) between the surface and the electrolyte, experience a significant force. Consequently, these double layer charges move, pulling the fluid along and generating a secondary flow. The effect of electroosmotic flow is considered as slip wall boundary condition for fluid motion equation. The electroosmotic velocity is well approximated by Helmholts-Smoluchowski equation (Equation 5), which is valid for thin double layer [11, 14]:
E
U r0eo , (5)
where 0 is the dielectric permittivity in a
vacuum, r is the relative dielectric permittivity of
the liquid, is the electrokinetic zeta potential,
is the fluid dynamic viscosity and E is the electric
field. The concentration field of solution in such an electroosmotic flow can be described by Convection-Diffusion equation:
CDC)uu(t
C 2epeo
, (6)
where C is the concentration of species (Fluid A and B are described by species concentration of 1 and 0 mol.m-3, respectively), D is the diffusion
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32
coefficient of the species, eou is the electroosmotic
velocity of the species, and epu is the
electrophoretic velocity of the species, which, the electrophoretic mobility of the species is negligible in comparison with the electroosmotic mobility [15]. Material properties of the solution and also boundary conditions are shown in Table 2 and Fig. 2, respectively. As shown in Fig. 2, the electrodes are located in the side walls and excited by time-
dependent voltages ( )()( 21 tandt ). The phase
difference among )(1 t and )(2 t is 180 degrees.
Fig. 2. A mixing unit boundary conditions; five microelectrodes are placed in the side walls
(the microelectrode’s size is d).
As discussed earlier, the current simulation model considers the laminar flow due to the small characteristic length scale. It mixes two species in to the microchannel. It assumes the variation in the fluid concentration does not alter the viscosity and density properties of two fluids [16]. The mean
velocity of the initial fluid is 0U (driven by AC
electroosmotic pump [17, 18]).
Table 2. Material properties of the mixing rocess.
Symbol Description Value D Diffusion coefficient 110-11 m2.s-1 µ Viscosity of fluid 110-3 N.s.m-2 ρ Density of fluid 103 kg.m-3 ζ ζ-potential -100 mV εr Dielectric constant 80.2 ε0 Vacuum permittivity 8.85410-12 F.m-1
U0 Mean input velocity 0.1 mm.s-1
V0 Amplitude of electric potential
500 mV
ƒ Frequency excitation 6 Hz
The pressures at the two ends of the microchannel were specified as zero: )OutletandInletat(.0P (7)
Also, the pressure gradient is set to be zero at the channel walls, considering no flux across the walls: )wallschannelat(.0Pn (8)
The electrodes in the side walls are modeled by placing the boundary conditions as shown in Fig. 2. Insulation conditions (Equation 9) were applied at other boundary conditions.
0y
(9)
The transverse electric field intensity is given by
Equation 4. The Laplace equation (Equation 10) can be used to solve the transverse electric potential subject to the boundary conditions shown in Fig. 2. 0ˆ e
2 (10)
The corresponding boundary conditions for the
slip velocity are:
.Eu
.Eu
yy
xx
wallschannelat (11)
and
.0y
u
.0x
u
y
x
OutletandInletat (12)
The electrodes are excited and generating different flow patterns. Resulting, mixing process is occurred by interaction between the primary steady flow and secondary oscillatory external electric field [19]. 4. Results and Discussion A set of simulations were performed to investigate the fluid velocity streamlines, species concentration distribution, mixing performance and the effect excitation parameters. Fluid velocity streamlines are shown in Fig. 3, for different times. Actually, the streamlines show the interaction between the initial steady velocity flow and the secondary time-dependent flow. The electroosmotically-driven flows are oscillating with the frequency of ƒ. In a result, we can see the eddy rotation by separating the streamlines near the electrodes. This actions cause to chaotic regime, associated with stretching, folding and breaking the fluid up, which significantly increases the interfacial area between the two solutions (solvent and solute) [11].
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33
Fig. 3. Fluid velocity streamlines at different times.
Fig. 4 illustrates the evolution of the species concentration distribution in the bended microchannel. It can be seen that the chaotic perturbation effects generated, due to the electroosmotic secondary flow.
Species concentration profiles are plotted for different times as a function of channel width in Fig. 5.
4.1. Mixing Efficiency
In order to evaluate mixing performance, the mixing efficiency Q at any cross-section of the microchannel can be quantified via the following equation [20].
%100]
dACC
dACC
1[Q
A0
A
(13)
where, C is the species concentration across the width of the channel, C is the species concentration in the perfectly mixed state (C=0.5), and C0 is species concentration in the completely unmixed condition (C0 = 0 or 1). Fig. 6 illustrates mixing efficiencies profile for two units of bended channels. 4.2. Excitation Parameters
As discussed earlier, when the electrodes are excited by electric potential, the recirculation phenomena is created periodically near the walls. These secondary flow leads to mix the low Reynolds number flow. The electroosmotic field intensity can be controlled by excitation parameters. Fig. 7 illustrates the excitation frequency and voltage amplitude effect on mixing efficiency. In frequency point of view, It is clear that, in the high frequencies
(above 10 [Hz]) the secondary electroosmotic flow has not sufficient time to dominate the initial steady flow. Also in very low frequencies (above 2 [Hz]) the secondary electroosmotic flow is very slow and initial steady flow is dominate. In voltage amplitude point of view, the large voltage amplitude causes a strong flow field [21].
Fig. 4. Distribution of species concentration in a mixing unit.
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Fig. 5. Concentration profile (C) versus channel width (W) for different times, as shown in figure legend.
Fig. 6. Mixing quality: (a) Distribution of species concentration for two mixing unit, (b) Mixing efficiency over the channel width at different time (shown in the figure legend).
Fig. 7. Frequency effect on mixing efficiency; this profile are plotted for two different voltages (0.35 and 0.5 V).
4. Conclusion
Using curvature microchannels, an electroosmotic actuated micromixer was designed and investigated numerically. The existence of chaotic behavior was demonstrated by generating strong perturbation effects which associated with stretching, folding and breaking actions. The simulation results showed a mixing efficiency as
high as 90 %, when a time-dependent electric field was applied. Some parameters of designed and presented micromixers are assigned in accordance with Table 3. The frequency and voltage variations showed that the mixer is of interest in low frequencies (between 2 and 10 [Hz]). It is obvious that, the high electric field gradient can damage cells or samples, so the frequency effect is more significant than the voltage effect.
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Table 3. Presented micromixers.
Reference Disturbance and
Type Channel
width Using chamber
Velocity [mm/s]
Frequency [Hz]
Mixing Efficiency
[2] Passive-parallel 85 [µm] Without chamber 0.7 - Not reported [3] Chaotic-patterned wall 200 [µm] Without chamber 0.01-0.09 - 90 %
[19] Electrokinetic 50 [µm] Rectangular hamber 100 µm ×100 µm
Not reported
Not reported 95 %
[21] AC-Electroosmotic 3D- Simulation
20 [µm] Without chamber 0.1 5 93 %
This paper Electroosmotic 30 [µm] Without chamber 0.1 6 94 % References [1]. H. A. Stone, A. D. Stroock, and A. Ajdari,
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