Difference between revisions of "Team:SUSTech Shenzhen/Model"

 
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= Overview =
 
= Overview =
  
When we were discovering audio-genetics, to find correspondences between our mechanosensitive(MS) channels and different sound wavelengths, we needed the support of modeling and logical result ascription besides constructing a huge mutagenesis library and testing them in vitro continuously, although it is already very hard to do. We designed the experiment based on the discovery of the mechanism of MS channel and applying it on the regulation of downstream gene expression. Modeling has been our guide throughout the project and we finally got the result we initially expected.
+
Modeling is usually used to make sense of the experimental discovery in traditional biological studies. In this synthetic biology project, we believe that carefully carried out modeling will be critical for the experiment design and data analysis at different stages of the project. We hope to demonstrate that the modeling is especially helpful to finalize the microfluidics chip design, and determine the absolute shear force in the experiments, as well as characterization and optimization of acoustic stimulation experiments.
  
In one part, we employed microfluidics to realize the stable force field controlled by fluidic velocity. In-vitro experiments were operated on the designed chips. On the other hand, we used various devices to generate sound field and tested cell response in different conditions.
+
Simplified fluidic mechanic theory is sufficient to guide the geometry design of shear force screening microfluidics chip. Together with direct experimental measurement of flow speed, numerical simulation of the flow in the microfluidics chip using Finite Element Analysis (FEA) enable us to derive actual shear force in the chip.
  
Finite Element Analysis (FEA) was applied to modeling of the field generated by the microfluidic devices and the acoustic stimulators. COMSOL Multiphysics® acted as both the modeling tool and the data analysis tool. Modeling reliability has been tested and confirmed by comparing the calculated result with raw results from the experiments.
+
On the other hand, the acoustic stimulation devices are very different from each other. Our empirical is not sufficient to help select and data analysis. We use Finite Element Analysis (FEA) to model the force field generated by the acoustic stimulators, with the help of acoustometer measurements.
  
= Force of Field =
+
= Force Field =
  
To quantitatively measure the response of MS channel on the cell membrane, we designed our experiment manipulated on microfluidic chip. CHO-K1 cells were cultured adherent on the bottom of PDMS tunnel. Stable and flexible force field could be formed surrounding cell, which directly controlled by the pumped-inflow rate. Each time when we applied a constant pumped inflow, cells in 3 different observation tunnel could receive corresponding small, middle, large, 3 level of force magnitude(1: 9: 81). By changing the pumped flow rate, we could measure MS channel response under a series of forces with different magnitude order.
+
To quantitatively measure the response of MS channel on the cell membrane, we designed our experiment manipulated on microfluidic chip. CHO-K1 cells were cultured adherent on the bottom of PDMS channels. Stable and flexible force field could be formed surrounding cell, which directly controlled by the pumped-inflow rate. Each time when we applied a constant pumped inflow, cells in 3 different observation channels could receive corresponding small, middle, large, 3 level of force magnitude(1: 9: 81). By changing the pumped flow rate, we could measure MS channel response under a series of forces with different magnitude order.
  
{{SUSTech_Image_Center | filename=T--SUSTech_Shenzhen--rendered-device.png|width=800px|caption=}}
+
{{SUSTech_Image_Center_8 | filename=T--SUSTech_Shenzhen--refvrgbegf.png|width=800px|caption=<B>Fig. 1 Microfluidic Channels</B>}}
  
== Mathematical Demonstration ==
+
== Mathematical Analysis ==
  
In experiment, when fluid(culture medium x flowed through the tunnel, the shear force was applied on the wall. Seeing the culture medium as a Newtonian flow, it has a constant viscosity μ,0.012dyn·s/cm<sup>2</sup><ref>Booth, R., &amp; Kim, H. (2012). Characterization of a microfluidic in vitro model of the blood-brain barrier (μBBB). Lab on a Chip, 12(10), 1784-1792.</ref>. The shear stress that medium generated on the wall is proportional to strain rate. As a result, we could relate the magnitude of stress to the velocity gradient along the transversal surface of each tunnel.
+
During experiment, when fluid(culture media x flowed through the channels, the shear force was applied on a thin layer close to wall. The culture media can be treated as a Newtonian flow with a constant viscosity μ,0.012dyn·s/cm<sup>2</sup><ref>Booth, R., &amp; Kim, H. (2012). Characterization of a microfluidic in vitro model of the blood-brain barrier (μBBB). Lab on a Chip, 12(10), 1784-1792.</ref>. The shear stress that medium generated on the wall is proportional to strain rate. As a result, we could relate the magnitude of stress to the velocity gradient along the transversal surface of each channel.
  
Due to the extremely small scale of microfluidic tunnel (only 0.285mm of width), fluid in it observes the Laminar flow. We could assume there is no turbulence when inflow applied constantly, even at the corners, and the head loss of the pumped inflow could also be ignored. The modeling of flow between 2 parallel plates applies to such stable state, in which the magnitude of shear stress on the bottom is proportional to the maximum velocity( at the longitudinal central line).
+
Due to the extremely small scale of microfluidic channel (only 0.285mm of width and 0.090mm of height), fluid in it exists as the Laminar flow. Turbulent flow is not possible with the physiology range of flow speed, even at the corners.  The head loss of the pumped inflow is also negligible in our experiment. The modeling of flow between 2 parallel plates applies to such stable state, in which the magnitude of shear stress on the bottom is proportional to the maximum velocity ( shown as the longitudinal central line in Fig. 2).
  
As the shear stress is proved proportional to the flow rate in the tunnel, we designed the chip to achieve that each of 3 tunnels in observation area has the same transversal surface but the gradient (81: 9: 1 from up to bottom) flow rate, also the average speed.<br />
+
As the shear stress is proved proportional to the flow rate in the channels, we designed the chip to achieve that each of 3 channels in observation area has the same transversal surface but the gradient (81: 9: 1 from up to bottom) flow rate, also the average speed, as shown in Fig. 3.
The lengths of straight tunnels between AB and AC (L<sub>AB</sub>, L<sub>AC</sub>)are 14.3mm and 12.0mm, and the curved tunnels between AB and BC(R<sub>AB</sub>, R<sub>BC</sub>) are 108.0 mm and 105.0mm.
+
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--35011F22BF6BCC10C3DF1F593E43DCF1.jpg|caption=}}
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--35011F22BF6BCC10C3DF1F593E43DCF1.jpg|caption=<B>Fig. 2 Speed distribution inside channels</B>}}
 
Newtonian fluid flows between two wide, parallel plates Flow driven by pressure difference Parabolic velocity profile given by
 
Newtonian fluid flows between two wide, parallel plates Flow driven by pressure difference Parabolic velocity profile given by
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>u = V[1-(y/h)^2]</nowiki>}}
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>u = V[1-(y/h)^2]</nowiki>}}
 
where {{SUSTech_Shenzhen/math|equ=<nowiki>V</nowiki>}} is the maximum velocity (along channel centerline {{SUSTech_Shenzhen/math|equ=<nowiki>y=0</nowiki>}}) Along bottom wall, {{SUSTech_Shenzhen/math|equ=<nowiki>y=-h</nowiki>}}, shear stress
 
where {{SUSTech_Shenzhen/math|equ=<nowiki>V</nowiki>}} is the maximum velocity (along channel centerline {{SUSTech_Shenzhen/math|equ=<nowiki>y=0</nowiki>}}) Along bottom wall, {{SUSTech_Shenzhen/math|equ=<nowiki>y=-h</nowiki>}}, shear stress
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\tau=\mu \frac{du}{dy}=\mu(-2V\frac{y}{h^2})=\frac{2\mu V}{h}</nowiki>}}
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\tau=\mu \frac{du}{dy}=\mu(-2V\frac{y}{h^2})=\frac{2\mu V}{h}</nowiki>}}
For a constant flow rate within the tunnel, the average speed remains same
+
For a constant flow rate within the channels, the average speed remains same
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\bar V=\frac{Q}{A}=\frac{\int_A udA}{A}=\frac{1}{2}V</nowiki>}}
 
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\bar V=\frac{Q}{A}=\frac{\int_A udA}{A}=\frac{1}{2}V</nowiki>}}
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--annotated-device.png|width=800px|caption=}}
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--annotated-device.png|width=800px|caption=<B>Fig. 3 The geometry of the microfluidic channels.</B> The lengths of straight channels between AB and AC (L<sub>AB</sub>, L<sub>AC</sub>) are 14.3mm and 12.0mm, and the curved channels between AB and BC(R<sub>AB</sub>, R<sub>BC</sub>) are 108.0 mm and 105.0mm.}}
  
Based on the integral form of the continuity equation for an incompressible fluid, during a given time, the sum of flow volume in each branch is equal to the total volume pumped in the whole chamber. According to the Kirchhoff's law, the accumulation of flow speed at the joint point must be zero. It is easy to get the equation that{{SUSTech_Shenzhen/bmath|equ=<nowiki>\begin{matrix} L_{AC}V_1=L_{AB}V_2+R_{AB} V_3 \\
+
Based on the integral form of the continuity equation for an incompressible fluid, at any given time, the sum of flow volume in each branch is equal to the total volume pumped in the whole chamber. According to the Kirchhoff's law, the accumulation of flow speed at the joint point must be zero. It is easy to get the equation that{{SUSTech_Shenzhen/bmath|equ=<nowiki>\begin{matrix} L_{AC}V_1=L_{AB}V_2+R_{AB} V_3 \\
 
V_2:V_3=R_{AB}:L_{AB}
 
V_2:V_3=R_{AB}:L_{AB}
 
\end{matrix}</nowiki>}}
 
\end{matrix}</nowiki>}}
Consequently, we could reach the conclusion that the maximum velocity, average flow rate and the shear force on the bottom of each tunnel is at a ratio of 81:9:1. To confirm the modeling result, we made calibration in real microfluidics chip, and the testing result is very close to designing value (about 80:10:1) (See the [[Team:SUSTech_Shenzhen/Measurement|Measurement]] page)
 
  
== Experimental result Analysis ==
+
Consequently, we could reach the conclusion that the maximum velocity, average flow rate and the shear force on the bottom of each channel is at a ratio of 81 : 9 : 1. To verify the modeling result, we made calibration in the real microfluidics chip, and the testing result is very close to designing value (about 75 : 8 : 1 of the maximum velocity ratio in each channel) and the simulation result (80 : 8 : 1).
  
On October 12th, we testify one of our MS channels, Piezo1, under the simulation of shear stress, with R-GECO fluorescent indicating its activation level. (results shown below)
+
== Experimental Result Analysis ==
  
== Simulation ==
+
In the whole experiment, we tested one mechanosensitive channel, Piezo1, with different magnitude orders of shear stress.
  
To make the analysis of experimental result is convincible, we also made the simulation using COMSOL Multiphysics® to define that the field in microfluidic channel confirmed to our expectation.
+
Comparing the fluorescence intensity amplitudes corresponded to the shear stress ranged from 0 Pa to 5 Pa, we found a best response at around 0.01-0.1 Pa. No response was observed when the shear stress is larger than 2 Pa.  
  
COMSOL Multiphysics® is a general-purpose software platform, based on finite element analysis, for modeling and simulating physics-based problems. It divides a large problem into smaller elements, these smaller elements will be solved separately and then be assembled backed to the original model. A collection of smaller elements is called a “mesh”, the “mesh” is constructed by numerous elements, the smaller the size of the element is, the finer the “mesh” is, and the more accurate will the result be.
+
{{SUSTech_Image_Center_8 | filename=T--SUSTech_Shenzhen--AD0520F4BABB8B3DC7ECF6A15CBF1652.jpg |width=1000px|caption=Fig.  Comparison between the R-GECO cell response(a) and Piezo1+R-GECO cell response(b) to the 15kHz Buzzer’ s simulation.}}
  
We made the simulation with the following procedures, and the result of maximum velocity and shear force applied on the bottom wall match with the mathematics perfectly.
+
{{SUSTech_Image_Center_8 | filename=T--SUSTech_Shenzhen--20160907,R-GECO+Piezo1,sound,20K.png |width=1000px|caption=<B>Fig. 5 Fluorescence change of R-GECO+Piezo1 cell when stimulate by 20kHz sound emitted by a buzzer.  Sound was started from 5s to 15s. 5 cells were selected and their fluorescence intensity changed as shown in the figure. </B>}}
  
=== a. Geometry ===
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<html><a href="/Team:SUSTech_Shenzhen/Model/Result" class="btn btn-default"><i class="ion-arrow-right-c"></i> Discussion Details</a></html>
  
First we imported the designed pattern file created by Solidworks®.
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== Calibration ==
  
Then we draw two circles which have the diameter equal to the inner diameter of the fluid pipes that we used (0.65mm). The circles were placed around the center of the two circles we reserved for the fluid pipes. Since we used our bear hands to control the position of the holes for the fluid pipes in chip fabrication, the circles were just placed around the center parts like real cases.
+
Rainbow beads (SPHEROTM Rainbow Calibration Particles, diameter: 6um) were dissolved in the cell culture medium. A series of pumped flow rate (5ul/min, 15ul/min, and 45ul/min) were applied to generate a steady fluid flow. The exposure time was set to 100ms (one representative image is shown in Fig. 6).
  
Then we extruded the pattern to 90μm, and deleted the undesired parts. The final geometry was shown below.
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--DB56D45F-D056-4A82-897A-2CE77C2C4A12.png | caption=<B>Fig. 6 Bead trace in the fastest microfluidics channel with The Flow Rate of 5ul/min</B> | width=1000px}}
  
=== b.Parameters ===
+
By using our customerized MATLAB program, the ratio of maximum flow velocities were calculated as 13 : 100 : 978. The absolute speed with pump speed of 45 um/min is shown in Fig. 7.
  
All geometry domains were applied with the build-in material "water" to represent the petro medium that we used in our experiment.
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--855C7E02-2E51-441A-9492-A2B281185010.png | caption=<B>Fig. 7 Maximum Velocities in Each Channel with The Flow Rate of 45ul/min</B> | width=1000px}}
  
The material parameters can be seen from bellow.
+
<html><a href="/Team:SUSTech_Shenzhen/Model/Calibration" class="btn btn-default"><i class="ion-arrow-right-c"></i> Code &amp; Details</a></html>
 +
 
 +
== Simulation ==
 +
 
 +
To further validate our design, we also performed the simulation using the Finite Element Method (FEM) to confirm that the field in microfluidic channel satisfies our expectation. FEM is a method for modeling and simulating physics-based problems. It divides a large problem into smaller elements, these smaller elements will be solved separately and then be assembled backed to the original model. A collection of smaller elements is called a “mesh”, the “mesh” is constructed by numerous elements, the smaller the size of the element is, the finer the “mesh” is, and the more accurate will the result be. The final geometry set up can be seen from below (Fig. 8).
 +
 
 +
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--geometrydscvdfscvsd.jpg|caption=<B>Fig. 8 Final geometry setup</B> | width=1000px}}
 +
 
 +
Under different pumped inflow rate(5μL/min, 15μL/min and 45μL/min), the velocity magnitude distribution was calculated. The result of maximum velocity and shear force applied on the bottom wall matched with the mathematics perfectly(around 80: 10: 1 in all the conditions, shown in the table below).
  
 
{|class="table table-striped"
 
{|class="table table-striped"
| '''Description'''
+
|
| '''Value'''
+
Channel
 +
 
 +
Flow Rate
 +
| fast
 +
| middle
 +
| slow
 
|-
 
|-
| Dynamic viscosity
+
| 5μL/min
| eta(T[1/K])[Pa*s]
+
| 5414μm/s
 +
| 549μm/s
 +
| 68μm/s
 
|-
 
|-
| Ratio of specific heats
+
| 15μL/min
| 1.0
+
| 16242μm/s
 +
| 1646μm/s
 +
| 204μm/s
 
|-
 
|-
| Electrical conductivity
+
| 45μL/min
| {{5.5e-6[S/m], 0, 0}, {0, 5.5e-6[S/m], 0}, {0, 0, 5.5e-6[S/m]}}
+
| 48724μm/s
|-
+
| 4938μm/s
| Heat capacity at constant pressure
+
| 612μm/s
| Cp(T[1/K])[J/(kg*K)]
+
|-
+
| Density
+
| rho(T[1/K])[kg/m^3]
+
|-
+
| Thermal conductivity
+
| {{k(T[1/K])[W/(m*K)], 0, 0}, {0, k(T[1/K])[W/(m*K)], 0}, {0, 0, k(T[1/K])[W/(m*K)]}}
+
|-
+
| Speed of sound
+
| cs(T[1/K])[m/s]
+
 
|}
 
|}
  
'''Table 1 Material Properties of "water"'''
+
'''Table 1 Simulation results of central line speed of each channel'''
  
The parameters that we actually used was the dynamic viscosity (eta), and the density (rho). Their values with respect to the change of the temperature (K) can be seen form below.
+
Results of mathematical demonstration (1: 9: 81), calibration (13: 100: 978) and simulation (1: 10: 80) are consistent with each other. This shows that the model is feasible for estimating the shear force that generated by microfluidics on cell membrane. In order to obtain the exact shear force, we inputted the experimentally used flow rate as a boundary condition (6.25μL/min,50μL/min) in our model. The shear stress was also calculated.
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--plot-eta.png|caption=Fig. 1 Plot of eta(T)}}
+
{|class="table table-striped"
 +
|
 +
Channel
  
eta(T)=1.3799566804-0.021224019151*T^1+1.3604562827E-4*T^2-4.6454090319E-7*T^3+8.9042735735E-10*T^4-9.0790692686E-13*T^5+3.8457331488E-16*T^6 (273.15K≤T≤413.15K)
+
Flow Rate
 
+
| fast
eta(T)= 0.00401235783-2.10746715E-5*T^1+3.85772275E-8*T^2-2.39730284E-11*T^3 (413.15 K≤T≤553.75K)
+
| middle
 
+
| slow
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--plot-rho.png|caption=Fig. 2 Plot of rho(T)}}
+
 
+
rho(T)=838.466135+1.40050603*T^1-0.0030112376*T^2+3.71822313E-7*T^3 (273.15K≤T≤553.75K)
+
 
+
Since the temperature of our model is set to the reference temperature as 293.15K, the respect value of eta(T) and rho(T) are 0.00101 Pa*s and 999.61509 kg/m³.
+
 
+
We used incompressible laminar flow interface to simulate our experiment, and the equations that the interface used is shown below.
+
 
+
(EQUATION)
+
 
+
All boundaries except the inlet and the outlet circles were set to be no slipping walls.
+
 
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--plot-boundaries.png|caption=Fig. 3 Boundaries Considered as "No Slipping Walls"}}
+
 
+
The inlet circle was given the velocity of 2.5113E-4 m/s, 7.534E-4 m/s and 0.0022602 m/s, which will give us the rate of flow values of 5μL/min, 15μL/min and 45μL/min.
+
 
+
The outlet circle was given the pressure of 0.
+
 
+
=== c. Mesh ===
+
 
+
We choose “fine” mash to simulate our model. The specifics of the mash are shown below.
+
 
+
{|class="table table-striped"
+
| '''Description'''
+
| '''Value'''
+
 
|-
 
|-
| Minimum element quality
+
| 6.25μL/min
| 9.185E-4
+
| 0.269Pa
 +
| 0.027Pa
 +
| 0.003Pa
 
|-
 
|-
| Average element quality
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| 50μL/min
| 0.4356
+
| 2.15Pa
|-
+
| 0.22Pa
| Tetrahedral elements
+
| 0.03Pa
| 503702
+
|-
+
| Pyramid elements
+
| 260
+
|-
+
| Prism elements
+
| 363692
+
|-
+
| Triangular elements
+
| 182924
+
|-
+
| Quadrilateral elements
+
| 160
+
|-
+
| Edge elements
+
| 19326
+
|-
+
| Vertex elements
+
| 524
+
 
|}
 
|}
  
'''Table 2 Mash Specifics'''
+
'''Table 2 Simulation results of central line shear stress'''
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--mesh-large.png|caption=Fig. 4 Mash Generated}}
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--sheardsgvfdv.png|caption=<B>Fig.9 Shear stress distribution under input flow rate 50μL/min (log scale)</B> | width=1000px}}
  
By choosing this mash size, the mash generated was fine enough to give six solution points with in the width of a single channel.
+
<html><a href="/Team:SUSTech_Shenzhen/Model/Simulation_Force_Field" class="btn btn-default"><i class="ion-arrow-right-c"></i> Detailed Protocol</a></html>
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--mesh-detail.png|caption=Fig. 5 Mash details}}
+
= Acoustic Field =
  
=== d. Solver Configuration ===
+
Sonic and ultrasonic waves could generate a pressure field to the cells adhering to the bottom of the cell dish. In our study of the sensitivity of mechanosensitive (MS) channel, we really found a most efficient sound frequency using buzzer and 108kHz ultrasonic transducer.
  
The solver was configured to compute for the stationary values under this specific model configuration. The relative tolerance was set to 0.000001, which means that the solver will only stop computing if the deviation of the result from the actual solution to the equations is under one in a million of the value of the actual solution.
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--POCStrwgtvbwr.jpg | width=400px|caption=<B>Fig. 10 B</B>}}{{SUSTech_Image | filename=T--SUSTech_Shenzhen--POCSrtheteyh.jpg | width=400px|caption=<B>Fig. 10 A</B>}}
  
=== e.Results ===
+
'''Fig. 10 (A) R-GECO+Piezo1 cell fluorescence intensity increased greatly when stimulated by 15K and 20KHz sound. While no obvious fluorescence intensity changed when GECO cells (without MS channel) were stimulated (B).'''
  
In the microfluidic channels the fluid will be applied a dragging force from the channel walls. So the fluid in the center line of the channel flows with the fastest speed.
+
However, to quantitively define the relationship of channel opening ( considering the influence of energy or force difference), it was important to know the pressure field distribution on the cell layer under certain conditions. Mathematical analysis and finite element analysis (FEA) were used to define the modeling.
  
In order to show the speed distribution inside the microfluidic channels, speed diagrams of the cut plane in the middle of the bottom plane and the top plane is shown below.
 
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--velocity-mag-distribution-5uL.png|caption=Fig. Velocity magnitude Distribution Under Input Flow Rate 5μL/min (log scale)}}
+
== Audible Frequency Result Analysis ==
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--velocity-mag-15uL.png|caption=Fig. Velocity magnitude Distribution Under Input Flow Rate 15μL/min (log scale)}}
+
To discover the response of MS channels to audible vibration, buzzers, balanced amatures and speakers were tried as sonic stimulators applied to the cells with R-GECO and Piezo1 channel, but only buzzers induced obvious cell response significantly in high frequency conditions (15kHz and 20kHz) when they are attached to the bottom of a cell dish each time.
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--veclocity-mag-45uL.png|caption=Fig. Velocity magnitude Distribution Under Input Flow Rate 45μL/min (log scale)}}
+
To explain that, a modal analysis method could be used when a buzzer was attached to the bottom of a cell dish, the shear stress induced by the asynchronism between cell culture medium and cell dish buzzer-forced oscillation is the driving factor of the channel response. It is interesting that the shear force magnitude in this condition is similar to the force magnitude in microfluidics channels.
  
In order to further show the speed difference under three different parameters, we draw a line on the cut plane from (-16, -4) to (-16, -6.45) crossing through three microfluidic channels in the observation zone. and plot the flow speed on that line.
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--buzzer-system-photo.png|caption=Fig. 12 Buzzer attached on the bottom of cell dish| width=400px}}{{SUSTech_Image | filename=T--SUSTech_Shenzhen--buzzer-system-model.png|caption=Fig. 11 Design pattern of the buzzer| width=400px}}
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--cut-lines.png|caption=Fig. Cut Line Drawn}}
+

Considering that the cell culture medium is a viscous and incompressible fluid with μ= 0.012dyn·s/cm2(0.0012Pa·s), it can not vibrate uniformly with the buzzer. The shear stress due to the differential distribution of fluidic velocity surrounding cell can apply a strain {{SUSTech_Shenzhen/math|equ=<nowiki>\gamma</nowiki>}} on the cell membrane.
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--velocity-mag-cutline.png|caption=Fig. Velocity Magnitude Distribution on The Cut Line}}
+
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\dot \gamma=\lim_{\delta t \rightarrow 0}\frac{\delta \theta}{\delta t}=\frac{\partial \theta}{\partial t}=\frac{\partial u}{\partial v}</nowiki>}}
  
The speed at the central line in all three channels at three different flow rate is listed below.
+
For sound waves,
 +
{{SUSTech_Shenzhen/math|equ=<nowiki>I \propto p_0^2</nowiki>}}, p<sub>0</sub> is the acoustic pressure and
 +
{{SUSTech_Shenzhen/math|equ=<nowiki>I \propto s_0^2</nowiki>}}, s<sub>0</sub> is the displacement amplitude.
  
{|class="table table-striped"
+
Thus we have
|
+
{{SUSTech_Shenzhen/bmath|equ=<nowiki>I = \frac{p_0^2}{2\rho v},\Delta p_m=(v\rho \omega)s_m</nowiki>}}, which indicates that the intensity of sound waves follow an inverse square law.
Channel
+
  
Flow Rate
+
Shear stress in the fluid is given by
| fast
+
{{SUSTech_Shenzhen/bmath|equ=<nowiki>\tau = \mu \frac{du}{dy},u=s_m\cdot f</nowiki>}}
| middle
+
| slow
+
|-
+
| 5μL/min
+
| 5413.994μm/s
+
| 548.52153μm/s
+
| 67.9229μm/s
+
|-
+
| 15μL/min
+
| 16241.73779μm/s
+
| 1645.63652μm/s
+
| 203.79536μm/s
+
|-
+
| 45μL/min
+
| 48723.94763μm/s
+
| 4937.93255μm/s
+
| 611.65866μm/s
+
|}
+
  
'''Table 3 Simulation Results of Central Line Speed'''
+
To define the amplitude of dish vibration, we measured the sound intensity by using Brüel & Kjær 1/8-Inch Pressure Field Microphone with Type 2669 Preamplifier (4138-C-006), which is calibrated from 6 Hz to 140 kHz.<ref>Brüel & Kjær TEDS System Product Data, Retrieved from https://www.bksv.com/~/media/literature/Product%20Data/bp2225.ashx</ref>
 Sound speed in the air v=340 m/s, air density is 1.29 kg/m<sup>3
</sup>, angular velocity is 2π*15000Hz forced by the buzzer.
  
=== g. Discussion ===
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--illustration-acoustic-measurement.png|caption=Fig. 13 Measure the sound intensity by acoustometer}}
  
In this simulation, we consider all the channel walls are rigid, but in real cases, channel walls will deform when pressure applied. So the cross section area of the channel will be larger than what we have considered in this simulation.
+
Acoustic pressure {{SUSTech_Shenzhen/math|equ=<nowiki>\Delta p_m = 4\text{Pa}</nowiki>}} is applied by the buzzer attached on the bottom of dish. 
From the formula above, the amplitude of dish vibration is around 9.68*10-7m. The shear stress applied on the dish bottom could also be calculated and the result is 0.01 Pa, which matches accurately to the shear stress generated in the microfluidic channel when the flow rate is 50μL/min in the slow channel.
  
In real cases, the microfluidic channels have a lot of defects at the edges of the channels. So the dragging force applied by these channels will be larger than what we have considered in this simulation, causing the fluid to have a lower speed. But due to the random distribution of the defects, at some points, the defects might accelerate the fluid flow by making the channel to be narrower than usual.
+
== Ultrasound Experiment Analysis ==
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--topside-channel-5x.png|caption=}}
 
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--topside-su8-20x.png|caption=Fig. Topside View of Microfluidic Channels 5X(up) and 20X(bottom)}}
 
  
In this simulation, microfluidic channel width was set to 285μm as we designed, with channel walls exactly perpendicular to the bottom. While as in real cases, due to the low transmittance of SU-8 photoresist to the low-wavelength light, the photoresist at the top side of the channel will absorb higher energy than the photoresist at the bottom, causing a trapezoidal cross section profile. The flow speed change caused by this phenomenon is still unknown to us.
+
First of all, a function was studied to give pressure on the surface of the ultrasonic transducer-water interface knowing the input voltage. Based on the interface pressure and physical properties of device, we constructed FEA models to simulate the ultrasonic radiant pressure field of the cell layer. Pressure field was studied in conditions of diverse power and distance between transducer interface and cell layer.
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--transmittance-su8.png|caption=Fig. Optical Transmittance of SU-8 Photoresist}}
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--GECO-PIEZO-Ultrasound.png|caption=Fig. 14 R-GECO+Piezo1 cells with DOX added in culture medium were stimulated by 108kHz ultrasound from 10s to 30s. Four regions were selected. Two R-GECO+Piezo1 cell region were chosen one from the right side of the video and another from left side. Two backgrounds were chosen the same way. | width=1000px}}
  
In order to obtain the exact shear force applied to the cells by the fluid flow. We input the experimentally used flow rate as a boundary condition in our model, which have already been tested before, to calculate the shear stress on the bottom of the channel where the cells can adhere to.
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--equivalent-schematic-emitter.png|caption=Fig. 15 Equivalent Schematics of the Transducer}}
  
The inlet circle was given the velocity of 0.0012557 m/s, 0.0025113 m/s and 0.0050226 m/s, which will give us the rate of flow values of 25μL/min, 50μL/min and 100μL/min. And the outlet circle was given the pressure of 0.
+
The equivalent circuit of ultrasonic transducer was used to calculate the ultrasonic radiant power of an ultrasonic transducer. We assume the ultrasonic energy was evenly distributed on the transducer interface<ref>A Zhen-Xiao, Simulation and Visualization of the Radiated acoustic Field of Ultrasonic Transducer. Nondestructive examination (NDE), 33(5),2-6</ref>, that is:
  
shear force of the shear stress on the bottom plane is shown below.
+
{{SUSTech_Shenzhen/math|equ=<nowiki>I\left( x,y,z = 0 \right) = \left\{ \begin{matrix}
 +
I_{0},x^{2} + y^{2} \leq R^{2} \\
 +
0,x^{2} + y^{2} \lt R^{2}
 +
\end{matrix} \right.\ </nowiki>}}
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--shear-stress-25uL.png|caption=Fig. 1 shear Stress Distribution Under Input Flow Rate 25μL/min (log scale)}}
+
Where I<sub>0</sub> is the absolute ultrasound intensity, R is the radio of transducer interface
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--shear-stress-50uL.png|caption=Fig. 2 shear Stress Distribution Under Input Flow Rate 50μL/min (log scale)}}
+
According to power intensity and pressure relation:
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--shear-stress-100uL.png|caption=Fig. 3 shear Stress Distribution Under Input Flow Rate 100μL/min (log scale)}}
+
{{SUSTech_Shenzhen/bmath|equ=<nowiki>I_{0} = \frac{{P_{0}}^{2}}{2c\rho}</nowiki>}}
  
In order to further show the shear stress difference under different parameters, we draw a line on the bottom plane from (-16, -4) to (-16, -6.45) crossing through three microfluidic channels in the observation zone. and plot the shear stress on that line.
+
In which {{SUSTech_Shenzhen/math|equ=<nowiki>P_0 , c, \rho</nowiki>}} are respectively absolute pressure, acoustic velocity and water density. We managed to calculate the pressure on the transducer-culture medium interface.
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--shear-profile.png|caption=Fig. 4 Shear Stress Profile}}
+
Then, we implemented FEM to do a series of simulations to find the absolute pressure filed distribution in different conditions. 108kHz and 1.1MHz transducer device were modeled as is shown in Fig. 16
  
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--shear-stress-profile.png|caption=Fig. 5 shear Stress Distribution on The Cut Line}}
+
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--11_1_2D_Nt.png |width=400px|caption=<B>Fig. 16 B</B>}}{{SUSTech_Image | filename=T--SUSTech_Shenzhen--108_1_2D_Nt.png |width=400px|caption=<B>Fig. 16 A</B>}}
 +
{{SUSTech_Image | filename=T--SUSTech_Shenzhen--11_1_3D_Nt.png |width=400px|caption=<B>Fig. 16 D</B>}}{{SUSTech_Image | filename=T--SUSTech_Shenzhen--108_1_3D_Nt.png |width=400px|caption=<B>Fig. 16 C</B>}}
  
The speed at the central line in all three channels at three different flow rate is listed below.
+
'''Fig. 16 (A) Pressure distribution of 108KHz ultrasonic transducer, the transducer was 1.0mm far above the cell layer. (B) Pressure distribution of 1.1MHz ultrasonic transducer. 3D pressure distribution for 108KHz condition (C) and 1.1MHz condition (D).'''
  
{|class="table table-striped"
+
The influence of distance error on pressure distribution pattern was also studied, which indicated that the 108kHz transducer was very robust to distance error, while the 1.1MHz acted as a chaos when little distance error occurs.
|
+
Channel
+
 
+
Flow Rate
+
| fast
+
| middle
+
| slow
+
|-
+
| 25μL/min
+
| 1.07519Pa
+
| 0.10819Pa
+
| 0.0132Pa
+
|-
+
| 50μL/min
+
| 2.15057Pa
+
| 0.21642Pa
+
| 0.02641Pa
+
|-
+
| 100μL/min
+
| 4.30273Pa
+
| 0.43314Pa
+
| 0.05288Pa
+
|}
+
  
'''Table 1 Simulation Results of Central Line shear Stress'''
+
In all, the 108kHz ultrasonic transducer was recommended as ultrasonic stimulator for quantitative measure cell response based on modeling and experimental results.
  
'''Audio-genetics'''
+
<html><a href="/Team:SUSTech_Shenzhen/Model/Sound" class="btn btn-default"><i class="ion-arrow-right-c"></i> Details</a></html>
  
 
= References =
 
= References =

Latest revision as of 03:02, 20 October 2016

Team SUSTC-Shenzhen

Model

Overview

Modeling is usually used to make sense of the experimental discovery in traditional biological studies. In this synthetic biology project, we believe that carefully carried out modeling will be critical for the experiment design and data analysis at different stages of the project. We hope to demonstrate that the modeling is especially helpful to finalize the microfluidics chip design, and determine the absolute shear force in the experiments, as well as characterization and optimization of acoustic stimulation experiments.

Simplified fluidic mechanic theory is sufficient to guide the geometry design of shear force screening microfluidics chip. Together with direct experimental measurement of flow speed, numerical simulation of the flow in the microfluidics chip using Finite Element Analysis (FEA) enable us to derive actual shear force in the chip.

On the other hand, the acoustic stimulation devices are very different from each other. Our empirical is not sufficient to help select and data analysis. We use Finite Element Analysis (FEA) to model the force field generated by the acoustic stimulators, with the help of acoustometer measurements.

Force Field

To quantitatively measure the response of MS channel on the cell membrane, we designed our experiment manipulated on microfluidic chip. CHO-K1 cells were cultured adherent on the bottom of PDMS channels. Stable and flexible force field could be formed surrounding cell, which directly controlled by the pumped-inflow rate. Each time when we applied a constant pumped inflow, cells in 3 different observation channels could receive corresponding small, middle, large, 3 level of force magnitude(1: 9: 81). By changing the pumped flow rate, we could measure MS channel response under a series of forces with different magnitude order.

T--SUSTech Shenzhen--refvrgbegf.png
Fig. 1 Microfluidic Channels

Mathematical Analysis

During experiment, when fluid(culture media x flowed through the channels, the shear force was applied on a thin layer close to wall. The culture media can be treated as a Newtonian flow with a constant viscosity μ,0.012dyn·s/cm2[1]. The shear stress that medium generated on the wall is proportional to strain rate. As a result, we could relate the magnitude of stress to the velocity gradient along the transversal surface of each channel.

Due to the extremely small scale of microfluidic channel (only 0.285mm of width and 0.090mm of height), fluid in it exists as the Laminar flow. Turbulent flow is not possible with the physiology range of flow speed, even at the corners. The head loss of the pumped inflow is also negligible in our experiment. The modeling of flow between 2 parallel plates applies to such stable state, in which the magnitude of shear stress on the bottom is proportional to the maximum velocity ( shown as the longitudinal central line in Fig. 2).

As the shear stress is proved proportional to the flow rate in the channels, we designed the chip to achieve that each of 3 channels in observation area has the same transversal surface but the gradient (81: 9: 1 from up to bottom) flow rate, also the average speed, as shown in Fig. 3.

T--SUSTech Shenzhen--35011F22BF6BCC10C3DF1F593E43DCF1.jpg
Fig. 2 Speed distribution inside channels
Newtonian fluid flows between two wide, parallel plates Flow driven by pressure difference Parabolic velocity profile given by u = V[1-(y/h)^2] where V is the maximum velocity (along channel centerline y=0) Along bottom wall, y=-h, shear stress \tau=\mu \frac{du}{dy}=\mu(-2V\frac{y}{h^2})=\frac{2\mu V}{h} For a constant flow rate within the channels, the average speed remains same \bar V=\frac{Q}{A}=\frac{\int_A udA}{A}=\frac{1}{2}V

T--SUSTech Shenzhen--annotated-device.png
Fig. 3 The geometry of the microfluidic channels. The lengths of straight channels between AB and AC (LAB, LAC) are 14.3mm and 12.0mm, and the curved channels between AB and BC(RAB, RBC) are 108.0 mm and 105.0mm.

Based on the integral form of the continuity equation for an incompressible fluid, at any given time, the sum of flow volume in each branch is equal to the total volume pumped in the whole chamber. According to the Kirchhoff's law, the accumulation of flow speed at the joint point must be zero. It is easy to get the equation that\begin{matrix} L_{AC}V_1=L_{AB}V_2+R_{AB} V_3 \\ V_2:V_3=R_{AB}:L_{AB} \end{matrix}

Consequently, we could reach the conclusion that the maximum velocity, average flow rate and the shear force on the bottom of each channel is at a ratio of 81 : 9 : 1. To verify the modeling result, we made calibration in the real microfluidics chip, and the testing result is very close to designing value (about 75 : 8 : 1 of the maximum velocity ratio in each channel) and the simulation result (80 : 8 : 1).

Experimental Result Analysis

In the whole experiment, we tested one mechanosensitive channel, Piezo1, with different magnitude orders of shear stress.

Comparing the fluorescence intensity amplitudes corresponded to the shear stress ranged from 0 Pa to 5 Pa, we found a best response at around 0.01-0.1 Pa. No response was observed when the shear stress is larger than 2 Pa.

T--SUSTech Shenzhen--AD0520F4BABB8B3DC7ECF6A15CBF1652.jpg
Fig. Comparison between the R-GECO cell response(a) and Piezo1+R-GECO cell response(b) to the 15kHz Buzzer’ s simulation.

T--SUSTech Shenzhen--20160907,R-GECO+Piezo1,sound,20K.png
Fig. 5 Fluorescence change of R-GECO+Piezo1 cell when stimulate by 20kHz sound emitted by a buzzer. Sound was started from 5s to 15s. 5 cells were selected and their fluorescence intensity changed as shown in the figure.

Discussion Details

Calibration

Rainbow beads (SPHEROTM Rainbow Calibration Particles, diameter: 6um) were dissolved in the cell culture medium. A series of pumped flow rate (5ul/min, 15ul/min, and 45ul/min) were applied to generate a steady fluid flow. The exposure time was set to 100ms (one representative image is shown in Fig. 6).

T--SUSTech Shenzhen--DB56D45F-D056-4A82-897A-2CE77C2C4A12.png
Fig. 6 Bead trace in the fastest microfluidics channel with The Flow Rate of 5ul/min

By using our customerized MATLAB program, the ratio of maximum flow velocities were calculated as 13 : 100 : 978. The absolute speed with pump speed of 45 um/min is shown in Fig. 7.

T--SUSTech Shenzhen--855C7E02-2E51-441A-9492-A2B281185010.png
Fig. 7 Maximum Velocities in Each Channel with The Flow Rate of 45ul/min

Code & Details

Simulation

To further validate our design, we also performed the simulation using the Finite Element Method (FEM) to confirm that the field in microfluidic channel satisfies our expectation. FEM is a method for modeling and simulating physics-based problems. It divides a large problem into smaller elements, these smaller elements will be solved separately and then be assembled backed to the original model. A collection of smaller elements is called a “mesh”, the “mesh” is constructed by numerous elements, the smaller the size of the element is, the finer the “mesh” is, and the more accurate will the result be. The final geometry set up can be seen from below (Fig. 8).

T--SUSTech Shenzhen--geometrydscvdfscvsd.jpg
Fig. 8 Final geometry setup

Under different pumped inflow rate(5μL/min, 15μL/min and 45μL/min), the velocity magnitude distribution was calculated. The result of maximum velocity and shear force applied on the bottom wall matched with the mathematics perfectly(around 80: 10: 1 in all the conditions, shown in the table below).

Channel

Flow Rate

fast middle slow
5μL/min 5414μm/s 549μm/s 68μm/s
15μL/min 16242μm/s 1646μm/s 204μm/s
45μL/min 48724μm/s 4938μm/s 612μm/s

Table 1 Simulation results of central line speed of each channel

Results of mathematical demonstration (1: 9: 81), calibration (13: 100: 978) and simulation (1: 10: 80) are consistent with each other. This shows that the model is feasible for estimating the shear force that generated by microfluidics on cell membrane. In order to obtain the exact shear force, we inputted the experimentally used flow rate as a boundary condition (6.25μL/min,50μL/min) in our model. The shear stress was also calculated.

Channel

Flow Rate

fast middle slow
6.25μL/min 0.269Pa 0.027Pa 0.003Pa
50μL/min 2.15Pa 0.22Pa 0.03Pa

Table 2 Simulation results of central line shear stress

T--SUSTech Shenzhen--sheardsgvfdv.png
Fig.9 Shear stress distribution under input flow rate 50μL/min (log scale)

Detailed Protocol

Acoustic Field

Sonic and ultrasonic waves could generate a pressure field to the cells adhering to the bottom of the cell dish. In our study of the sensitivity of mechanosensitive (MS) channel, we really found a most efficient sound frequency using buzzer and 108kHz ultrasonic transducer.

T--SUSTech Shenzhen--POCStrwgtvbwr.jpg
Fig. 10 B
T--SUSTech Shenzhen--POCSrtheteyh.jpg
Fig. 10 A

Fig. 10 (A) R-GECO+Piezo1 cell fluorescence intensity increased greatly when stimulated by 15K and 20KHz sound. While no obvious fluorescence intensity changed when GECO cells (without MS channel) were stimulated (B).

However, to quantitively define the relationship of channel opening ( considering the influence of energy or force difference), it was important to know the pressure field distribution on the cell layer under certain conditions. Mathematical analysis and finite element analysis (FEA) were used to define the modeling.


Audible Frequency Result Analysis

To discover the response of MS channels to audible vibration, buzzers, balanced amatures and speakers were tried as sonic stimulators applied to the cells with R-GECO and Piezo1 channel, but only buzzers induced obvious cell response significantly in high frequency conditions (15kHz and 20kHz) when they are attached to the bottom of a cell dish each time.

To explain that, a modal analysis method could be used when a buzzer was attached to the bottom of a cell dish, the shear stress induced by the asynchronism between cell culture medium and cell dish buzzer-forced oscillation is the driving factor of the channel response. It is interesting that the shear force magnitude in this condition is similar to the force magnitude in microfluidics channels.

T--SUSTech Shenzhen--buzzer-system-photo.png
Fig. 12 Buzzer attached on the bottom of cell dish
T--SUSTech Shenzhen--buzzer-system-model.png
Fig. 11 Design pattern of the buzzer


Considering that the cell culture medium is a viscous and incompressible fluid with μ= 0.012dyn·s/cm2(0.0012Pa·s), it can not vibrate uniformly with the buzzer. The shear stress due to the differential distribution of fluidic velocity surrounding cell can apply a strain \gamma on the cell membrane.

\dot \gamma=\lim_{\delta t \rightarrow 0}\frac{\delta \theta}{\delta t}=\frac{\partial \theta}{\partial t}=\frac{\partial u}{\partial v}

For sound waves, I \propto p_0^2, p0 is the acoustic pressure and I \propto s_0^2, s0 is the displacement amplitude.

Thus we have I = \frac{p_0^2}{2\rho v},\Delta p_m=(v\rho \omega)s_m, which indicates that the intensity of sound waves follow an inverse square law.

Shear stress in the fluid is given by \tau = \mu \frac{du}{dy},u=s_m\cdot f

To define the amplitude of dish vibration, we measured the sound intensity by using Brüel & Kjær 1/8-Inch Pressure Field Microphone with Type 2669 Preamplifier (4138-C-006), which is calibrated from 6 Hz to 140 kHz.[2]
 Sound speed in the air v=340 m/s, air density is 1.29 kg/m3
, angular velocity is 2π*15000Hz forced by the buzzer.

T--SUSTech Shenzhen--illustration-acoustic-measurement.png
Fig. 13 Measure the sound intensity by acoustometer

Acoustic pressure \Delta p_m = 4\text{Pa} is applied by the buzzer attached on the bottom of dish. 
From the formula above, the amplitude of dish vibration is around 9.68*10-7m. The shear stress applied on the dish bottom could also be calculated and the result is 0.01 Pa, which matches accurately to the shear stress generated in the microfluidic channel when the flow rate is 50μL/min in the slow channel.

Ultrasound Experiment Analysis

First of all, a function was studied to give pressure on the surface of the ultrasonic transducer-water interface knowing the input voltage. Based on the interface pressure and physical properties of device, we constructed FEA models to simulate the ultrasonic radiant pressure field of the cell layer. Pressure field was studied in conditions of diverse power and distance between transducer interface and cell layer.

T--SUSTech Shenzhen--GECO-PIEZO-Ultrasound.png
Fig. 14 R-GECO+Piezo1 cells with DOX added in culture medium were stimulated by 108kHz ultrasound from 10s to 30s. Four regions were selected. Two R-GECO+Piezo1 cell region were chosen one from the right side of the video and another from left side. Two backgrounds were chosen the same way.

T--SUSTech Shenzhen--equivalent-schematic-emitter.png
Fig. 15 Equivalent Schematics of the Transducer

The equivalent circuit of ultrasonic transducer was used to calculate the ultrasonic radiant power of an ultrasonic transducer. We assume the ultrasonic energy was evenly distributed on the transducer interface[3], that is:

I\left( x,y,z = 0 \right) = \left\{ \begin{matrix} I_{0},x^{2} + y^{2} \leq R^{2} \\ 0,x^{2} + y^{2} \lt R^{2} \end{matrix} \right.\

Where I0 is the absolute ultrasound intensity, R is the radio of transducer interface

According to power intensity and pressure relation:

I_{0} = \frac{{P_{0}}^{2}}{2c\rho}

In which P_0 , c, \rho are respectively absolute pressure, acoustic velocity and water density. We managed to calculate the pressure on the transducer-culture medium interface.

Then, we implemented FEM to do a series of simulations to find the absolute pressure filed distribution in different conditions. 108kHz and 1.1MHz transducer device were modeled as is shown in Fig. 16

T--SUSTech Shenzhen--11 1 2D Nt.png
Fig. 16 B
T--SUSTech Shenzhen--108 1 2D Nt.png
Fig. 16 A
T--SUSTech Shenzhen--11 1 3D Nt.png
Fig. 16 D
T--SUSTech Shenzhen--108 1 3D Nt.png
Fig. 16 C

Fig. 16 (A) Pressure distribution of 108KHz ultrasonic transducer, the transducer was 1.0mm far above the cell layer. (B) Pressure distribution of 1.1MHz ultrasonic transducer. 3D pressure distribution for 108KHz condition (C) and 1.1MHz condition (D).

The influence of distance error on pressure distribution pattern was also studied, which indicated that the 108kHz transducer was very robust to distance error, while the 1.1MHz acted as a chaos when little distance error occurs.

In all, the 108kHz ultrasonic transducer was recommended as ultrasonic stimulator for quantitative measure cell response based on modeling and experimental results.

Details

References

  1. Booth, R., & Kim, H. (2012). Characterization of a microfluidic in vitro model of the blood-brain barrier (μBBB). Lab on a Chip, 12(10), 1784-1792.
  2. Brüel & Kjær TEDS System Product Data, Retrieved from https://www.bksv.com/~/media/literature/Product%20Data/bp2225.ashx
  3. A Zhen-Xiao, Simulation and Visualization of the Radiated acoustic Field of Ultrasonic Transducer. Nondestructive examination (NDE), 33(5),2-6

Made by from the iGEM team SUSTech_Shenzhen.

Licensed under CC BY 4.0.