Line 290: | Line 290: | ||
The metering accuracy can be calculated using the following formula: | The metering accuracy can be calculated using the following formula: | ||
<br> | <br> | ||
− | <div style="text-align:center"> | + | <div style="text-align:center; margin-top:20px;"> |
\[Percent Accuracy = \frac{Volume Metered}{Volume Dispensed} * 100\] | \[Percent Accuracy = \frac{Volume Metered}{Volume Dispensed} * 100\] | ||
</div> | </div> | ||
Line 296: | Line 296: | ||
The metering error can be calculated using the following formula: | The metering error can be calculated using the following formula: | ||
<br> | <br> | ||
− | <div style="text-align:center"> | + | <div style="text-align:center; margin-top:20px;"> |
\[Error(uL) = Volume Metered - Volume Dispensed\] | \[Error(uL) = Volume Metered - Volume Dispensed\] | ||
</div> | </div> |
Revision as of 16:23, 30 October 2017
![](https://static.igem.org/mediawiki/2017/0/02/MARSbackground.png)
![](https://static.igem.org/mediawiki/2017/2/22/MARSLogo2.png)
![](https://static.igem.org/mediawiki/2017/f/fd/MARS_FF.png)
Evaluate your Chip with Fluid Functionality Checklist
Summary
$c = \pm\sqrt{a^2 + b^2}s$
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Cras lacinia urna ut lectus dictum ultricies. Phasellus euismod tellus quis felis condimentum ullamcorper. Aenean blandit rutrum viverra. Nam at nisl feugiat, gravida magna non, porttitor libero. Suspendisse at purus mattis, ullamcorper odio at, fringilla mi. Sed ultrices viverra est, eu fermentum justo feugiat vitae. Nunc sed egestas enim. Sed sed eros ac mauris suscipit aliquam. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Pellentesque tincidunt nisi justo, a volutpat risus eleifend non.
![Picture](https://static.igem.org/mediawiki/2017/5/5f/LysisFlow.png)
Qualitative
Leak (Initial)
This qualitative failure is characterized by liquid leaking out of a channel and/or primitive into the space between the PDMS and flow layer. An initial leak occurs almost immediately after a liquid passes the area of the leak. Regardless of scale, these leaks are considered a failure mode.
Leak (Over Time)
This qualitative failure is characterized by liquid leaking out of a channel and/or primitive into the space between the PDMS and flow layer. A leak that occurs over time is not characterized by an initial leak growing over time but as a leak that appears a significant amount of time after liquid has passed the location of a leak. These leaks can be seen in situations where a seal degrades during incubation period, leading to a new leak forming minutes after liquid initially passed through a section. Regardless of scale, these leaks are considered a failure mode.
![](https://static.igem.org/mediawiki/2017/5/5b/MARS_FF_Leak.png)
Air Bubble
This qualitative failure is characterized by an air bubble being present within a channel or primitive. Air bubbles can affect proper liquid flow and can reduce the accuracy of design features such as time-dependent mixers and metering. Regardless of scale, air bubbles are considered a failure mode.
![](https://static.igem.org/mediawiki/2017/c/c3/MARS_FF_Bubble.png)
Liquid does not cross an OPEN Valve
This qualitative failure is characterized by liquid not crossing over a valve that has been opened by actuating the corresponding syringe on the control layer. This failure can exist in many forms, such as liquid pausing after filling the first portion of the valve and never crossing into the second section or leakage around the first portion of a valve. This failure is often accompanied by leakage due to pressure buildup.
![](https://static.igem.org/mediawiki/2017/4/4a/MARS_FF_NoPass.png)
Liquid crosses a CLOSED Valve
This qualitative failure is characterized by a liquid crossing over a valve that is closed, meaning that it’s corresponding control syringe has not been actuated. This failure can exist in many forms, such as liquid leaking over a valve that has never been opened before or leaking over a valve that was previously opened by is not closed. This failure can lead to contamination of liquids as well as inaccuracies with features such as metering.
![](https://static.igem.org/mediawiki/2017/6/67/MARS_FF_PassClosed.png)
Mixer does not mix liquids sufficiently
This qualitative failure is characterized by the final output of a mixer not being sufficiently mixed. This failure can be dependent on the chip being tested, as certain procedures will have varying levels of tolerance regarding mixture homogeneity. In general, liquids exiting a mixer should be relatively homogenous; a quantitative calculation of mixing can be performed to calculate how homogeneous the final mixture is.
![](https://static.igem.org/mediawiki/2017/0/0f/MARS_FF_NOMIX.png)
Quantitative
PSI Calculation
When a chip's internal pressure exceeds the maximum pressure that the sealing can withstand many complications such as leaks will ensue. In order to evaluate whether the chip will be able to function without these issues a PSI calculation is needed to be performed. This quantitative test is utilized to measure the internal pressure of a specific primitive inside your microfluidic chip. The MARS chips have all been manufactured using Makerfluidics, and have been evaluated to withstand an internal pressure of up to 5 PSI. To calculate the pressure in a given primitive the following three equations need to be used.
- \[10h < w\] or \[2h>w\]
- \[12\mu L/wh^{3} < R_{fluid} < 32\mu L/wh^{3}\]
- \[\Delta P=R_{fluid}Q\]
Mixer Effiency
The mixing of two fluids is something that can often be qualitatively observed, however in order to properly perform an experiment certain amounts of mixing must be achieved. In order to evaluate the degree of which fluids are being mixed in a mixer primitive a mixer efficiency test is needed to be performed. This quantitative test is broken down into a two part process:
- Image Processing After running fluid through your mixer, pictures need to be taken at the regions prior to entering the primitive and after it exits the primitive. In order to obtain RGB data from these images, image processing software such as ImageJ need to be implemented. Using ImageJ a 1 pixel wide box is created that spans the length of the channel. The two important pieces of data that need to be obtained using this box are the average RGB value over that area, and the RGB value at the outer edge of the channel. After collecting this data we can move on to calculate the mixing efficiency.
- Efficiency Calculation The efficiency of the mixing itself can be measured using the following equation:
![](https://static.igem.org/mediawiki/2017/0/02/MARS_FF_Mixer1.png)
![](https://static.igem.org/mediawiki/2017/a/ad/MARS_FF_Mixer2.png)
\[\gamma = 1-2\left [ \frac{\int RGB-RGB_{avg}dL}{\int dL} \right ]\]
Once this value is obtained the channel primitive is able to measured to see if it is suitable to perform the needed function.
Valve Actuation
Even though it can be easily observed that a fluid is not traveling over a valve, it is not easy to determine whether the PDMS is being properly actuated by the primitive. In order to evaluate each valve’s functionality a valve actuation test can be performed.
This quantitative test involves modeling the deflection of the PDMS as a beam fixed at both ends. This is would only be an approximation since the valve geometry would not directly align with the geometry of a beam. The maximum deflection of the beam would be equivalent to the PDMS deflecting into the circle valve.
We would substitute the value of length in the max deflection equation with the diameter value of the valve. We can than calculate the force needed in order to fully actuate the PDMS into the circle valve.
The next step is to convert that value of force into a value of pressure. Can use the formula:
Lastly, since we know the volume within the chip and tubing the syringe is connected to we can use Boyle's law to calculate for the amount of volume we would need to pull the syringe back to actuate the valve.
This quantitative test involves modeling the deflection of the PDMS as a beam fixed at both ends. This is would only be an approximation since the valve geometry would not directly align with the geometry of a beam. The maximum deflection of the beam would be equivalent to the PDMS deflecting into the circle valve.
\[\Delta Z = \left ( \frac{5}{358} \frac{Wl^{3}}{EI}\right )\]
We would substitute the value of length in the max deflection equation with the diameter value of the valve. We can than calculate the force needed in order to fully actuate the PDMS into the circle valve.
\[W = (\frac{358\Delta Z E I }{5D^{2}})\]
The next step is to convert that value of force into a value of pressure. Can use the formula:
\[P = FA\]
Lastly, since we know the volume within the chip and tubing the syringe is connected to we can use Boyle's law to calculate for the amount of volume we would need to pull the syringe back to actuate the valve.
\[P_{1}V_{1} = P_{2}V_{2}\]
Metering Accuracy
The metering primitive was developed to dispense relatively accurate volumes of liquid. However, for biological experiments a certain level of accuracy is required when it comes to volumes used. In order to ensure this primitive is dispensing relatively accurate volumes of liquid, a metering accuracy test must be performed. This quantitative test is broken down into a two part process:
- Image Processing After running the metering portion of your chip, pictures need to be taken before and after the oil has dispensed all the liquid from the metering section. An image processing software, such as ImageJ is then used to analyze how much liquid was metered and how much was actually pushed.
- Accuracy Calculation The metering accuracy can be calculated using the following formula:
To analyze the amount of metered liquid, first set the scale for ImageJ in units of microns. Then, using the Rectangle selection tool, draw a rectangle encapsulating the first metered liquid section. This can be seen below:
\[Volume Metered =Area*Depth*10^{-9}\]
Repeat this process for each individual metering sections, summing them together as follows to find the total metered volume:
\[Total Volume Metered =\sum_{i}^{n}Area_{i}*Depth_{i}*10^{-9}\]
To analyze the amount volume of liquid dispensed, perform the same analysis as before on the image taken after all of the liquid has been displaced by the mineral oil.
\[Percent Accuracy = \frac{Volume Metered}{Volume Dispensed} * 100\]
The metering error can be calculated using the following formula:
\[Error(uL) = Volume Metered - Volume Dispensed\]
If there is a significant error in metering, this suggests that there was either a milling inaccuracy or a leak at a channel and/or valve during the pushing process.