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Multidisciplinary Senior Design ConferenceKate Gleason College of Engineering

Rochester Institute of TechnologyRochester, New York 14623

Project Number: P13373

Nano-Fluidic Characterization

David WestMechanical Engineering

Justin DavisMechanical Engineering

David SharpMechanical Engineering (Leader)

ABSTRACT:

The main objective for this project is to build, test, and validate an apparatus to test various Nano-porous membranes and write a program to collect the characteristics of the flow across these membranes. Such characteristics include the pressure drop between both sides of the membrane, fluid flow rate through the system, and a measurement of the fluid temperature. The system itself consists of various fittings to ensure the same size diameter piping is used throughout the system, a membrane holder to house and protect the membrane, pressure transducers to observe the pressure difference, a flow sensor, a thermocouple, and a syringe pump to inject the fluid into the piping. The entire system will be kept secured on a ridged frame that will keep all parts connected and in place, preventing them from moving during the procedure. As fluid is injected through the pipe using a syringe pump, data for each of the fluid characteristics will be collected using various sensors. A fitting for secondary fluid injection can also be used for a secondary testing procedure, in which electrolytes and food coloring can be injected into the system during testing. The data collected during the experiment will then be exported onto LabVIEW, where the data can be observed and edited for further analysis.

NOMENCLATURE:

Nanoporous Membranes- A Small disk like material with microscopic pores throughout its surface area.

Carbon Infused Membranes- Membranes with carbon lining through each of its pores

NBIL- Nano-bio Interface Lab – Dr. Michael Schrlau’s lab at Rochester institute of technology that analyses nano-materials.

CNT- Carbon Nanotubes, membranes lined with carbon throughout their pores.

DAQ- Data Acquisition Device used to collect data from the pressure transducers.

Copyright © 2013 Rochester Institute of Technology

Table 1: List of Customer Needs

BACKGROUND

Nano-porous membranes are used for a multitude of uses. They are primarily used for filtration uses in the medical industry where quick and precise filtration is necessary when injecting fluids into the body. These membranes primary usage in the NBIL will be as a template for building CNT’s. Currently however, there are no definitive ways to characterize the flow across these nanoporous membranes accurately for usage at the NBIL.

The current testing system uses a syringe pump to inject fluid through the membrane, and then have it immediately exit into a beaker so that an average flow rate can be determined. Since the exit of the system goes directly outside the system, the pressure is assumed to be atmospheric, so only the pressure just before the membrane would need to be measured. The new system design will ensure that all values obtained will be directly from the sensors themselves, eliminating any measurement errors during the analysis. Also, it is desired that the flow going through the membrane should be visibly seen. Below are the main components that the system must accommodate throughout the design process.

Quantify expected flow across membrane through calculations and assumptions Reduce the cost of measurement devices and system parts Physically observe the flow from outside the system Collect and store all data from within the system Change the flow rate of the system Control the sampling rate of data collection

DESIGN PROCESS

Customer Needs:

Spec # Specification (metric) Unit of Measure Marginal Value Expected ValuesS 1 Test rig size limit (l x w x h) mm 200x120x100 510X115X40S 2 Membrane diameter mm 13 - 25 13S 3 Development cost $ < 2,500 < 2,500S 4 Measuring pressure range kPa < 500 <690S 5 Measuring pressure accuracy Pa 0.1 1725S 6 Measuring flow rate range mL/min 0 - 3 0-5S 7 Measuring flow rate accuracy microliter/s 0.001 2.5S 8 Measuring temperature range ᵒC -20 to 100 -20 to 100S 9 Measuring temperature accuracy ᵒC 0.01 1

S 10 Fine sampling rate per second 100 100S 11 Coarse sampling rate per minute 1 1

In order to accurately design a system that meets the customer specifications, each need and specification was analyzed and changed based on how the proposed design would meet each specification. Shown in table 1, each of the main specification for the system to meet was listed along with the desired value for it to achieve once completed. The column to the right shows the proposed design’s specification values, allowing the two values to be compared and analyzed in order to come to a consensus as to which specifications are able to be obtained and which ones would need to be sacrificed in order to obtain the most accurate results possible. This process was repeated until the final design of the system was able to meet customer satisfaction.

Before the final design, an initial analysis of the fluid flow through the system was conducted so that a baseline of expected values can be obtained. This step in the design procedure is critical since the values that the system obtains will need to be cross-referenced with values from both the previous system as well as calculated values obtained prior to testing. That way, the validity of the measurements found from the constructed system is


Figure 1 Pressure vs. Flow Rate with Varying Pore Diameters

tested and secured. These measurements incorporate the fluid flow from the entrance of the system where the syringe pump will inject fluid, to the end of the system where the flow sensor is located. The calculations themselves will incorporate measuring the velocity of the flow throughout the system as well as the pressure difference found between both sides of the membrane.

To begin calculations, various assumptions of the flow across the system need to be made. Firstly, it is assumed that flow going through the pipe is fully developed laminar flow, since the flow will have enough time to become fully developed once it has reached the membrane. It will also be assumed that the fluid itself will remain incompressible and at a standard temperature and pressure. Since it is hard to predict exactly how many nano-pores are within each membrane, it is assumed that each membrane has a constant pore density across its surface area. This assumption allows for the calculation of pore number for the effective surface area of that membrane. Lastly, the effects of head loss throughout the system can be considered negligible, since previous data calculations have shown that the head loss of the system did not greatly impact the values found.

Once the assumptions are obtained, equations for the mass flow rate and the differential pressure in the system are derived based on standard fluid mechanic laws. These simplified equations are shown below:

Equation 1: Flow Velocity Equation 2: Differential Pressure:

The first equation shows the velocity of the fluid going through the system and the flow going through each the membrane’s pores. In this case, the area of the pipe refers to the area of the membrane pore. In the pressure change equation, the diameter of the membrane is pore and the thickness of the membrane is used along with the fluid flow going across the membrane. This calculation is valid since the pressure difference of both ends of the tube represents the pressure difference between both sides of the entire membrane. These equations were then input into MATLAB so that the effects of the velocity of the fluid and the exposed surface area of the membrane as well as the membrane diameter can be compared to see its effect on the pressure difference in the system.

After performing the calculations in MATLAB, the results from figure 1 are obtained. This shows that as the pore diameter of the membrane decreases, the flow rate of the fluid increases for the same pressure drop. The current standard membrane pore diameter is 147nm with carbon injected within the pores; this value is able to range between 200nm with no carbon inside to enough to reduce the tube to 100nm.

Software System Architecture:


Figure 2: Sensor to Computer Layout

Figure 3: LabVIEW Block Diagram

In order to be able to collect information from each of the sensors in the system, a program was created in LabVIEW so that the data can be observed throughout the experiment and then exported to Excel for further analysis. In this system, there are the two pressure transducers, the thermocouple, and the flow sensor each taking separate measurements at the same instance. These sensors are all connected a computer via USB.

The two pressure transducers are connected to a data acquisition device connected to the computer and powered with a 19V power source. The DAQ device will serve as a way to convert the voltage values from the pressure transducers into data LabVIEW understands, which can then be edited so that a pressure value can be seen for each sensor. In order to adjust the voltage to display the correct pressure value, each transducer needs to be calibrated to see the relation between the voltage signal read and the actual pressure being given. That way, a simple equation can be written in LabVIEW to change the voltage signal into pressure values.

The temperature sensor is a T type thermocouple, which signifies the two types of metal used to measure change in resistance. It is first put into a National Instruments Thermocouple reader, which is then plugged into the computer for LabVIEW to detect. The block diagram for the thermocouple is similar to the one used for the pressure transducers; however the set-up for the temperature sensor is far more simple as it does not require calibration due to the sensor specific reader purchased.

The flow sensor comes with its own cable and program that can be used to read the flow values from it. However, to ensure that the values obtained for the flow rate matches the values for the pressure and temperature at the same instance in time, the measurements will be taken through LabVIEW using the flow sensor’s driver software. This driver software is integrated into the VI written for the other sensors, that way all values obtained will be able to be assured of their timing. Once all the sensors are connected, the block diagram should look similar to the one shown above. Note: Sensirion driver software is not shown, as it is extremely complex and would be hard to depict in Figure 3.


Figure 4: LabVIEW Front Panel

Figure 5: SolidWorks System Design

Figure 4 shows the LabVIEW front panel of the block diagram depicted in Figure 3. There are two graphs, thermometer, COM port protocols, and time controls. The first graph shows the pressure difference between the transducers while the next shows the flow rate of the fluid in the system (recorded as a function of time). The thermometer shows the current temperature of the flow. In order to set a time step, a “Time Step” field is available to the user that can be changed from any maximum level down to the minimum processing time of the flow sensor communication with the USB port. This value changes from computer to computer, dependent and the version of USB used as well as the allotted ram allocation of the computer used. If a lower value is entered than this minimum, the times step will bottom out at this value. A time step of “0” seconds will result in this minimum.

System Design:The system itself consists of various couplings and fittings so that each of the sensors can be fastened

securely to the system. First, a straight compression fitting is used so that the pipe from the syringe pump and the system piping can be connected. Next, a T type compression fitting is placed so that the first pressure sensor can be connected and take readings before the membrane holder. Another type of T-fitting (Luer Lock T) is put in place after to serve as both a pressure release point as well as a secondary fluid injection point just before them membrane holder. A custom made fitting is then used in order to attach the holder to the Luer T. Clear piping is pressed onto the holder exit so that the flow leaving the membrane can be seen. This leads to another compression fitting so a cross-type NPT coupling (where the thermocouple and the second pressure transducer are connected) can be used. Lastly, the flow sensor is attached after the cross fitting so that the flow rate of the fluid can be verified. The entire system is supported by two extruded aluminum ASS railings to ensure the sensors remains stable and components can be easily rearranged.

Each of the sensors (save the thermocouple) also has an extra support part designed to make sure the system does not bend due to their weight. The transducer supports consists of an L shape metal piece in which the transducers can secured with a set screw to keep the transducer from moving. The flow sensor is supported with a flat plate connected to either rail and screwed to the base of the flow sensor itself. The frame is supported with the option of two ¾ inch aluminum pieces each with four rubber bumpers to ensure added stability in the system, or the 4 detachable legs used to raise the system.

The system in Figure 5 shows a computerized design of the system made in SolidWorks. This system was used as a reference model so that the true system could be constructed. The picture in Figure 6 shows the fully constructed system used for the experimentation of the nano-porous membranes. Also, the membrane holder can be switched between a plastic or metallic version depending on user requirements. The plastic holder lets the user observe flow around the membrane during experimentation, but cannot survive high pressure, whereas the metallic holder cannot be seen through, but can survive higher amounts of pressure.


Figure 6: Constructed System Design


TESTING PROCEDURE

To begin using the system for experimentation, the membrane holder is removed from the system by sliding back the plastic tubing from the holder. To remove the membrane easier, unscrew the second transducer and flow sensor supports enough so that it can slide easier. After removing the holder open it, revealing the O-ring and screen if the metal holder is used (the plastic holder does not have these additions). The screen inside the membrane holder is used to support the membrane and prevent it from breaking under high pressure. Carefully place a membrane on top of the screen inside the membrane holder, making sure the membrane does not crack or split during the process. After carefully closing it, the membrane holder can now be placed back into the system. Make sure that all connections on the holder itself are secured and any screws and connections in the system are tightened. Next, the syringe pump is loaded with a syringe filled with a desired fluid, and connected to the inlet of the system. The pump is then set to the desired flow rate and the syringe size that will be used.

Once the system has been set up successfully, the sensors are each connected to the computer and the LabVIEW program is opened. In the LabVIEW program, in the “Time Step” field (on the Front Panel), type in the desired sample rate in which the data will be collected (this value is in seconds). Also, on the Front Panel, make sure to specify the location that the data will be saved prior to experimentation. The LabVIEW program can either begin running just before starting the experiment or just after the system has been fully primed depending on what values are desired.

After making sure the LabVIEW program is set correctly and that all connections are tightly fastened and secured, the syringe pump can now be turned on so that testing can begin. Since there will be air initially in the system, it is best to wait until the entire system is fully primed and void of any air bubbles before officially recording any values. If desired, air bubbles can also be removed using the secondary injection fitting simply by slightly opening the cap on top of the fitting to allow air to escape. It takes an average of 10ml of fluid for the system to become fully primed. If a secondary fluid is to be used, connect this syringe before priming to avoid the addition of more air into the system. Once the system is fully primed, data from each of the sensors can now be collected using the LabVIEW program. Anomalous data may be due to either air in the system or a possible leak. During testing, all fluid used in the experiment exits into a beaker.

After the desired testing time has elapsed, the LabVIEW program is stopped using the stop button on the Front Panel and the pump is shut off shortly after. Ending the current run with the stop button will cause the program to save the data onto the file specified previously on the Front Panel. If the emergency stop is used then no data is created. Once the data has been output successfully, it can then be edited and used for further calculations. If any additional tests are required, these steps are repeated, making sure to fasten all connections properly again and to fill the syringe with fluid once more. Be sure to specify a new file path for additional runs to prevent data loss.

All values obtained are expected to behave similarly to the calculations done previously on MATLAB; however based on the previous system’s data, it is possible to see some spikes in pressure as the fluid flows through the system due to the initial pressure required to push flow through the membranes before leveling off.

1. Acquire Data:a. Do several runs, timing with a stop watch. Starting at t = 0 to t = 4 minutes 30 seconds, ran at

pump speed 1 ml/min. Up flow to pump speed 2 ml/min until 9 minutes. At 9 minutes, turn up to final rate of pump speed 3ml/min

b. Let this run until syringe is out of water.c. Pull pressure and flow data for each run from respective excel files into one, and average flow and

pressure columns, taking care to truncate extra data at the end as more than likely one column may have a few more data points than another.

d. Plot Average pressure vs. average flow ratee. Use linear trend line to output a fit formulaf. Use MATLAB to plot fit line to compare to theoretical line.


Figure 7: Pressure vs. Flow Rate Analytical vs. Average Numerical Data

RESULTS:

In order to find a prediction of the flow across the membrane and compare it to the calculated data found during the analytical analysis, one membrane was tested under multiple flow rates and set periods of time to keep the data collected as consistent as possible. This process was done multiple times to ensure the average of the data found would best represent the behavior of the flow through the system. The membrane used for this procedure had a 200nm pore diameter with an exposed surface area of diameter 9mm. To keep the assumptions of fluid behavior simplified, standard filtered water was used during the test. After taking measurements from multiple tests using the membrane testing apparatus, the values of the average pressure difference and the flow rates were calculated in Excel. Both run and the average were graphically represented so that a general equation describing the relationship of pressure to flow rate can be determined. This equation was then plotted alongside the analytical data found in MATLAB before to see how closely the values found during testing represented the expected values. The resulting comparison is shown in the figure below. To calculate the error bars, a high bound and low bound were created by using excel to create a formula for the two separate runs. Subtracting these two formulas and dividing by 2 yeilded the spread of the points.

Looking at the resulting comparison, it can be inferred that the data collected from the system matches the linearity between the pressure drop and the rate of flow as found in the theoretical analysis. Pore density used in the theoretical analysis could be slightly different than that of the true value, resulting in the difference in slope of the two lines above. This assumption is further supported due the analytical data showing how much the pressure difference can increase simply by slightly increasing or decreasing the pore diameters. The results found from each individual test trial also show that each membrane can have either a slightly higher or lower pressure for each corresponding flow rate. These were used to calculate the error spread. Seeing as the theoretical data line falls in the error bars, the data is a decent fit. This can be due to the fact that there is a possibility of some slight error from the measurement devices themselves, or due to the fact that the flow characteristics change as the membrane is wetted and re-wetted. However, this difference in the measurements is only slight, still proving that the system is able to predict the flow across the membranes successfully.


CONCLUSIONS AND RECOMENDATIONS:

After completing the designing and testing of the nano-fluidic characterization test apparatus, the resulting product received is able to accurately predict and read flow values for each of the membranes with a high amount of confidence in its values. The setup of the system allows for easy rearrangement of each of the sensors along the railings while still providing adequate amount of support to each of the parts along the system. The frame on the system has been elevated just enough so the flow coming from the syringe pump remains strait and linear along the system.

During testing of the 200 nm pore density membrane, the data collected seemed to vary in pressure difference, however looking at the overall values given for each trial, they each were either slightly higher or lower than the expected values for pressure, which was seen when the average of these tests were taken and graphed Also, for each new membrane tested, there was a certain amount of pressure build up required for flow to pass through the membrane before the pressure became stable at that flow. This effect can also be seen in the previous testing set up, confirming that the new apparatus is able to yield the same results and better once all necessary precautions of loading the membrane are taken.

Looking back at the beginning of the design of the system, a few things could have been done differently to ensure the system designed was perfected. Firstly, the use of the clear membrane holder was originally meant for high pressure flow as well as low pressure, however due to the inconsistency with the sealing of the clear membrane holder, there were often leaks that would appear, meaning the flow was going around the membrane and not through as originally predicted. For the sake of getting consistent data and to keep the membranes from breaking too often from the loading process, the metallic membrane holder is recommended to be used for the membrane testing. Also, given more time to work with the system frame, the system would be designed so that both the width and the height of the whole system could be adjusted to meet the needs of the pump. However, due to time constraints on the construction of the frame and the lack of materials needed to design it, the height of the system can only be changed from a higher to lower elevation. Another issue that would be worth looking into in the future would be the apparent large error spread of the pressure data. The transducers were reading correctly according to the calibration, so an explanation as to why two identical runs can yield different results is a point worth further study. Lastly, if there was more time to work on the LabVIEW coding, synchronization between the program and the pump would have been implemented so that the syringe pump would start as soon as the program began taking measurements, as well as have its settings changes on the front panel as well. This idea however would have taken too much time to implement, so was kept to changing the pump functions manually for simplicity reasons.

ACKNOWLEGEMENTSSpecial Thank You To:

Dr. Michael Schrlau (ME Department) Masoud Golshadi - Primary User Michael Zona (Xerox) - Industry Guide John Wellin (ME Department) - Guide


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