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Single Cell Biosensor Allan Fierro David Sehrt Doug Trujillo Evan Vlcek Michael Bretz.

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Presentation on theme: "Single Cell Biosensor Allan Fierro David Sehrt Doug Trujillo Evan Vlcek Michael Bretz."— Presentation transcript:

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2 Single Cell Biosensor Allan Fierro David Sehrt Doug Trujillo Evan Vlcek Michael Bretz

3 Introduction Allan Fierro Optical Detection Circuit Flow Control Cell Trapping Fabrication

4 What is Flow Cytometry? Technique for counting cells Examining cells Sorting cells

5 Example of Flow Data Analysis of a marine sample of photosynthetic picoplankton by flow cytometry showing three different populations (Prochlorococcus, Synechococcus and picoeukaryotes)

6 What is Optofluidics? Optofluidics combines microfluidics and optics Able to see the difference in light refraction wavelength *diagrams courtesy of L. Shao, Ph.D. from Ph.D. Defense Presentation

7 Flow Cytometry vs. Optofluidics Flow uses scatter of light Flow more expensive to run Flow samples take longer to prep Can’t use cells after Optofluidics uses refraction of light No fluorescent dye - cheaper and less prep time Optofluidics can keep cells after Flow CytometryOptofluidics

8 Microscope Infrared LED Cell Light

9 Fabrication David Sehrt Optical Detection Circuit Flow Control Cell Trapping Fabrication

10 DEP Chip Images courtesy of Weina Wang

11 DEP Chip Processing 1. 30 nm Chrome Deposition 2. 120 nm Gold Deposition 3. Spin Photoresist 4. Exposure 5. Development 6. Gold Etch 7. Chrome Etch 8. Resist Removal

12 PDMS Channel PDMS- Polydimethylsiloxane Suitable optical properties Adhesive to glass Channel mold made of a silicon substrate and SU-8 Photoresist PDMS poured into mold and baked to form elastic solid

13 DEP PDMS Bonding Oxygen-plasma treated Bonding is performed with a mask aligner Minute Pressure is applied for bonding to transpire PDMS Channel DEP Chip

14 Flow Control Evan Vlcek Optical Detection Circuit Flow Control Cell Trapping Fabrication

15 Chip Design for Fluid Two drilled holes at each end Nanoports for each hole 200 µm wide, 25 µm deep, channel Need flow rate of approximately 40 µm/s drilled hole nanoport channel chip 200 µm flow *picture courtesy of L. Shao, Ph.D. from Ph.D. Defense Presentation

16 Nanoport Assembly chip drilled hole adhesive o ring nanoport nanotube TOP VIEWSIDE VIEW nanotube nanoport from pump “waste” adhesive o ring

17 Block Diagram Pump?Off CycleStop?On CycleStop Pump Set Parameters Yes No Labview program Oriel Controller DB9  RS-232 ActuatorSyringeNanotube Chip

18 Actual Setup Pump set to move actuator 0.5 µm/s On for 0.825 s, off for 7 s (≈10.5% duty cycle) π cm 2 syringe area * 0.5 * 10 -4 cm/s * 0.105  1.66 * 10 -5 cm 3 /s through channel This is 1.43 liters being pumped through the channel every 24 hours! Oriel Controller nanotube syringe actuator Labview VI RS 232 0.5 µm/s

19 Actual Setup actuator syringe Labview program Oriel controller

20 Optical Detection Circuit Doug Trujillo Optical Detection Circuit Flow Control Cell Trapping Fabrication

21 Optical Detection of Cells -Purpose- Detect the presence of a cell in proximity of a trap Interface with the pump flow controller Provide triggering for the RF traps -Implementation- Photo diode coupled via fiber optic cable from microscope to detect light modulation Monitor the change of the reverse bias current from the diode through the use of a USB Data Acquisition unit Digital switch to trigger RF traps

22 Optical Detection of Cells -Requirements- Able to detect light modulation of cells traveling 40 µm/sec Output a voltage in the range of 2V - 3.8V. Any higher voltage output may damage the DAQ Photodiode must be responsive to light source of 860-910 nm Circuit Design Flow Chart Microscope output Photo Diode Low pass filter Amplifier Buffer Signal to DAQ

23 Optical Detection of Cells -Light Source- The light source is set up as shown in the figure. The LED is a high-intensity Infrared LED. Lear, Kevin L., Hua Shao, Weina Wang, and Susan E. Lana. "Optofluidic Intracavity Spectroscopy of Canine Lymphoma and Lymphocytes." IEEE Explore (2007). 4 Dec. 2007. 50/125 multimode fiber micro- fluidic sample beam- splitter infrared source LEDs Circuit Labview DAQ Traps DAQ LabviewTraps

24 Optical Detection of Cells -Circuit Design- ~2mV Output from Diode A1 signal to USB DAQ

25 Optical Detection Figure of Time Response of Optical Detection Circuit Rise Time: 128 µs Peak Voltage: 2.7 V

26 Cell Trapping Michael Bretz Optical Detection Circuit Flow Control Cell Trapping Fabrication

27 Automated Trapping Detection Circuit Data Acquisition Unit Triggering Circuit Analog OutputDigital Output AC Signal The digital signal from the Data Acquisition Unit is input into an ADG- 452 (basically a digital switch) chip. This allows an AC signal to be applied to the DEP traps DEP Traps

28 Dielectrophoretic(DEP) Trapping Uses theory of electromagnetics to trap cells A non-uniform electric field causes polarization within individual molecules of spheres/cells. This polarization along with electric field apply a force that will move spheres to a desired location. Electric field

29 Electromagnetic modeling Ground +AC Voltage fluid flow The force caused by the electric field will push the spheres into the center of the trap. Picture Courtesy of Weina Wang et al. powerpoint presentation “Lab-on-a-Chip Single Particle Dielectrophoretic (DEP) Traps” 3-6-2006.

30 Requirements 1.Sphere must be traveling at 40 micron/second or less 2.Signal used to generate the electric field must be a time varying signal in order to produce a non-uniform electric field. 3.Signal used to generate the electric field must have an amplitude greater than 5 Volts peak to peak Both of these requirements are necessary in order for the for the force caused by the electric field to overcome the force caused by the flow of water. i.e. an object in motion stays in motion unless acted upon by a net external force.

31 Pictures of DEP traps

32 Video of DEP Trapping

33 Budget ADG 452 Digital Switch -- $15 Various circuit elements -- $10 Hytek iUSBDAQ U120816 -- $105 TOTAL EXPENSES = $130

34 Future Work Improve glass chip fabrication process Fine-tune optics for better optical detection Incorporate spectrometer and automate data acquisition Research best trap design to allow for faster flow rate Explore methods to allow for cells to be analyzed faster


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