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Cleanroom Fabrication and Applications of Surface Acoustic Wave Devices
Nitasha Goyal Madelyn Hutton Kevin Mao
[email protected] [email protected] [email protected]
Walter Roper Soumya Sudhakar [email protected] [email protected]
AbstractBeyond traditional uses as filters in radios and cell phones, surface acoustic wave (SAW) devices have applications in the medical field as biosensors. Five SAW devices were fabricated in the Rutgers MERL cleanroom through the processes of thin film deposition, photolithography, and wet etching. Measurements of the bandwidths using 3 decibel (dB) width calculations and measurements of operating frequencies of the SAW devices showed functionality as filters. Measurements of the mass of biotin demonstrate the potential use of SAW devices as microbalances and biosensors.
1 Introduction Nanotechnology and microfabrication
have gained importance in today’s world since the fields enable machines to be more energy and cost efficient. One type of device in this field is the surface acoustic wave (SAW) device. Most commonly, SAW devices act as frequency filters in instruments such as cell phones and radios, selecting only a certain bandwidth of frequencies. Today, research is being conducted using SAW devices as biosensors. Biosensors can be microbalances that measure the mass of objects on a microscale such as a strand of DNA. In addition to aiding in genetic research such as DNA hybridization, SAW devices can help diabetic patients in blood glucose testing by substantially reducing the amount of blood collected. Some recent research is focused on
SAW devices’ ability to improve the efficiency of solar panels[1]. In this work, SAW devices were demonstrated successfully as filters and used in the biosensing application as microbalances.
2 Background
The microfabrication procedure has been successfully improved in both research and industry in the past decades. Our SAW devices were fabricated in the cleanroom at Rutgers’ Microelectronics Research Laboratory (MERL).
2.1 The Cleanroom
A cleanroom is a lab in which certain environmental pollutants are highly controlled. This type of lab is commonly used in fields that are sensitive to ecological contamination such as semiconductor manufacturing, biotechnology, and microfabrication processes[2]. Despite its name, cleanrooms are not sterile; rather, they have a controlled level of airborne contamination. Airflow rates and direction, pressurization, temperature, humidity and filtration are regulated to keep pollutants at a minimum[3].
A cleanroom is necessary for the fabrication process in order to preserve the integrity of the devices made. Dust particles in the air can interfere with the fabrication of SAW devices during the fabrication process. Since the SAW devices are on the microscale, these dust particles are large enough to cause the devices to be defective[4]. In addition to
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dust, other particulates in air, such as smoke, bacteria, and cells, can also cause similar problems in the devices. For these reasons, microfabrication processes are carried out in cleanrooms where the number of particulates in the air can be controlled, decreasing the probability of defective devices.
2.2 Surface Acoustic Wave Devices
SAW filters utilize interdigital transducers (IDTs) and piezoelectricity to produce surface acoustic waves.
IDTs consist of finger-like patterns made of conductive material, such as aluminum, as seen in Figure 2.1, and are used to generate and receive the surface acoustic waves. The number of fingers, the spacing between the fingers, and the spacing between the IDTs determines which frequencies are able to travel through the circuit effectively.
Figure 2.1 Blue represents the IDTs of the SAW
device while yellow represents the quartz delay line. Courtesy of Zheng Zhang, Rutgers University.
The SAW device utilizes the piezoelectric effect by converting electrical energy (AC voltage) to mechanical energy at one end of the device and converting back to electrical energy at the other end. The piezoelectric effect refers to the electric charge in response to pressure due to dipole formation in the crystal lattice. The effect is reversible; the inverse piezoelectric effect results in the generation of mechanical strain from an applied electric field. Voltage across the input IDT generates a current which energizes the quartz underneath the IDT fingers. Quartz is a piezoelectric material. The electrical energy is converted into mechanical energy waves due to the contraction of the
quartz. The waves travel across the quartz to the output IDT. The output IDT then converts the mechanical waves back to electrical energy, resulting in a voltage.
SAW-based processors are lightweight and versatile and have low energy consumption; therefore, they are advantageous to use in portable wireless communication devices[4].
2.3 Usage of SAW Devices as Filters
One common use of SAW devices is as filters found in appliances such as radios and cell phones.
SAW devices filter frequencies through the basic principles of wave interference. When waves are in phase across the device, they cause constructive interference and are allowed through the device. When waves are out of phase across the device, they cause destructive interference and are filtered[5]. The phase coherence depends on the frequency of the waves (or the wavelength), the distance between the IDTs and the IDT periodicity.
2.4 Quartz Crystal Microbalance
A new area of research involves using acoustic wave devices as biosensors to determine the mass of objects. In this work, this application was demonstrated using the quartz crystal microbalance (QCM). QCM is also a piezoelectric device, but uses acoustic waves propagating longitudinally rather than tranversely. The biosensors in Figure 2.2 work since QCM devices can detect changes in frequency. Using Equation 1, it is possible to determine the change in mass.
Equation 1
= 3.336x103 m/s (acoustic velocity of quartz)
= 2.648x103
(density of quartz)
= 0.2047 cm3 (area of quartz)
= change in frequency
= fundamental frequency
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This microbalance can be used to detect gas absorption as well as the interactions between the biological molecules: DNA-DNA, DNA-RNA, protein-protein, and protein-small molecules.
Figure 2.2 Microbalance with the SAW device in
the center
Biotin is used in research to test the microbalance since it is representative of biomolecules that can be measured on a microbalance[6].
Another device that can be used as a biosensor is a quartz crystal microbalance (QCM). QCMs have larger electrodes, thus better suited for finding changes in frequencies. Though not a SAW device, QCMs also utilize piezoelectricity and are a suitable replacement for measurement purposes. The major difference between the SAW device and the QCM is that the SAW device operates on transverse waves whereas the QCM operates on longitudinal waves.
2.5 Microfabrication Processes and Measurement Principles 2.5.1 Mask
Masks are tools to imprint the design of the device onto the photoresist on the aluminum conductor. The mask has a chrome pattern of the SAW device on a glass substrate as seen in Figure 2.3. A mask with defects can result in a low yield of chips[4].
Figure 2.3 Glass mask with chrome pattern
2.5.2 Photolithography and Wet Etching
Photolithography includes the process of spin coating photoresist on to the substrate. This procedure has to be done in a yellow-lit room since the photoresist reacts to UV light. The layer of photoresist applied by spin coating reacts with the concentrated UV light during exposure[7].
The process used to expose the photoresist to the light is contact printing. Contact printing involves the wafer touching the mask to allow for correct pattern transfer during exposure. Contact printing may be susceptible to dust particles on the wafer that can potentially damage the mask; therefore, proper care must be taken during the mask to substrate contact[4].
The developing stage removes the photoresist that has been exposed to UV light during exposure, leaving the unexposed photoresist to remain on the substrate. After using this resist to pattern the aluminum by wet etching, the photoresist is left on the wafer to prevent corrosion; this process is called passivation.
The etch rate of the aluminum is not only dependent on the concentration of solutes but also on the temperature of the solution, the agitation of wafers, and the impurities or alloys in the film[4].
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2.5.3 Bandwidth and Operating Frequency
The bandwidth is the optimal range of frequencies that the device will allow. Any frequency outside the bandwidth range will be unlikely to resonate in the device. The bandwidth is calculated by analyzing the frequency values three decibels (dB) down from the peak operating frequency – the mode – and finding the width of the gap as shown in Figure 2.4. The interval of 3 dB is chosen since this marks the half power point - the point at which the wave’s output power is half that of its mid-band value.
The peak operating frequency is the frequency associated with the wave that experienced the most constructive interference, as indicated by a high signal strength. More than one operating frequency can occur for each SAW filter. The resonance of the waves results in a fundamental frequency and additional harmonics, all of which can be considered as multiple peak operating frequencies.
Figure 2.4 The bandwidth of a wave between
frequency 1 and frequency 2
3 Microfabrication, Measurements, and Biosensor Application of SAW Devices
SAW devices and microbalances are fabricated through a series of detailed steps and tested.
3.1 Microfabrication of SAW Devices in Cleanroom
Microfabrication includes electron beam-physical vapor deposition, photolithography, contact printing, developing, and wet etching. This process was done for five samples.
3.1.1 Cleaning and Electron Beam-Physical Vapor Deposition
Cleaning of the quartz substrates was done using acetone and methanol [8]. Next, the wafer was rinsed with deionized water and blown dry with nitrogen which quickly evaporates any solvents or liquids on the wafer. Nitrogen is used because it does not cause the wafer to oxidize [9]. The wafer was baked to dry and remove solvents. A film of aluminum conductor was deposited on one side of the quartz wafer by electron beam physical vapor deposition [10], as shown in
Figure 3.1.. Figure 3.1 The samples of quartz substrate coated
with aluminum
3.1.2 Spin Coating
Spin coating began by placing the sample in the middle of the spinner. A few drops of photoresist (AZ 5124) were put onto the center of the aluminum layer of the quartz as seen in Figure 3.2 until the sample was covered. To ensure the purity of the photoresist, the tip of the dropper must not touch the opening of the bottle nor the sample. The substrate was then rotated at a high speed in order to spread the coating
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evenly by centrifugal force. Rotation was done for 5 seconds at 500 rpm and then subsequently for 40 seconds at 4,000 rpm. After the spinning was done, the wafer was soft baked to dry off any solvent from the spin coating, improve the adhesion of the resist to the wafer, and anneal the stresses put on the wafer during spin coating[11].
Figure 3.2 Spinner with the aluminum-coated
substrate (Sample 1) and pink photoresist (AZ 5124)
For Sample 2, an extra layer of
photoresist was applied due to a spinner error. After applying the photoresist to Sample 2, the spinner started immediately at 4,000 rpm, a higher speed than intended. As a result, the spinning was stopped and Sample 2 was reexamined; some of the photoresist was no longer on the chip. Photoresist was reapplied to Sample 2 and the correct program was used to spin Sample 2.
3.1.3 Mask and Exposure The samples were positioned on the
stage in order to maximize the number of chips on the samples. Once the shadow disappeared as the sample contacted the mask, the UV light was turned on; exposure lasted for 15 seconds.
For all samples, the shadow was examined in order to ensure the wafer was just touching the mask. As the wafer moved closer to the mask, the shadow diminished.
3.1.4 Image Developing
The sample was then soaked in a developer to remove the exposed photoresist
leaving behind the pattern as seen in Figure 3.3. The developer was AZ 1:1 and was compatible with the AZ 5214 photoresist. The amount of time in the developer varies depending on the sample, but is usually around one minute. The samples were dipped in distilled water, then removed, and then dipped once again. This method was used to ensure that all the developer was off the wafer. The wafer was then dried using high-pressure nitrogen.
Figure 3.3 Samples after developing
As seen in Table 1, the samples were
in the developing solution twice before the photoresist was removed. They had to be developed for 30 sec, dried, and developed for 30 sec again to observe the development progress. Sample 2 needed more time during the developing stage. Sample 2 was developed for 1 minute and 6 seconds, with two rounds of 30 seconds each and a third round of 6 seconds. This was likely because at the earlier spinning step, the photoresist was re-applied.
Sample Developing Time/Sequence Etching
Time
1 30 sec + rinse + 30 sec + rinse = 60 sec total
11:50
2 30 sec + rinse + 30 sec + rinse + 6 sec + rinse= 66 sec total
20:07
3 30 sec + rinse + 30 sec + rinse = 60 sec total
25:01
4 30 sec + rinse + 30 sec + rinse = 60 sec total
9:00
5 30 sec + rinse + 30 sec + rinse= 60 sec total
10:42
Table 1 Developing and etching times
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3.1.5 Aluminum Wet Etching
The final step is wet etching the aluminum. This experiment used 0.25 g KOH to oxidize the aluminum and used 0.5g K3Fe(CN)6 to dissolve the oxidized aluminum. As seen in Figure 3.4, the aluminum slowly disappears around the edges of the sample and around the patterns from the mask. The remaining photoresist was left on top of the aluminum to prevent it from corroding.
Figure 3.4 Sample 4 during the wet etching process
Each sample was in the petri dish of K3Fe(CN)6 , KOH , and DI water for anywhere from 9-26 minutes which is agitation dependent. The lab equipment used varied and some samples were given larger petri dishes of the solution than others. Each sample was placed in a dish and the solution was swirled around it to insure that all possible aluminum was dissolved. After it was dissolved the piece was carefully removed and placed into beaker of DI water for exactly 2 minutes. Then, it was air dried and placed under the microscope for observation.
3.2 Measuring SAW Devices
After the microfabrication, the devices were characterized for spectral response using the HP 8753D network analyzer as shown in Figure 3.5. An optimal device was chosen from the whole wafer by the appearance. Ideally, the electrode testing pads should have a greenish tint under the microscope, rather than pink. This green
color indicates less photoresist which produces a better signal. The two probes connecting to the network analyzer were lightly placed on the surface of the electrodes to prevent damage. Readings from two devices from each sample were taken, giving 10 sets of measurement data.
Figure 3.5 HP 8753D Network Analyzer probes on
Sample 4 device
3.3 Biotin Microbalance
Since the original fabricated SAW devices did not have enough signal strength to register frequency shifts, a QCM was used as a substitute device. The QCM was placed on the probe station to measure both frequency and amplitude. Once it was properly secured with the electrodes attached, the biotin solution was placed on the center of the device as shown in Figure 3.6. This biotin solution was pipetted in increments of 20
microliters ( using a micropipette. After each addition of biotin on the balance, the
frequency was calculated and recorded. 20 of biotin was added five times to give the final
volume of 100 on the microbalance.
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Figure 3.6 Microbalance with the biotin
4 Results and Discussion
Data collected from both the filters and the microbalance confirm that both devices were successfully executed.
4.1 Frequency Filter
The first application of the SAW device tested was the SAW filter; the functionality of the filters proved the success of the fabrication process.
4.1.1 Final Product
Observation for the different developing and etching times are explained through the procedural steps in Section 3. Samples 1, 4, and 5 had the larger petri dishes, so they could be swirled in the dish. As a result, Samples 1, 4, and 5 had shorter etching times, as seen in Table 1. The longer etching time for Sample 2 is likely due to leftover photoresist still on the device. Despite this flaw in the process of Sample 2, some of the devices on the chip were still intact when examined under the microscope. Though this decreased the yield of the devices on the chip, the devices were still functional. Sample 3’s longer etching time can be explained by the smaller petri dish since it did not allow for proper agitation.
After the final layer of aluminum was removed, the device patterns were revealed. Figure 4.1 shows the samples revealing the initial quartz substrate and the aluminum pattern.
Figure 4.1 All 5 samples after etching and
passivation
4.1.2 Microchip Data Figure A1 (see Appendix) shows the
data collected through the measurement of the SAW devices. The graph displays the amplitude of the waves with the frequencies of the waves. The amplitude of the waves indicates signal strength, meaning the higher the amplitude, the stronger the signal. The frequencies of the waves provide information to determine the bandwidths and operating frequencies of the devices.
From this graph, three main modes can be identified. The frequencies in these modes are associated with the waves that experienced constructive interference and were allowed through the SAW filter. These modes are analyzed to find the bandwidth and operating frequency of each device.
Bandwidth was calculated for one device. For this process, Sample 4 D2 was chosen since it had the largest signal strength and the least external and common noise. The bandwidths for this device were 441 MHz to 454 MHz for Mode 1 (13 MHz), 519 MHz to 540 MHz for Mode 2 (21 MHz), and 715 MHz to 731 MHz for Mode 3 (16 MHz). Only these frequencies will be allowed through the device; other frequencies will be not resonate across the device. This ability to select only certain ranges of frequencies illustrates the success of the SAW device as a filter.
From Figure A1, the operating frequencies for each device and for each mode were calculated. The operating frequencies of
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the ten devices are illustrated in Figure A2 (see Appendix). The linear trend of the data indicates the devices were consistent since the devices from the five samples had about the same operating frequency. Moreover, the average operating frequencies of the 10 devices for the three modes was calculated, as displayed in Table 2. Considering that all the devices were based off of the same pattern and all the devices had similar frequency peaks, the results demonstrated the reproducibility of the process.
Figure A3 (see Appendix) further emphasizes the success of the devices. This graph displays the peak amplitude of each of the ten devices for the three modes. For all except two devices, Mode 2 had the strongest signal strength. Mode 2 was generally the highest and Mode 1 was generally the lowest. This was an unexpected result since Mode 1, the fundamental frequency, was predicted to be the highest, followed by Mode 2 and Mode 3, the harmonics. This difference may be attributed to the design of the SAW device. Table 2 summarizes these results.
The results in Figure A3 (see Appendix) are proved to be consistent by the fact that the data shows a horizontal trend. The inconsistent data from Sample 4 were due to the probes placement accuracy on the electrodes. This, along with the low standard deviation shown in Table 2, supports the fact that the microfabrication procedure produced reliable devices on each sample.
Although all the samples were made from the same pattern, it is seen in Figure A1 that not all the data matches exactly. These differences can be attributed to a variety of factors such as probes having different contacts with the electrodes, photoresist remaining on the electrodes, misaligned fingers, interference from leftover aluminum, and external and common noise present during data collection.
Peak Frequency Mode
Average (MHz)
Standard Deviation (MHz)
1 453 3.83
2 532 2.59
3 725 3.82
Peak Amplitude Mode
Average (dB)
Standard Deviation (dB)
1 -7.768 0.182
2 -7.441 0.212
3 -7.509 0.120
Table 2 Peak amplitude and frequency averages and
standard deviations by mode
4.2 Micro Balance
The measurements from the biotin on the biosensor demonstrated that the device is sensitive to frequencies change as mass was added to the filter.
4.2.1 Micro Balance Data
Figure A4 (see Appendix) displays both the frequency and amplitude of the
waves decreasing with each 20 increment. The amplitude of the waves decreases due to a dampening effect of the extra mass while the frequency of the waves decreases due to the interference of the resonance of the waves. For Equation 1, only change in frequency is necessary to calculate change in mass.
Equation 1
This equation indicates change in mass is directly proportional to change in frequency. Figure A5 (see Appendix) was used to determine the accuracy of this equation. This graph displays the change in frequency of the device with the change in volume of biotin added to the device. Change in volume correlates with the change in mass.
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The linear trend in Figure A5 supports Equation 1 since it illustrates the proportionality of the change in mass to the change in frequency.
The data in Figure A5 shows that
from 0 to 60 of added biotin, there is a linear correlation between the mass of biotin
and the frequency of the wave. From 60 to
100 , this linear trend showed some deviation. This is due to the fact that the biosensor has a limit to the amount of mass it can measure. Once the device is mostly or fully covered with biotin, the change in frequency can no longer be detected. In addition, more accurate data comes from measuring the changes of mass of a solid rather than a liquid such as biotin since liquids dampen the resonating waves of the device.
Error in pipetting 20 amounts of biotin could also contribute to lack of linearity. Despite these issues, the data was still mostly linear.
Equation 1 was used to determine the changes in mass of the biotin added to the microbalance. Results are summarized in Table 3.
Increments
Volume (µL)
Frequency (MHz)
∆ Frequency (MHz)
∆m (kg)
0 0 9.984555 0 0
1 20 9.983879 -0.000676 0.00061
2 40 9.983294 -0.001261 0.00114
3 60 9.982738 -0.001817 0.00165
4 80 9.982525 -0.00203 0.00184
5 100 9.982176 -0.002379 0.00216
Table 3 Data and calculations extracted from the
biotin microbalance process
5 Conclusions
The fabrication of each SAW device was successful in making functional filters.
The operating frequencies of the SAW devices
were measured to be at 450 3.83 MHz,
532 2.59 MHz, and 725 3.81 MHz. This data showed that the SAW devices were able to select particular frequencies, similar to the filters used in cell phones and radios. However, since the signal strengths of the fabricated SAW devices were not strong enough, the QCM was employed as a substitute device to perform the biosensor application. The biosensor application of the QCM device worked by measuring decrease in frequency with the addition of microliter
amounts of biotin. As each 20 increment was added to the microbalance biosensor, the frequency decreased. This linear trend allowed for calculation of the mass of the biotin through Equation 1.
Future work should look to improve the SAW filters by minimizing the external and common noise present. In addition, tests need to be done to understand why the waves in Mode 1 in Figure A1 did not have the largest signal strength even though they are the fundamental frequency. For the biosensor application of the SAW device, further research into the capacity of the device should be conducted to see the limits of Equation 1’s ability to calculate change in mass. SAW devices have the potential to have a large impact in both the medical field and the solar energy industry. The success of both the fabrication and application of the SAW devices demonstrate the versatility of SAW devices and their importance to the field of nanotechnology.
Acknowledgments
We would like to thank our mentors, Dr. Pavel Reyes and Dr. Warren Lai of the Microelectronics Research Laboratory (MERL), for guiding us and letting us push the boundaries with this project. We are especially thankful for the Rutgers School of Engineering and Dean Thomas Farris for their permission to access the cleanroom facilities as well as their support. In addition, we express
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our gratitude to Robert Lorber for the cleanroom technical support. We would also like to thank The Governor’s School of Engineering and its sponsors: Rutgers, The State University of New Jersey, Morgan Stanley, NJ Resources, South Jersey Industries, PSE&G, and the GSET alumni and community. Furthermore, we would like to thank Jean Patrick Antoine, and all of the counselors for giving us this opportunity. A special thank you to Jeff Kowalski, our Residential Teaching Associate, for always being there for us and taking us to where we need to be.
References
[1] "Highly Efficient Photovoltaic Energy Conversion Using Surface Acoustic Waves in Piezoelectric Semiconductors | University of Maryland Energy Research Center." Highly Efficient Photovoltaic Energy Conversion Using Surface Acoustic Waves in Piezoelectric Semiconductors | University of Maryland Energy Research Center. N.p., n.d. Web. 24 July 2013. <http://www.umerc.umd.edu/projects/solar05>. [2] “In NASA’s Sterile Areas, Plenty of Robust Bacteria.” New York Times, 9. October 2007. [3] McFadden, Roger. "A Basic Introduction to Clean Room." Coastwide Laboratories. N.p., n.d. Web. 5 July 2013. <http://www.coastwidelabs.com/Technical%20Articles/Cleaning%20the%20Cleanroom.htm>. [4] Ng, Kwok K. “Lithography and Etching.” Semiconductor Device Technology. By Simon M. Sze. N.p.: Wiley, 2005. 404-18. Print.
[5] Coon, Allan. "SAW Filter PCB Layout." RFM. N.p., n.d. Web. 19 July 2013. <http://www.rfm.com/products/apnotes/an42.pdf>. [6] "What Is Biotin?" WiseGEEK. N.p., n.d. Web. 19 July 2013. <http://www.wisegeek.org/what-is-biotin.htm>. [7] "Photolithography." Photolithography. N.p., n.d. Web. 05 July 2013. <http://www.ece.gatech.edu/research/labs/vc/theory/photolith.html>. [8] "Cleaning Procedures for Class Substrates." UCIRvine, n.d. Web. 5 July 2013. <http://www.inrf.uci.edu/wordpress/wp-content/uploads/sop-wet-cleaning-pro-for-glass-substrates.pdf>. [9] Downie, N. A. Industrial Gases. London: Blackie Academic & Professional, 1997.Google Books. Web. 5 July 2013. [10] "Electron Beam Physical Vapour Deposition (EB-PVD)." Phoenix Scientific Industries Ltd. N.p., n.d. Web. 04 July 2013. <http://www.psiltd.co.uk/Products/DepositionSystems/ElectronBeam/tabid/238/language/en-GB/Default.aspx>. [11] "Coating Quality and Spin Coating." Materials Science and Engineering. N.p., n.d. Web. 25 July 2013.
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Appendix
Figure A1 Amplitude versus frequency for all 10 tested SAW devices
Mode 1 Mode 2 Mode 3
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Appendix A
Figure A2 Operating frequencies for the 3 modes of the 10 tested devices
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Appendix A
Figure A3 Peak amplitude for the 3 modes of the 10 tested devices
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Appendix A
Figure A4 Amplitudes versus frequencies showing decreasing trend in both as increasing increments of biotin is
added to the microbalance
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Appendix A
Figure A5 Change in frequency versus volume of added biotin
