A Micromachined Quartz Resonator Array for ... - IEEE Xplore

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JOURNAL OF MICROELECTROMECHANICAL SYSTEMS, VOL. 18, NO. 3, JUNE 2009

A Micromachined Quartz Resonator Array for Biosensing Applications Ping Kao, Steffen Doerner, Member, IEEE, Thomas Schneider, David Allara, Peter Hauptmann, and Srinivas Tadigadapa, Member, IEEE

Abstract—An 8-pixel micromachined quartz crystal resonator array with a fundamental resonance frequency of 66 MHz has been designed, fabricated, and tested. A compact impedancespectrum-analyzer electronic interface has been developed and combined with the quartz resonator array to form the biosensing system. The sensor array was calibrated using water–glycerol solutions, and the performance was found to be exactly as expected. Measurement of the crosstalk between the sensor pixels showed an isolation of ∼30 dB. Selective functionalization of the pixels was achieved through the use of aqueous 3, 3 -Dithiobis (sulfosuccinimidylpropionate) (DTSSP) molecules. The adsorption of avidin on DTSSP gave a frequency signal of 60 kHz in comparison to unfunctionalized pixels. The specific adsorption of avidin on functionalized pixels was confirmed through fluorescence microscopy. Comparing the performance of the micromachined quartz crystal microbalance (QCM) with a commercial 5-MHz device, we found that the micromachined QCM has a 4.25 times higher signalto-noise ratio. Based on the measurement of the noise and using three times the frequency noise as the limit for the detection of avidin molecules, we expect to resolve a minimum of ∼1/960 of a monolayer of avidin corresponding to an aerial mass density resolution of 0.7 ng/cm2 . [2008-0196] Index Terms—Biosensor array, impedance spectrum analyzer, quartz crystal microbalance (QCM), quartz micromachining.

I. I NTRODUCTION

T

HE NEED for low-cost fast easy-to-use analytical systems for biochemical sensing has been steadily growing, primarily driven by health care, security, and environmental monitoring needs. Such sensor systems consist of four main Manuscript received August 11, 2008; revised February 4, 2009. First published April 7, 2009; current version published June 3, 2009. This work was supported in part by the NSF funded PSU Center for Nanoscale Science under Grant MRSEC DMR-0080019. The work of S. Tadigadapa was supported by an Alexander von Humboldt Fellowship. Subject Editor A. J. Ricco. P. Kao and S. Tadigadapa are with the Department of Electrical Engineering, Pennsylvania State University, University Park, PA 16802 USA (e-mail: [email protected]; [email protected]). S. Doerner is with Otto-von-Guericke-University Magdeburg, TEPROSA, 39016 Magdeburg, Germany (e-mail: [email protected]). T. Schneider is with the Department of Electrical Engineering and Information Technology and the Institute of Micro and Sensor Systems, Otto-vonGuericke-University Magdeburg, 39016 Magdeburg, Germany (e-mail: [email protected]). D. Allara is with the Department of Chemistry and the Materials Research Institute, Pennsylvania State University, University Park, PA 16802 USA (e-mail: [email protected]). P. Hauptmann is with the Institute of Micro and Sensor Systems, Ottovon-Guericke-University Magdeburg, 39016 Magdeburg, Germany, and also with the Institute for Automation and Communication, 39106 Magdeburg, Germany (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JMEMS.2009.2015498

components: 1) transducer; 2) biochemical recognition layer/ material; 3) signal conditioning and signal processing electronics; and 4) signal interpretation algorithms. Gravimetric sensors offer the possibility of high-sensitivity label-free detection for chemical and biochemical sensing. Fig. 1 shows a schematic representation of such a biosensor. The transducer element in such sensors consists of high-sensitivity mass detectors, typically, a cantilever structure or a piezoelectric resonator [1], [2]. Recent advances in micro- and nanoscale fabrication techniques have shown that, in properly designed systems, it is possible to measure mass into the 10−21 gram (zeptograms) range, allowing the possibility of single atom/molecule detection [3], [4]. (Bio)chemical sensing is typically achieved by the use of a functional layer atop the mass sensing element which essentially provides the molecular hooks or active sites for the specific analytes of interest. Current research and development on high-sensitivity gravimetric sensors are primarily focused upon micromachined cantilever designs. These sensors detect the attachment of mass either through a change in the resonance frequency or through a change in static deflection resulting from the attachment of the molecules and are measured using impedance or optical techniques [5], [6]. Recent advances in micromachining techniques have also led to the miniaturization of quartz crystal microbalances (QCMs) which now allow for the measurement of absolute mass in the subfemtogram range [7]–[10]. Unlike the cantilever-based flexural-mode resonator gravimetric arrays which are heavily damped in liquid environment, the inverted-mesa-design-based QCM arrays have the advantage that the shear-mode resonance shows considerably reduced damping effects and the planar surface of the array is readily compatible with biofunctionalization and liquid testing [10], [11]. This allows for greater versatility in the functionalization of the individual sensor pixels as well as the possibility to integrate simple polydimethylsiloxane (PDMS)-based microfluidic channels and reaction chambers on the sensor array. In contrast, micro/nanoscale cantilever sensors are quite cumbersome to functionalize, and most detection techniques using optical techniques are harder to integrate at the chip level [12]. Although micromachined quartz resonator arrays have been fabricated by several researchers [13], [14], the detailed performance of high-frequency resonators in liquid ambient for biochemical sensing applications have not been reported. The most detailed reports of the performance of single and arrays of QCM are in the 20–30-MHz region [11], [13], [15] and, more recently, on 62-MHz single resonators from our group [10]. In this paper, we report the design and performance

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KAO et al.: MICROMACHINED QUARTZ RESONATOR ARRAY FOR BIOSENSING APPLICATIONS

Fig. 1.

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Schematic representation of a gravimetric (bio)chemical sensor.

of a 64-MHz bulk-acoustic-wave quartz resonator array for biochemical sensing applications. We have interfaced the sensor array with a fast portable impedance-spectrum-analyzer interface and simultaneously recorded the response of three or four sensor pixels under various loading conditions. Through selective functionalization of pixels, we clearly demonstrate the response of the sensing array and its potential for multianalyte biochemical sensing using a bioaffinity-based sensing mechanism at a microliter analyte volume. II. QCM A typical commercial QCM consists of a ∼333-μm-thick and ∼25-mm-diameter disk made from an AT-cut quartz crystal with gold electrodes on each face, has a shear resonance frequency in the 5-MHz range, and exhibits a sensitivity of ∼17 ng · cm−2 · Hz−1 . While thinner crystals are increasingly available, the mechanical fragility of the quartz crystals has limited the widespread use of crystals with a maximum fundamental resonance frequency of ∼10 MHz.1 Under the conditions that the adsorbed film material is: 1) rigid; 2) sufficiently thin compared to the quartz crystal; and 3) attached to the sensor surface under a no-slip condition, the dependence of the frequency change (Δf ) of a resonating quartz crystal to the mass loading (Δm) is given quite accurately by the Sauerbrey equation Δm √ Δf = − 2f02 / μq ρq A

(1)

where f0 is the fundamental resonant frequency with no attached mass, μq is the shear modulus of the quartz (2.947 × 1010 N · m−2 for AT-cut quartz), ρq is the density of quartz (2.648 × 103 kg · m−3 ), and A is the area of the electrode on the quartz crystal. The negative sign indicates a reduction in the resonance frequency upon mass loading. A very important aspect of (1) is that the change in frequency (Δf ) for the same absolute mass loading (Δm) increases as the square of the decrease in the thickness and inversely as the area of the resonator. This provides a possible way of making large enhancements in the performance of quartz crystal resonators if methods of fabrication can be developed to miniaturize them. The remainder of this paper describes the design, fabrication, and performance of ∼25-μm-thick (62–64 MHz) quartz resonator arrays that 1 The 9–10-MHz quartz resonators are commercially available from Maxtek, Inc. (a division of Inficon), and 27-MHz resonators are commercially available from Initium, Inc. (a division of Ulvac).

Fig. 2. (a) Photograph of the as-fabricated QCM array with eight resonators per chip. Inset shows the zoomed view of one of the pixels. Packaged device: (b) view through the hole machined in the ceramic DIP package and (c) view from the back side showing individual wire bonds to the eight resonators.

have been interfaced with a four-channel multiplexed compact impedance analyzer for biochemical sensing applications. III. D EVICE F ABRICATION The detailed fabrication process for a micromachined quartz resonator is described elsewhere [10]. Briefly, circular resonator areas with a diameter of 1 mm and thickness of ∼25 μm were etched out of mirror-polished 100-μm-thick AT-cut quartz substrates obtained from a commercial vendor (Boston PiezoOptics, Inc., Bellingham, MA). An inductively coupled plasma reactive ion etch process was used for quartz etching [16], [17]. The process uses a mixture of SF6 and Ar as the etching gases. Mirror finish with an average surface roughness less than 2 nm was achieved after an etch depth of 75 μm. A patterned nickel hard mask layer was deposited by electroplating. The quartz crystal was thereafter etched for ∼3.5 h. High selectivity (∼10 : 1) for Ni mask:quartz and high quartz etch rates (∼0.4 μm/min) were achieved using the etching process [16], [18]. This was followed by stripping the hard nickel mask in aqua regia. A 10/100-nm Cr/Au bottom-side electrode was patterned using Shipley 1805 positive photoresist and wet etching. The 1805 photoresist provided good lithographic pattern definition in spite of the large topographic variations. Finally, the topside electrodes were aligned and patterned using lift-off to complete the QCM array. Fig. 2(a) shows an optical picture of the 8-sensor-pixel packaged QCM microarray. The diameter of the etched area is 1 mm with an electrode diameter of 0.5 mm. A 5 × 5 mm2 square hole was machined in a 24-pin dual-in-line ceramic package (DIP). The flat (unetched) side

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Fig. 3. Basic working principle of impedance-spectrum-analyzer electronics.

of the resonator array having the common electrode where the mass sensing experiments were performed was placed facing the machined hole in the package [Fig. 2(b)] and attached using a room-temperature-vulcanized silicone elastomer adhesive. The common front-side electrode was electrically connected to the gold layer on the package using silver epoxy and wire bonded to one of the pads while the individual backside electrodes of each resonator were directly wire bonded to various pads in the package [Fig. 2(c)]. IV. S ENSOR I NTERFACE E LECTRONICS In this paper, we have developed the interface electronics based on frequency-domain impedance spectroscopy. With the design of a customized multiplexer stage, a single impedanceanalyzer module can be used to assay a complete sensor array. The corresponding resonance frequencies are properly extracted from the real part maxima of measured admittance spectra in the vicinity of the fundamental resonance. Frequency-domain methods commonly utilize analog techniques, like ac-coupled bridges or correlation frequency response analyzers [19]. The measurement signals are then converted from analog to digital. Required low-pass filters or averages limit the measurement rate through their inherent settling time [20], [21]. Since each frequency needs to be applied individually to the device under test, these methods may become time consuming particularly when acquiring spectra with a large number of frequencies. To overcome these restrictions, we introduced the direct sampling technique (DST) [22]. The aim of this method was to avoid analog-signal handling at the earliest possible step and, hence, to reduce overall noise and distortion. Fig. 3 shows the working principle of the developed impedance-analyzer electronics. A frequency sweep generator provides the source signal VS for powering the impedance probe. The resulting voltage signals V1 and V2 correlate to the sensor’s impedance. With DST, both voltages are converted from analog to digital directly after the input amplifier stage. Subsequent analysis is done with pure digital-signal processing. Different mathematical algorithms are used to obtain a set of voltage ratios from the sampled pairs of sine waveforms and to calculate the calibrated impedance spectrum. The analyzer shown schematically in Fig. 4(a) consists of different stages for signal generation, signal detection, data evaluation, and process control. The sensor module itself pro-

vides adequate interconnectivity between sensor electronics and the sensor. By separating the sensor module from sensor electronics, we gain advantages compared with the previous implementations. This separation allows the individual adaptation of driver and input stages for any sensor application based on impedance spectroscopy. For the signal-generation stage, a direct digital synthesizer is used to generate the frequency-swept sinusoidal signal that powers the sensor array. The resonator impedance is determined from the complex voltage ratio of the sensor response voltage in channel B to the reference voltage in channel A. To measure the magnitude and phase of these complex voltages for the signal detection stage, DST is used to replace analog signal processing by digital signal processing at the earliest possible processing step. Subsequent digital signal analysis is done with sine-wave fitting that has been implemented in a field-programmable gate array [23]. Separate mathematical algorithms are used to obtain a set of voltage ratios from the sampled pairs of voltages and to calculate the calibrated impedance spectrum as well as the liquid-dependent resonant-frequency shift. These calculations are done by the data evaluation stage consisting of an embedded microcontroller with a powerful SC520 AMD processor core. For a measurement based on the voltage divider principle, the multiplexed sensor module (Fig. 5) is made up of two wideband switches (500-MHz bandwidth) with low on-resistances of 5 Ω. The separation between the impedance transforming input stage and analyzer enables the use of longer coaxial cables without affecting the sensor resonance behavior. In our measurement configuration, we implemented a four-channel input stage. However, an extension up to 16 channels or more would be easy to achieve. The major specifications for the developed impedance spectrum analyzer are shown in Table I. The developed high-speed digital signal processing unit delivers a very high measurement rate. Currently, acquiring a spectrum with 200 frequency points takes less than 200 ms. In terms of the used sensor array, it means that four resonators can be measured in about 0.8 s which includes the switching delay time. Unlike commercial network analyzers, the main advantages of the developed compact impedance analyzer are its speed, portability, and conformity to data-exchange standards while still offering comparable accuracy. The noise behavior of the developed analyzer has been tested in a wide impedance range and compared with that of the commercial network analyzer from Agilent, Inc. (4395A). The standard deviation for 1000 impedance spectra measurements showed no significant differences for the curve progression and for the minimum and maximum levels [23]. Fig. 4(b) shows a photograph of the developed impedance analyzer. Table I summarizes the impedance-spectrum-analyzer specifications. V. P ERFORMANCE OF THE Q UARTZ R ESONATOR A RRAY A. Admittance Characteristics Fig. 6 shows the at-resonance admittance (Y ) curve for one of the pixels in air. The fabricated pixels show the expected admittance circle characteristic from which the motional resistance can be calculated to be ∼49 Ω. The series resonance frequency for the pixel is 66.062639 MHz. Table II lists the


Fig. 4.

(a) Schematic diagram of the impedance-spectrum-analyzer electronics. (b) Photograph of the impedance spectrum analyzer.

Fig. 5.

Schematic diagram of the sensor module with multiplexer circuit.

TABLE I SPECIFICATIONS SUMMARY OF THE IMPEDANCE SPECTRUM ANALYZER

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Fig. 6. Admittance characteristics of the QCM in air for one of the pixels. TABLE II SUMMARY OF THE TYPICAL RESONANCE PARAMETERS OF THE M ICROMACHINED R ESONATOR

typical resonance parameters obtained for the micromachined quartz resonators. B. Water–Glycerol Calibration Experiments To evaluate the suitability of the micromachined resonator array for biochemical diagnostics which are typically performed under liquid loading conditions, the operation of the QCM was carefully investigated using water–glycerol mixtures of various concentrations. Water and glycerol are miscible liquids with pure-form densities of 0.99821 and 1.2613 g · cm−3 and viscosities of 1.0 and 1499 mPa · s at 20 ◦ C, respectively. The

behavior of the QCM under viscous (liquid) loading conditions is modified and is governed by [24] 3 ηL ρL (2) Δf = −f02 πμQ ρQ where f0 is the resonance frequency, ηL is the viscosity of liquid, ρL is the density of liquid, μQ is the shear modulus of quartz, and ρQ is the density of quartz. The frequency decrease is linearly proportional to the square root of the viscosity–density product of the liquid loading atop the QCM electrode surface. Fig. 7 shows the frequency change for four sensor pixels measured simultaneously as different concentrations of water–glycerol mixtures were added onto the sensor surface. The results clearly show the expected linear

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Fig. 7. Shows the expected linear dependence of the frequency change as a function of the square root of the liquid viscosity–density product for the 4 pixels.

dependence for the QCM frequency change with the square root of the liquid density–viscosity product. Furthermore, the liquid loading calibration shows a very close agreement to the expected sensitivity for all the 4 pixels. This is in contrast to our earlier reported observation of 1/5 of the expected sensitivity [10]. By modifying the sensor array packaging process and carefully removing any thermal stresses generated during the packaging process, we have been able to achieve this improvement in the observed sensitivity. C. Crosstalk Measurement In order to measure the crosstalk between the pixels, the impedance spectrum analyzer was programmed to scan a narrow band of frequency spanning the resonance frequency of the resonators. An HP-4395A spectrum analyzer was used to measure the signal strength when connected directly to the pixel being driven and at the nearby pixels on the sensor array as shown schematically in Fig. 8(a). The experiment was performed in both air and water ambient to observe any influence arising due to the presence of the analyte liquid. The measurement of the direct output of the signal generator gave a signal output of 88 dBm against the output from one of the neighboring pixels of ∼58 dBm [Fig. 8(b)]. This gives an isolation of ∼30 dB at 62-MHz frequency in both air and water environment conditions. VI. S ELECTIVE F UNCTIONALIZATION OF P IXELS FOR B IOSENSING A PPLICATIONS A. SAMs as Functionalization Layers To demonstrate the effectiveness of the QCM array for biosensing applications, three of the 8 pixels were selectively functionalized with octadecanethiol (ODT) self-assembled monolayers (SAMs). To do this, the QCM array chip was carefully cleaned in methanol and in dilute (20 : 1) piranha solution and was carefully immersed in 1-mM ODT solution in methanol for 4 h. In this method of functionalization, only the 3 pixels to be functionalized were carefully immersed below

Fig. 8. (a) Schematic representation of the setup used to measure the crosstalk between the QCM array pixels. (b) The result of the measurement when the spectrum analyzer is connected directly to the signal generator and when it is connected to a nearby pixel in an isolation of ∼30 dB both in air and water ambient.

the ODT liquid meniscus level, and no protective layer was used to cover the rest of the pixels. Extreme care was taken so that only three of the pixels were actually in contact with the ODT solution. However, a narrow gap between the quartz array chip and the ceramic package resulted in the ODT solution spreading around the periphery of the entire QCM array due to capillary forces. Therefore, a partial vapor phase functionalization of the remaining 5 pixels is also expected. After the SAM formation step on the top gold electrode, the QCM array was carefully rinsed in ethanol and dried in nitrogen. Of the 8 pixels, two unfunctionalized pixels and one functionalized pixel were connected to the electronic interface, and bovine serum albumin (BSA) dissolved in phosphate buffer solution (PBS) was placed on the QCM array. Only one resonator pixel showed a frequency decrease of 460 Hz; the other two unfunctionalized resonators showed no shift in frequency after injecting the BSA solution [25]. This result is consistent with the expectation that, in comparison with bare gold surfaces, the hydrophobic methyl termination of ODT makes it a more preferable site for BSA adsorption. However, the total frequency shift upon BSA adsorption is much less than the expected value which we believe is due to the relatively poor quality of the ODT layer formed on the gold electrode. B. DTSSP Functionalization Scheme A new aqueous functionalization scheme based upon 3,3 -Dithiobis (sulfosuccinimidylpropionate) (DTSSP) (Pierce


Biotechnology) was used to realize the selective biofunctionalization of desired QCM pixels, using photoresist as the mask for the remaining pixels. The DTSSP molecule has an amine-reactive N-hydroxysulfosuccinimide (sulfo-NHS) ester at each end of an eight-carbon alkyl chain [26]. The cleavable disulfide bond is used as an anchor for binding molecules to the gold surface. Once the molecule has cleaved at the disulfide bond and attached to a gold surface, there is only a three-cabon alkyl chain between the sulfur attachment and the NHS ester at the free end. Avidins with several primary amines in the side chain are available as target for reacting with sulfo-NHS esters at pH 7–9 to form stable amide bonds. Avidin and biotin (5fluorescein) conjugates from Sigma Aldrich were used in this work. A 6.5-mM DTSSP solution, a 1-mg/mL avidin solution, and a 1-mg/mL biotin solution were made in the PBS solution. The micromachined QCM array was thoroughly cleaned by three cycles of exposure to UV ozone, each 30 min long, followed by thorough rinsing with ethanol and immersion in ethanol for 1 h. From our earlier work on gold surfaces, we have established this cleaning protocol to be very effective for adsorbing high-quality and uniform SAMs [27]. Shipley 1827 photoresist was directly used to block specific QCM array pixel electrodes and allowed to cure at room temperature and then at 80 ◦ C for 15 min. The entire front-side electrodes were thereafter immersed in DTSSP (aqueous) solution for 16 h. In order to remove any nonspecific physically adsorbed DTSSP, the QCM array was rinsed using PBS solution. The front-side of the entire QCM array was thereafter thoroughly cleaned by washing with acetone and pure ethanol. This step completely removed the photoresist from the previously photoresist-blocked pixels of the QCM without adversely affecting the DTSSP functionalized pixels. Finally, the QCM array surface was rinsed in PBS solution and then gently dried under a filtered nitrogen stream. The frequency of the functionalized QCM was found to be 24.08 kHz lower than that measured in air prior to DTSSP functionalization and clearly indicated mass loading. The observed frequency decrease implies a DTSSP surface density of 8 × 10−9 mol/cm2 which is approximately ten times larger than expected from the ideal thiol surface packing density calculations. Previous reports have established that deposited gold films can have a larger effective area than the geometric area due to the surface roughness factor [28]–[30] which can easily result in multilayer formation. This can account for two to five times larger adsorption of DTSSP molecules. Furthermore, it is also possible that the phosphate salts left behind from the PBS buffer were incompletely rinsed away by acetone and ethanol, since these salts are poorly soluble in the solvents used and can also account for the larger-than-expected frequency shift. Three of the pixels were connected to the impedanceanalyzer interface for real-time multiplexed resonator measurement. The entire QCM array with the front end of the interface electronics was placed in a temperature-controlled box with the temperature set at 23(±0.1) ◦ C. The impedance-analyzer interface was carefully calibrated by using open, short, and 100-Ω standard loads in the frequency range of interest. The QCM array was allowed to stabilize in air for 30 min to a constant frequency. Thereafter, a ∼15-μL drop of avidin solution was delivered on the QCM array top electrode surface. Fig. 9 shows

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Fig. 9. The frequency shift upon adsorption of avidin on (green) DTSSP functionalized pixel as opposed to the (red and blue) unfunctionalized QCM pixels.

the real-time frequency change upon the adsorption of avidin on one DTSSP functionalized pixel and two unfunctionalized pixels. From the graph, a frequency change of 41.4 kHz due to the presence of avidin solution on the unfunctionalized sensor pixels and 76.40 kHz for the functionalized pixel upon adsorption of avidin is observed. The Q-factor of the resonator adsorbing the avidin film was found to decrease to ∼12 700 from a value of ∼24 700 in air. With respect to the air baseline, the frequency shift for the functionalized pixel is the sum of the frequency shift due to DTSSP, the viscous loading from the PBS overlayer, and the adsorption of avidin. The ∼41-kHz frequency shift due to the PBS/avidin solution loading on the unfunctionalized pixels implies that the (ηL ρL )0.5 for the avidin solution is ∼19% higher than that of pure water—corresponding to a ∼15% glycerol–water solution from the calibration curve shown in Fig. 7. We can calculate the frequency shift due to the adsorption of the avidin layer on the DTSSP functionalized pixel using the multilayer viscoelastic/ viscous loading model [31]. Using the density–viscosity value of the supernatant liquid equal to that of water and the density of the avidin layer which is 1161 kg · m−3 and fitting the values of the storage and loss moduli to match the observed frequency change of ∼ −76 kHz and Q-factor decrease of ∼12 000 upon avidin adsorption, the storage and loss modulus values for avidin are calculated to be 7.70 × 104 and ∼1.88 × 105 N · m−2 , respectively. The calculated values of avidin storage and loss modulii show that the avidin film is stiffer and exhibits less loss in comparison with Mefp1 protein reported in literature [31]. To obtain an agreement with the observed frequency and Q-factor change, the effective hydrodynamic thickness of the avidin film was assumed to be 32 nm or approximately six monolayers. The larger-than-expected frequency change and the effective hydrodynamic thickness of the avidin film is consistent with the approximately ten times larger frequency change observed upon adsorption of DTSSP. In a separate set of experiments, we functionalized the surface of the micromachined QCM with solvent-based Dithiobis(sulfosuccinimidylpropionate) (DSP). We have performed extensive tests on evaporated gold samples functionalized with DSP and have verified the growth of very high quality monolayers of DSP using ellipsometry. For this functionalization

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Fig. 10. (a) Fluorescence image of a QCM pixel not functionalized with avidin shows no attachment of biotin to the pixel electrode. (b) Bright fluorescent spots of FITC label attached to biotin are clearly seen on the functionalized pixel.

we obtained a frequency change of −3.803 kHz upon avidin adsorption. This change in frequency is ∼9.2 times smaller than that obtained using DTSSP based functionalization in this work [32]. However, this method is not compatible with the photoresist-based selective functionalization of the QCM pixels in the array. In order to confirm that the observed frequency shift was indeed arising due to avidin adsorption on DTSSP, the QCM array was thereafter carefully washed in PBS solution. A fluoresceinisothiocyanate (FITC)-labeled biotin-molecule-containing solution was added atop the QCM surface. After 10 min of exposure, the QCM chip was thoroughly rinsed in PBS solution and then blow dried in filtered nitrogen. The QCM top electrodes were then observed under an Olympus BX61epifluorescence microscope with FITC/RSGFP/Bodipy/Fluo 3/DiO Filter Cube. Fig. 10 shows the fluorescence images of the unfunctionalized [Fig. 10(a)] and functionalized [Fig. 10(b)] pixels which clearly show the binding of biotin to the avidin on the functionalized pixel.

Next, we compare the performance of the 66-MHz micromachined QCM array with respect to a commercial 5-MHz QCM under identical loading conditions. Under viscous loading conditions, the resolution of a QCM is given as [33] QCMResolution-Liquid

VII. C ONCLUSION In summary, the performance of a 66-MHz micromachined QCM array has been studied. Through this paper, we have clearly established the interference-free simultaneous operation of four closely located individual QCM pixels. Using a DTSSPbased electrode functionalization procedure, we were able to selectively adsorb avidin on only selected pixels and were clearly able to distinguish the response of the functionalized and unfunctionalized pixels. This is expected to open the pathway for multianalyte biochemical sensing on the QCM array platform. It is interesting to note that the penetration depth of the 66-MHz resonator is ∼50 nm as opposed to 250 nm for the 5-MHz resonator. This implies that the miniaturized resonator is highly sensitive to the interfacial phenomenon to the properties of the adsorbed films. To conclude, the micromachined QCM array promises to be a very versatile biosensor for the development of next-generation biochemical sensors for clinical diagnostic instrumentation.

ACKNOWLEDGMENT

C. Comparison With Commercial QCM

√ ρL ηL = 5700 √ pg/cm2 . f0

higher than that of the commercial QCM. This value of signalto-noise-ratio enhancement for the micromachined QCM is close to the expected value of ∼3.6. The observed discrepancy can be attributed to the possible differences (imperfections) in the avidin adsorption between the two sensors. Based on the measurement of the noise and using three times the frequency noise as the limit for detection of avidin molecules, we expect to resolve a minimum of ∼1/960 of a monolayer of avidin corresponding to an aerial mass density resolution of 0.7 ng/cm2 . For the same experiment, the 5-MHz commercial QCM resulted in an aerial mass density resolution of 3 ng/cm2 .

The authors would like to thank Dr. U. Hempel and A. Lawitzke at the Institute of Micro and Sensor Systems for their assistance. The use of facilities at the Pennsylvania State University Site of the National Science Foundation National Nanotechnology Infrastructure Network under Agreement 0335765 is acknowledged.

(3)

From this expression, it is quite clear that a higher frequency resonator is likely to provide a higher resolution (signal-to1/2 noise ratio) that is inversely proportional to f0 . In this case, we expect a sensitivity enhancement of ∼(66/5)1/2 = ∼ 3.6 times. Under PBS loading conditions, we measured the frequency noise (defined as the standard deviation of frequency fluctuation) for the commercial QCM over a period of 100 s and obtained a value of 0.1 Hz, whereas for the micromachined QCM under identical conditions, the noise was found to be 1.3 Hz. The signal obtained for avidin adsorption on the DTSSP functionalized QCM gave a Δf = −73 Hz (i.e., S/N = 730) for the commercial QCM, whereas for the micromachined QCM, we obtained a Δf = −3.8 kHz (i.e., S/N = 2877). From these measurements, we found that the micromachined QCM has a signal-to-noise ratio that is 4.25 times

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Ping Kao received the M.S. degree in materials science from the Pennsylvania State University, University Park, in 2007, where he is currently working toward the Ph.D. degree in the Department of Electrical Engineering. His research focuses on the application of micromachined quartz resonator arrays and surfaceenhanced Raman spectroscopy for biochemical sensing.

Steffen Doerner (S’05–M’08) received the Diploma degree in electrical engineering and the Ph.D. degree from Otto-von-Guericke-University Magdeburg, Magdeburg, Germany, in 2008. He is with Otto-von-Guericke-University Magdeburg, where he was with the Institute of Micro and Sensor Systems working on acoustic and dielectric spectroscopy and where he is currently the Head of the research and development group for the TEPROSA technology platform. From 1996 to 2002, he was also working with the research and development group of a leading process instrumentation company, focusing on the design of ultrasound sensor systems for the in situ characterization of fluids. His research interests include modeling and design of miniaturized acoustic and impedimetric sensors, analog and digital sensor interface design, and the development of sensor systems for process instrumentation and industrial applications.

Thomas Schneider received the degree in electrical engineering from Otto-von-Guericke-University, Magdeburg, Germany. Since 2003, he has been a member of the Micro and Sensor Systems group of Prof. Hauptmann with the Department of Electrical Engineering and Information Technology, Otto-von-Guericke-University Magdeburg, where he is also with the Institute of Micro and Sensor Systems. He is working in the field of sensor interface electronics for resonant and capacitive sensors.

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David Allara received the B.S. degree from the University of California, Berkeley, in 1959, and the Ph.D. degree from the University of California, Los Angeles, in 1964. Between 1965 and 1969, he was a National Science Foundation Postdoctoral Fellow at Oxford University, Oxford, U.K., a Postdoctoral Associate and, subsequently, a Staff Scientist with Stanford Research Institute, and an Associate Professor of chemistry at San Francisco State University, San Francisco, CA. In 1970, he joined Bell Telephone Laboratories, Murray Hill, NJ, as a Technical Staff Member and was appointed as a Distinguished Member of Technical Staff in 1984. He currently holds a joint appointment as a Professor of chemistry and a Professor of materials science and engineering with the Department of Chemistry and the Materials Research Institute, Pennsylvania State University, University Park. In the commercial sector, he is a Cofounder of three start-up technology companies, serves on scientific boards of two other companies, and is an active consultant in technology areas ranging across biosensors, energy conversion, and nanotechnology. Over the years, his interests have included polymer interfaces and thin films and gas-phase kinetics of systems, including atmospheric chemistry, pyrolysis and combustion, and surface spectroscopy, but his primary research for the past two decades has been in the area of molecular surface chemistry and surface and thin-film characterization.

Peter Hauptmann received the Ph.D. and State Doctorate degrees from the Technical University Leuna-Merseburg, Magdeburg, Germany, in 1973 and 1979, respectively. He is a Professor and the Head of the Institute of Micro and Sensor Systems, Otto-von-GuerickeUniversity Magdeburg, Magdeburg, Germany. He is a Board Member of the Institute for Automation and Communication, Magdeburg, as well as a Consultant to industrial and governmental organizations in Germany and abroad. He is the Editor-in-Chief of the journal Measurement Science and Technology (IOP, U.K.). In 1985, he was appointed as a Full Professor with the Technical University Magdeburg. He is the author or coauthor of about 400 papers and seven books. He has extensive experience in ultrasonic sensors and ultrasonic systems, resonant chemical, biological, and mechanical sensors, sensor modeling, microsensors, new sensor materials, sensor interface electronics, and industrial sensor applications. He has been responsible for numerous successfully realized technology transfer projects.


Srinivas Tadigadapa (M’00) received the M.S. degree from the Indian Institute of Technology, Chennai, India, and the Ph.D. degree from the University of Cambridge, Cambridge, U.K., in 1994. He is an Associate Professor in the Department of Electrical Engineering, Pennsylvania State University, University Park. From 1996 to 2000, he was Vice President of Manufacturing of Integrated Sensing Systems, Inc. and was involved with the design, fabrication, packaging, reliability, and manufacturing of silicon microsystems. He was a Research Fellow with the University of Karlsruhe, Karlsruhe, Germany, and Visiting Faculty at Otto-von-Guericke-University, Magdeburg, Germany, and University College, Cork, Ireland. He serves on the Editorial Board of the Journal of Micro/Nanolithography, MEMS, and MOEMS and Measurement Science and Technology. His research interests include microsystems and exploring phenomenon at the micro–nano interface. Dr. Tadigadapa was the recipient of an Alexander von Humboldt Fellowship in Germany and the Walton Fellowship in Ireland.