Frequency Measurement for QCM Applications

QCM (quartz crystal monitor)

F.H. Schlereth, A.K Mahabalagiri, A. Khadeer, T. McLoed.

EECS, Dept. Syracuse University Syracuse, NY 13244

schleret@syr.edu

Abstract— It is desirable for QCM response time (time to measure a frequency change Δf ) to be as short as possible, particularly for newer applications of QCM technology such as biochemistry, environmental monitoring for explosives, intrusion detection as well as a microbalance. A new method for making high resolution, rapid frequency measurements is described. The method is applicable for uncoated or functionalized crystals, as the application demands. For a 5 MHz crystal a conservative estimation time for a Δf of 0.1 Hz is less than 1 msec.

Keywords—frequency measurement; phase lock loop;

detection; QCM;

I. INTRODUCTION The QCM (Quartz Crystal Monitor) is an instrument in wide use for mass measurement [1]. Early applications were for measurement of thickness of a deposit in semiconductor manufacture. More recently the range of applications has grown to include biochemistry, environmental monitoring, explosives detection, intrusion detection. We have been involved in QCM design and development since the early 70s. One of the authors (Schlereth) is a cofounder of Inficon [1] and led the engineering team in developing the first QCM to use a microprocessor. His colleague and co- founder, C.S. Lu, is the developer of the QCM sensor and is still actively engaged in this area.

Initially the QCM was developed for the semiconductor industry to provide a means for real time measurement of deposit thickness in the manufacture of semiconductors. Since that time applications have broadened, particularly when it was discovered that the quartz crystal would operate in liquids, as well as air, and vacuum.

Our interest is in improving response time ((time to measure a frequency change Δf ) of the QCM. This is important in broader applications, described below, and in particular, the development of new instrumentation for biochemical applications. Hence the collaboration with the Syracuse Department of Chemistry. Some of our work in this area is also described below.

It is in considering these broader applications that we developed the new approach for processing the sensor signal described in this paper.

J.T. Spencer, K.S. Sweder

Dept. of Chemistry, Syracuse University Syracuse, NY 13244 jspence@syr.edu

II Related Work

At present, the primary observable used in the QCM is frequency change of the crystal since the crystal mass is inversely proportional to the frequency change. Frequency measurements have evolved since the 1970s as follows: [2]

Stage 1 until 70s Conventional counting Stage 2 1980s reciprocal counting (period Measurement + inversion) Stage 3 1990s Interpolating Reciprocal Counting Stage 4 2000s Multiple Time Stamp Average Continuous Counting

There are other ways to measure the frequency change such as used by Inficon which “pings” the crystal and measures the response, rather than placing the crystal in an oscillator, and measuring frequency of oscillation. Another method for using the quartz crystal is to measure the dissipation of the crystal as a function of the kind and amount of the deposit. It is called QCM-D. This is a completely different phenomenon and outside our range of interest and expertise.

III Present Contribution

In this paper we describe a new way of using a QCM, based on the use of oscillator phase, rather than oscillator frequency as the primary observable. Advances in electronics technology have made this change practical. In addition, advances in coating technology have made it possible to functionalize the crystal surface, both mechanically and chemically. This, in combination with the measurement of phase, opens up many new application areas, e.g., measurement of phase jitter is a direct measure of pressure in a vacuum chamber. This measure is sensitive enough for use in high vacuum.(10-10 Torr). The measure of phase also provides a simple means to estimate frequency change in a short time (msec.), and phase accumulation is a measure of the total mass accumulation, similar to the output of presently available QCM instruments. Phase measurement has been used before, but only to make small mass measurements.

2015 International Conference on Industrial Instrumentation and Control (ICIC) College of Engineering Pune, India. May 28-30, 2015

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To wit, if

“the expected frequency shifts in QCM

served by traditional architectures. Details are omitted because of IP considerations, but the results, described next attest to the efficacy of our approach.

biosensors are very small, it could be possible to interrogate the sensor with an appropriate constant frequency signal, in the sensor resonance bandwidth, and then to measure the change in the phase response of the sensor while maintaining the frequency of the testing signal in the resonance bandwidth”. [3],

In our instrument we use a digital/analog phase lock system (PLL) with a stable, low jitter reference frequency so that we are not limited to measuring just small frequency shifts. This permits us to address the full range of QCM applications. We measure frequency change rapidly and with high resolution. .

The novelty of our new method lies in the employment of a combination of analog and digital circuits in a PLL, to measure frequency. The digital part gives high precision and the analog part avoids quantization effects in digital systems.

We have designed and tested all circuit subsystems and are currently in the process of designing coatings, refining simulations and building an instrument.

Before getting to the main topic, note that another important instrument component is the detector. In high sensitivity measurements the ultimate limit is the noise of the sensor and electronics. In some cases the statistical characteristics of the noise is not known, such as phase jitter or phase noise. Hence, an ancillary, but important, feature of the instrument is to utilize distribution-free signal processing so that the statistical properties of the results are not dependent on the probability density functions governing the noise. In the case of measurement of the instrument output (DC level of the PLL control pulses) it is safe to assume Gaussian noise.so that it is not necessary to employ distribution-free methods. Thus, given a specified confidence level and length of time for the measurement, we guarantee error and detection probabilities.

IV The Circuit

Figures 1 and 2 show a block diagram of the circuit and pertinent waveforms, respectively. The PLL circuit is different from the traditional implementation using separate VCO, phase detector, low pass filter components. It also differs from the digital PLL architectures which are currently available.

The difference in our approach is a result of the fact that the QCM application has peculiar requirements which are not

Figure 1 Block Diagram

Figure 2 Waveforms. Lines

1. time of input signal change 2. feedback signal 3. input signal 4. control signal 5. filter output

Figure 1 shows a block diagram of the circuit as modeled in Simulink. It is a phase lock loop. The reference pulses feed into a VCO which includes a feedback waveform generator. The control signal converts the reference pulses to a feedback signal suitable for comparison with the input signal. This comparison, in turn, forms the control signal, thus completing the feedback loop. Figure 2 shows pertinent waveforms. From the top, 1, shows the point at which the input waveform has changed frequency. 2, shows the change in the feedback signal. (Note the small Δ f. and that the correction takes place within a few cycles.) 3, shows the input signal and 4, the control pulses. (Note the slight shift in the average value of the

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control pulses.) This shift is reflected in 5, which shows the low pass filter output. This DC level shift is a measure of Δf. (The peaks are not displayed to emphasize the DC level change.) The time in which the loop responds to a frequency change at the input is within a few cycles of the input signal, which in real time is typically 5-6 MHz for a QCM crystal.

The frequency change for this example is 2.5%. The amplitude change, at the filter output, in the DC value of this control pulses is 4%. Unfortunately this correspondence will not be maintained as the input frequency change is reduced because of the quantization of the reference pulses. This quantization can be reduced at the expense of a higher clock rate for these pulses. For this simulation the reference clock rate is 100x the input frequency which corresponds to ~600 MHz in the actual circuit, which is easily achievable with presently available clock generators. Thus the lower limit on resolution is equal to the period of the 600 MHz clock, 1.62x10-9 sec.; equivalent to a frequency resolution in the input clock of between 0.1 to 0.2 Hz.

A higher clock rate is one way to reduce resolution, but another, which is more practical, is to introduce a dither into the amplitude of the control pulse. Either of these will improve the resolution still further; 10-fold for higher pulse rate and ~10-fold for dither.

Many factors will determine the best choice between clock rate and dither, and for now we leave this as a topic for future investigation. Other future efforts to be undertaken are described in the next section.

V Future Work and Applications

At the present time we have designed, built and tested many of the circuits needed in this instrument. One important area of further investigation is the use of a field programmable gate array (FPGA) and system on chip (SoC) technology. The potential advantages of using both technologies are numerous in the context of this application. FPGAs allow for the creation of hardware that can adhere to the strict timing requirements necessary to implement the digital portion of the PLL. The use of an SoC will allow for the more computationally intensive processing required by some components to be offloaded from the FPGA. By using the strengths of each technology, the high potential resolution of the circuit can be realized without significant custom hardware design work. A high-speed link between the two will allow for tight integration of the different components resulting in a better overall performance. The decreasing cost, size, and power requirements of both technologies will also allow for a small, inexpensive instrument to be constructed.

Another area of investigation is improved simulations. At present, it is not practical to use Simulink to investigate

possible issues involved with high speed and high resolution. [5] The simulation issue in the present context is related to the fact that we are able to make high sensitivity measurements of the behavior of molecular interactions with surfaces and each other, on a very small time scale. Another is related to the simulation of the behavior of the system for very small changes in frequency, which we are able to measure, partly because of the sensitivity of the sensor and partly because of the statistical techniques we employ in the detection process, as described above. The PLL is a complex nonlinear feedback system which is normally analyzed by making linearizing assumptions. This is not feasible for most of the applications we envision. It is necessary to iterate (perform large matrix inversions) at each time step of an experiment since system parameters are changing at each time step. This requires large computer resources and careful design of the simulation software. A third area of investigation, but not related to this paper, is the development of suitable coatings to take advantage of the new instrumentation. Applications which are being considered are high vacuum pressure measurement (10-10

Torr), explosives detection, environmental monitoring including intrusion detection, and biological instrumentation. For the latter, we believe this is the first instrument to be able to measure chemical reactions at surfaces in real time. A critical opportunity uniquely provided by the instrument is the ability to modify and functionalize the silica surface of the crystal. One is the use of nano structures to improve sensitivity for applications depending on jitter. Extensive analysis of the jitter mode shows that a single crystal sensor, with a suitable surface material, has a sensitivity of about 1 ppb, with PFA = .01, PD = 0.9 with a detection time of 1 sec. at a confidence level of 90%. The crystal is small, (3 mm diameter and 0.1 mm thickness), so that for mission critical application we could use 30 crystals, a detection time of 10 seconds and an optimized coating to achieve sensitivity in the 1 ppt range. Another is, apply coatings to allow greatly enhanced chemical sensitivity, specificity and molecular selectivity (discrimination). By preparing an array of either identically or differentially functionalized sites on the silica walls, the quartz detector system will be able to differentiate between various molecular targets and be tuned for sensitivity to a select group of reagents at exceptionally low concentrations. As the binding coefficient between a target molecule (analyte) and the functionalized silica surface increases, the detector will undergo a measurable phase shift due to the increased residence time of the target on the surface of the silica wall. Modification of the physical and electrical properties of inorganic-organic hybrid materials is well known. Very low concentrations of the analyte are expected to easily yield observable changes in the quartz crystal.

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Since the functionalization of the silica is designed to respond only to one specific or a specific class of molecules, this arrangement should provide a high degree of selectivity and discrimination between the desired analyte and other chemical species that might be present.

VI Conclusion/Comment

In this paper, the concern is whether the frequency of a waveform has changed as opposed to finding an exact value for the frequency, which would have to be traced back to an atomic clock. The method, using dither in a PLL, presented here, addresses the former and is limited only by the accuracy with which the filter output can be measured, which ultimately depends on the noise levels and the length of time used to estimate the value of the filter output voltage. This assumes the use of distribution-free statistical procedures, so noise statistics do not enter into the estimation procedure and also presupposes an agreed to value for the confidence level of the result. There’s no free lunch! On a practical level, ours is a very simple way to obtain data using a QCM when the frequency changes are very small and changing rapidly.

VII References

[1] http://www.inficon.com/Inficon [2] “New frequency counting principle improves resolution

“Staffan Johansson, M.Sc. in Applied Physics, http://www.spectracomcorp.com /Desktopmodules/Bring2Mind/DMX /Download.aspx?EntryId=446&PortalId=0

[3] Arruebo, M, Vallardes, M, and Gonzalez-Fernandez A. “Antibody-conjugated Nanoparticles for Biomedical Applications.” Journal of Nanomaterials 2009, Vol. 2009, Article ID 439389, http://dx.doi.org/10.1155/2009/439389.

[4] A FPGA-based Frequency Measurement System for High-Accuracy QCM Sensors María Dolores Valdés, Iria Villares, José Fariña, María José Moure Department of Electronic Technology University of Vigo, Spain E-mail: mvaldes@uvigo.es

[5] “Building Software for Simulation", JAMES J. NUTARO,

Oak Ridge National Laboratory Wiley, 2011

[6] “Fundamentals of the Electronic Counters”, Application Note 200 Electronic Counter Series http://www.leapsecond.com/pdf/an200.pdf

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