Quartz Crystal Microbalance (QCM) is one of the many acoustic transducers. It is the most popular and widely used acoustic transducer for sensor applications. It has found wide applications in chemical and biosensing fields owing to its high sensitivity, robustness, small sized-design, and ease of integration with electronic measurement systems. However, it is necessary to coat QCM with a sensing film. Without coating materials, its selectivity and sensitivity are not obtained. At present, this is not an issue, mainly due to the advancement of oscillator circuits and dedicated measurement circuits. Since a new researcher may seek to understand QCM sensors, we provide an overview of QCM from its fundamental knowledge. Then, we explain some of the recent QCM applications both in gas-phase and liquid-phase. Next, the theory of QCM is introduced by using piezoelectric stress equations and the Mason equivalent circuit, which explains how the QCM behavior is obtained. Then, the conventional equations that govern QCM behaviors in terms of resonant frequency and resistance are described. We show the behavior of QCM with a viscous film based on the acoustic wave equation and Mason equivalent circuit. Then, we present various existing QCM electronic measurement methods. Furthermore, we describe the experiment on QCM with viscous loading and its interpretation based on the Mason equivalent circuit. Lastly, we review some theoretical models to describe QCM behavior with various models.

We have developed a system to obtain both the resonance frequency and resistance from a Quartz Crystal Microbalance(QCM) using a portable vector network analyzer (VNWA). Acoustic loading on a QCM causes a change in admittance,which can be measured by a VNWA. For application as an odor sensor, it is necessary to coat the QCM with a sensing film. Since many sensing films are highly viscous, the noise level is high owing to viscous damping. Thus, we propose a curve fitting method by utilizes all the datapoints within a certain frequency range to obtain the resonance frequency. The scan frequency range, the number of datapoints and the measurement time per datapoint are optimized to achieve minimum noise. Then, the data after curve fitting are applied to a Savitzky–Golay filter with a polynomial approximation within the moving window to further smooth the temporal frequency data, while maintaining the sharpness of the sensor response. All the entire process can be carried out in real time. The Savitzky–Golay filter was found to be able to suppress noise after the optimization of window size optimization. The effectiveness of the system was confirmed by performing an independent t-test.

In odor sensing based on Quartz Crystal Microbalances (QCMs), the sensing film is crucial for both sensor sensitivity and selectivity. The typical response of the QCM due to sorption is a negative frequency shift. However, in some cases, the sorption causes a positive frequency shift, and then, Sauerbrey’s equation and Kanazawa’s equation cannot be applied to this situation. We model the QCM response with a Mason equivalent circuit. The model approximates a single layer of a uniform viscous coating on the QCM. The simulation of the equation circuit shows the possibility of the positive frequency change when the sorption occurs, which is the situation we find in some of the odor sensing applications. We measured the QCM frequency and resistance using the Vector Network Analyzer (VNWA). The QCMs were coated with glycerol, PEG2000, and PEG20M. To simulate odor exposure, a microdispenser was used to deposit the water. A positive frequency shift was observed in the case of PEG2000, and a negative frequency change was obtained for PEG20M. These results can be explained by the Mason equivalent circuit, with the assumption that when the film is exposed to water, its thickness increases and its viscosity decreases.

Introduction In odor sensing based upon QCM[1] sensing film is crucial for both sensor sensitivity and selectivity. The viscoelastic property of the sensing film greatly influences the response of the QCM sensor. The shear wave generated from QCM cannot penetrate deeply into the viscous sensing film. However, many appropriate sensing films with interesting properties are viscous. We would like to understand the behavior of the viscous sensing film although the behavior of the rigid sensing film is well understood. Method A QCM has an equivalent circuit derived from Mason equivalent circuit[2] as shown in fig. 1. Equations (1) and (2) indicate the acoustic impedance (Z_3e) due to acoustic loading as a function of film thickness (h) film density (ρ_A1) and complex wave velocity (ν_A1). To extract QCM equivalent circuit component, we used a network analyzer to measure conductance from a QCM. Then, we apply the curve fitting technique to extract R1, L1, and C1 from the conductance curve[3]. This technique was used instead of a conventional motional admittance method (measure the frequency of maximum conductance). Because all the data were used for fitting the curve, this method is more robust and less susceptible to noise than conventional motional admittance method. The dip-coating technique was used for coating viscous film on QCM (9MHz, AT-cut). The QCMs were immersed into glycerol solution and then pulled-up with various speeds, which results in different film thicknesses. Results and Conclusions To replicate odor deposition into sensing film. We were using a small-size dispenser to deposit droplets of liquid onto QCM. Water droplet was shot onto the glycerol film as on a QCM. The preliminary result is shown in fig.2. The frequency was increased after each vapor exposure, whereas the resistance was decreased, we sometimes encountered increase in frequency due to vapor exposure at the highly viscous environment. We tried to understand its mechanism using the following analysis. The study was firstly done with liquid loading which represents viscous film. Only a singles side of QCM should be in contact with liquid. We calculated resonance frequency shift and resistance change as a function of water film thickness as is shown in fig. 3. Our calculation result based upon Mason equivalent circuit roughly agreed with both Kanazawa’s equation[4] and the experiment when the film thickness became large. To estimate film thickness and dynamic viscosity of the film, Mason equivalent circuit was used. The optimization was performed to obtain the dynamic viscosity and film thickness using the experimental data obtained from various film thicknesses. Fig. 4 shows the experimental data points at estimated film thickness and calculated curve. The simulation of Mason circuit shows good agreement with experimental data. Moreover, the simulation result also suggests that the frequency increase occurs due to liquid loading at a certain condition. We will perform the experiment on depositing tiny liquid droplets into sensing film before the conference. References: [1] K. Nakamura, T. Nakamoto, and T. Moriizumi, Classification and evaluation of sensing films for QCM odor sensors by steady-state sensor response measurement, Sens. Actuators B, vol. 69, no. 3, pp. 295–301 (2000); doi: 10.1016/S0925-4005(00)00510-4 [2] T. Nakamoto, and T. Moriizumi, A Theory of a Quartz Crystal Microbalance Based upon a Mason Equivalent Circuit, Japanese Journal of Applied Physics, vol. 29, no. 5, pp. 963-969 (1990); doi: 10.1143/JJAP.29.963 [3] S. N. songkhla and T. Nakamoto, Signal Processing of Vector Network Analyzer Measurement for Quartz Crystal Microbalance with Viscous Damping, IEEE Sensors Journal, vol. 19, no. 22, pp. 10386 - 10392 (2019); doi: 10.1109/JSEN.2019.2930733 [4] K. K. Kanazawa and J. G. Gordon, Frequency of a quartz microbalance in contact with liquid, Anal. Chem, vol. 57, no. 8, pp.1770–1771 (1985); doi: 10.1021/ac00285a062 Figure 1