Quartz Crystal Microbalance Sensor Array Research Articles

Detection of CO2, H2S, NH3, and gas mixtures using a quartz crystal microbalance sensor array with five sensitive materials

The large-scale development of chicken farms has inevitably led to an increase in the emission of harmful gases, which has prompted rapid research development on the detection of harmful gases, such as quartz crystal microbalance (QCM) sensors. In this research, a QCM sensor array modified with ethyl cellulose (EC), polyethyleneimine (PEI), polypyrrole (PPy), tetramethylammonium fluoride tetrahydrate (TMAF), and Nitrogen-doped tungsten carbide supported on carbon nanosheets (WC@NC) was established to detect gas mixtures. By analyzing the relationship between the fundamental frequency shift and the number of sensitive material layers for the QCM sensor, the optimal number of layers was determined. The QCM sensor array consisted of a blank QCM sensor, an 8-layer EC sensor, a 4-layer PEI sensor, a 3-layer PPy sensor, an 8-layer TMAF sensor, and an 8-layer WC@NC sensor. The results showed that the PEI sensor exhibited maximum frequency shifts when detecting gases, while TMAF and WC@NC films had the highest contribution to NH3 detection. TMAF, PEI, and WC@NC played significant roles in the binary classification of exceeding the standard detection of NH3. Additionally, WC@NC and EC sensors played an important role in detecting H2S and CO2, respectively. The QCM sensor array could accurately classify the excessive state of CO2. Overall, the QCM sensor array demonstrated a correct recognition rate of 87.5 %, indicating its potential for classifying the exceedance of NH3, CO2, and H2S gases in gas mixtures. This work provides basic information for research on QCM sensor arrays in gas detection.

MEMS‐Based Ultra‐High Frequency Wireless 10 × 10 QCM Sensor Array for Biochemical Sensing Applications

The quartz crystal microbalance (QCM) biosensor is one of the devices that enables label‐free evaluation of biomolecular reactions. Commercial QCM biosensors have less than 10 channels for detection and are not suitable for the screening. The sensitivity of the QCM biosensor increases as the quartz thickness becomes thinner; however, the limit of thinning is 60–330 μm. In this study, applying micromachining technology, a QCM sensor array chip of 15 mm square that had 100 ultra‐thin quartz resonators (2.5 μm) that were operated wirelessly was developed. And we succeeded in detecting the resonance spectrum through the device evaluation. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Repeatability and sensitivity of quartz crystal microbalance (QCM) sensor array modified with four sensitive materials

With continuous expansion of livestock and poultry breeding industry, the emission of harmful gases has inevitably increased which has also prompted the rapid development of research on harmful gases detection, such as quartz crystal microbalance(QCM)sensors. In this research, a gas-sensing system based on QCM sensor array modified with ethyl cellulose (EC), polyethyleneimine (PEI), tetramethylammonium fluoride tetrahydrate (TMAF), and polypyrrole (PPy) was established to detect three standard harmful gases, namely CO2, NH3, and H2S. It has been observed that the QCM sensors modified with four materials had a good repeatability and a significant response to the three standard harmful gases. Furthermore, the suitable concentrations of the sensitive materials were 20 mg/ml for EC, 10 mg/ml for TMAF, 35 mg/ml for PEI, and 7 mg/ml for PPy. The frequency shift resulted by modified mass of the sensors for the four materials with the best concentrations were 21,343.1 Hz for EC, 21,065.5 Hz for TMAF, 2736.9 Hz for PEI, and 5292.4 Hz for PPy. Additionally, there was a linear relationship between the frequency shift and the concentration of three sample gases in different ranges with a high linear fit coefficient (R2>0.92), except TMAF versus CO2. Moreover, R2 with blank quartz wafer compensation was slightly smaller than which one without compensation. Therefore, the gas-sensing system based on QCM sensor array has an ideal repeatability and recovery response to the three standard gases, and the sensitivity performance was good. This work provides basic information for the research on QCM sensor array in gas detection.

A High Frequency Dual Inverted Mesa QCM Sensor Array with Concentric Electrodes

Quartz Crystal Microbalance (QCM) is a candidate technology for high sensitivity application. This mass sensor's property depends on the piezoelectric property of the AT-cut quartz crystal. QCM has been widely employed for gas detection due to its comparative advantages including high mass sensitivity, potential for array configuration, low cost, ease of fabrication as well as wide range of available sensitive material compatibility. However, its application has been limited due to two main disadvantages of the non-uniform mass sensitivity across the electrodes and lower frequency of operation. In this work, in order to overcome these disadvantages, a novel concentric electrode structure combined with the dual inverted mesa structure has been proposed and implemented. It is demonstrated that the developed and optimized concentric electrode has provided a uniform displacement across the QCM's sensing electrode. In addition, the dual inverted mesa design has been implemented in the QCM array in which a high fundamental resonant frequency of 33 MHz has been achieved without interference between the adjacent channels in the sensor array. The interference between the adjacent high frequency QCM channels has been eliminated and therefore, each QCM can function as an individual gas sensor when coated with the designed sensing layers. For 33 MHz, the interference has been eliminated at the optimal center to center between electrode distance (c2c). In the case of 10 MHz array, c2c value of 6 mm is achieved which is lower than the value of c2c achieved on a traditionally un-etched QCM array which was found equal to 6.5 mm. Therefore, the proposed QCM array design is shown to reduce the overall size while enhancing the device sensitivity, uniformity and performance.

A Perspective on Recent Advances in Piezoelectric Chemical Sensors for Environmental Monitoring and Foodstuffs Analysis

This paper provides a selection of the last two decades publications on the development and application of chemical sensors based on piezoelectric quartz resonators for a wide range of analytical tasks. Most of the attention is devoted to an analysis of gas and liquid media and to industrial processes controls utilizing single quartz crystal microbalance (QCM) sensors, bulk acoustic wave (BAW) sensors, and their arrays in e-nose systems. The unique opportunity to estimate several heavy metals in natural and wastewater samples from the output of a QCM sensor array highly sensitive to changes in metal ion activity in water vapor is shown. The high potential of QCM multisensor systems for fast and cost-effective water contamination assessments “in situ” without sample pretreatment is demonstrated.

Identification of Bioactive Compounds in Ginger Based on Molecularly Imprinted Polymer Quartz Crystal Microbalance Gas Sensor

Borneol, citral, and geraniol have been investigated as the major bioactive compound commonly found in ginger. In this work, a molecularly imprinted polymer (MIP) coated quartz crystal microbalance (QCM) sensor array has been employed for selective recognition of bioactive compounds in the ginger essential oil. In the experiment, the concentration of these bioactive compounds previously was measured using solid phase micro extraction gas chromatography-mass spectroscopy (SPME-GC/MS). Design of MIPs as the template of target molecules was created using polyacrylic acid (PAA) polymer matrix and three molecular targets (borneol, citral, and geraniol). An array of QCM sensor was prepared using four 9-Mhz AT-cut quartz crystal embedded between vacuum-deposited Au electrodes. For data recording, the headspace system flew the odorant of three varieties of ginger essential oil as positive control odorant and wild ginger essential oil as negative control odorant into the QCM sensor chamber. Then, mass loading in the MIP films caused frequency change of QCM sensor array due to odorant adsorption in a thin layer of MIP. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to analyse the QCM response sensor. PCA score plot showed segregation of feature response of ginger essential oil with and without the molecular target in the coordinate of principal components. Meanwhile, LDA was able to discriminate training datasets of 80 ginger samples containing borneol, citral, and borneol with accuracy more than 92.50%.

Verification of Quartz Crystal Microbalance Array using Vector Network Analyzer and OpenQCM

<p>Quartz Crystal Microbalance (QCM) is a device that allows non-destructive measurements of r in situ reaction activities. In this article, an array comprising of six 3MHz QCM sensors in an array were characterized using a vector network analyzer and OpenQCM, a portable measuring instrument that measures change in resonance frequency. Measurements of S21 transmission characteristics using the vector network analyzer provides the resonance frequency and can also be used to derive the RLC equivalent electrical circuit values of a resonant two-port network based on the Butterworth-Van Dyke model. In this work, R<sub>m</sub>, L<sub>m</sub>, C<sub>m</sub> and C<sub>o </sub>were obtained via curve-fitting of the measurement results to the simulated results. Measurements were done in triplicates to verify reproducibility for all 6 sensors. For comparison, measurements were also done using a portable, open-source instrument, OpenQCM. The OpenQCM instrument directly measures changes in resonance frequencies, making it ideal for biosensing experiments, which correlate changes in mass with changes in resonance frequencies. Comparison between resonance frequency measurements using VNA and OpenQCM exhibit low percentage difference 0.2%. This QCM sensor array has the potential of conducting real-time, point-of-care analyses for detection of biological molecules. </p>

Simple and rapid differentiation of toxic gases using a quartz crystal microbalance sensor array coupled with principal component analysis

A novel quartz crystal microbalance (QCM) sensor array was fabricated for differentiating three toxic gases (NH3, CO and NO2) from their tertiary mixtures. The QCM sensor array composed of three QCM sensors that were constructed using graphene oxide (GO)-based and N-substituted pyrrole derivative-based films. The response frequency changes of a QCM sensor array were recorded upon exposing to each target toxic gas with varying concentrations and the obtained data were analyzed by principal component analysis (PCA) in order to differentiate the target toxic gas under testing condition of tertiary mixing of toxic gases. The results of this work show promising prospects for the use of a low-cost, easy to use and rapid method for differentiating the target toxic gas in the presence of a mixture of gases.

QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration

Herein, a simplistic quartz crystal microbalance (QCM) approach for discrimination of petroleum based fuels is presented. In this regard, a quartz crystal microbalance (QCM) virtual multisensor array (V-MSA) was employed to discriminate between different petroleum based fuels and to detect gasoline adulteration with high accuracy. First, an ionic liquid based V-MSA was used to discriminate between four fuel types (petroleum ether, gasoline, kerosene, and diesel). Subsequently, the system was used to successfully discriminate between three gasoline grades as a precursor for studies of gasoline adulteration. Finally, the system was used to detect and determine the nature of several gasoline adulterants at different v/v ratios (1%, 10%, 20% and 40%). Excellent accuracy (100%) was achieved for each study extolling the potential of this approach. This report represents the first example of a QCM sensor array utilized for detection of gasoline adulteration.

QCM virtual sensor array: Vapor identification and molecular weight approximation

Herein, we present a promising approach for simultaneous identification and molecular weight approximation of closely related pure organic vapors using the quartz crystal microbalance (QCM). In this regard, a QCM virtual sensor array (VSA) was fabricated employing a binary blend of ionic liquid and polymer, i.e. 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([HMIm][NTf2]) and poly(methyl methacrylate). This VSA technique allows discrimination/identification of closely related alcohols including isomers, while use of a composite coating facilitates molecular weight approximation of this set employing only the first harmonic. Statistical analyses (principal component and discriminant analyses) allowed identification of all analytes with extremely high accuracy. Molecular weight approximations were achieved with a linear correlation of R2≈0.99. This is the first report of a QCM sensor array that allows both identification and molecular weight approximation of organic vapors.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes.

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

A novel quartz crystal microbalance sensor array based on molecular imprinted polymers for simultaneous detection of clenbuterol and its metabolites

For the rapid and robust detection of both parent clenbuterol (CLB) and its metabolites in swine urine samples, a novel quartz crystal microbalance (QCM) sensor array for CLB detection based on molecularly imprinted polymers (MIPs) was developed in this investigation. At first, clenbuterol and the structural analogs of its metabolites, 4-Aminohippuric acid (AHA) and 4-hydroxymandelic acid (HMA), were chosen as molecular templates. Through computational molecular modeling, the optimum ratio between the functional monomer and molecular template was selected. The surface imprinting method was applied to modify QCM electrode surface to graft a thin MIP film. The grafting polymer was characterized by Fourier-transformed infrared spectrometry (FTIR) and atomic force microscopy (AFM), respectively. After then, an array system composed of three sensors was employed to test the responses with different solutions and the principal component analysis (PCA) was adopted to analyze the corresponding data. As a result, for the designed sensor to clenbuterol, a linear equation y=100.07x-722.96 (R2=0.9928) was found between the sensor frequency shift ΔF and negative logarithm of clenbuterol concentration (-lgC). The limitation of detection (LOD) was 3.0ng/mL, which is lower than the Codex Alimentarius Commission regulations residue limit 10μg/L. The corresponding data of the three template solutions were analyzed by PCA, obtaining 100% recognition. The result demonstrated the feasibility that the developed method could be applied to detect whether the livestock was feed with CLB nutrient redistribution agent by checking the urine samples.

Enhancing detection of nitroaromatic vapors by utilizing polymer coatings on quartz crystal microbalances having strong dipoles

A novel class of PDMS based polymers containing azobenzene side chains were synthesized and evaluated as coatings for quartz crystal microbalance (QCM) based sensors to detect nitroaromatic vapors. The polymers contain functional groups (p-substituted azobenzene moieties and hydroxyl groups) that can interact with compounds with large dipole moments such as nitroaromatic chemicals through a combination of permanent dipole-dipole interactions and hydrogen bonding. A QCM sensor array was prepared by coating different polymers onto the surface of a quartz crystal and evaluating the response of the each coating to saturated vapors of a variety of analytes such as toluene, octane, 2-nitrotoluene, nitrobenzene, and 2,4 dinitrotoluene. The incorporation of azobenzene moieties in the polymer structure increased the sensor response towards the nitroaromatic analytes. Pattern recognition techniques such as principal component analysis (PCA) and decision tree learning methods were applied to evaluate the sensor response and predict analyte identity. A classification accuracy of 96% was obtained using classification and regression trees (CART) based learning. This novel approach opens new possibilities in ultrasensitive detection of chemical vapors with significant dipole moments.

A quick responding quartz crystal microbalance sensor array based on molecular imprinted polyacrylic acids coating for selective identification of aldehydes in body odor

In present work, a novel quartz crystal microbalance (QCM) sensor array has been developed for prompt identification of primary aldehydes in human body odor. Molecularly imprinted polymers (MIP) are prepared using the polyacrylic acid (PAA) polymer matrix and three organic acids (propenoic acid, hexanoic acid and octanoic acid) as template molecules, and utilized as QCM surface coating layer. The performance of MIP films is characterized by 4-element QCM sensor array (three coated with MIP layers and one with pure PAA for reference) dynamic and static responses to target aldehydes: hexanal, heptanal, and nonanal in single, binary, and tertiary mixtures at distinct concentrations. The target aldehydes were selected subsequent to characterization of body odor samples with solid phase-micro extraction gas chromatography mass spectrometer (SPME-GC–MS). The hexanoic acid and octanoic acid imprinted PAA exhibit fast response, and better sensitivity, selectivity and reproducibility than the propenoic acid, and non-imprinted PAA in array. The response time and recovery time for hexanoic acid imprinted PAA are obtained as 5s and 12s respectively to typical concentrations of binary and tertiary mixtures of aldehydes using the static response. Dynamic sensor array response matrix has been processed with principal component analysis (PCA) for visual, and support vector machine (SVM) classifier for quantitative identification of target odors. Aldehyde odors were identified successfully in principal component (PC) space. SVM classifier results maximum recognition rate 79% for three classes of binary odors and 83% including single, binary, and tertiary odor classes in 3-fold cross validation.

A vapor response mechanism study of surface-modified single-walled carbon nanotubes coated chemiresistors and quartz crystal microbalance sensor arrays

This paper compares the selectivity and discusses the response mechanisms of various surface-modified, single-walled carbon nanotube (SWCNT)-coated sensor arrays for the detection of volatile organic compounds (VOCs). Two types of sensor platforms, chemiresistor and quartz crystal microbalance (QCM), were used to probe the resistance changes and absorption masses during vapor sensing. Four sensing materials were used in this comparison study: pristine, acidified, esterified, and surfactant (sodium dodecyl sulfate, SDS)-coated SWCNTs. SWCNT-coated QCMs reached the response equilibrium faster than the chemiresistors did, which revealed a delay diffusion behavior at the inter-tube junction. In addition, the calibration lines for QCMs were all linear, but the chemiresistors showed curvature calibration lines which indicated less effectiveness of swelling at high concentrations. While the sorption of vapor molecules caused an increase in the resistance for most SWCNTs due to the swelling, the acidified SWCNTs showed no responses to nonpolar vapors and a negative response to hydrogen bond acceptors. This discovery provided insight into the inter-tube interlocks and conductivity modulation of acidified SWCNTs via a hydrogen bond. The results in this study provide a stepping-stone for further understanding of the mechanisms behind the vapor selectivity of surface-modified SWCNT sensor arrays.

Molecular imprinted polyacrylic acids based QCM sensor array for recognition of organic acids in body odor

In present research, a novel volatile acids imprinted 3-element quartz crystal microbalance (QCM) sensor array has been designed for the selective recognition of organic acids odor. The target organic acids have been previously assigned as significant biomarker in human body odor and human waste odor. This is also confirmed with solid phase micro-extraction gas chromatography-mass spectrometer (SPME-GC-MS) characterization of body odor samples in present study. Polyacrylic acid (PAA) polymer has been used to prepare three selective molecular imprinted polymers (MIPs). MIP films were coated on the surface of QCM electrodes. Performance of MIP based QCM sensor array has been studied by exposing different concentrations of propenoic acid, hexanoic acid, and octanoic acid in singly and their binary mixtures. The response time and recovery time were 5s and 14s, respectively for one of the MIP coated QCM sensor to a typical binary mixture of acids odor. Frequency shift of QCM due to odor molecules adsorption in thin layer of MIP was measured as sensor signal. Sensor signal response matrix has been analyzed with principal component analysis (PCA) and support vector machine (SVM) methods for the odor recognition. The acid odors were identified effectively in principal component (PC) space. SVM classifier results 70–76% recognition rate for three classes of binary odor. While excluding the binary mixture of propenoic acid and octanoic acid the average recognition rate approaches to 95% in 3-fold cross validation of SVM classifier.

Development of a plasticizer-poly(methyl methacrylate) membrane for sensing petroleum hydrocarbons in water

A quartz crystal microbalance (QCM) sensor based on a poly(methyl methacrylate) (PMMA) film has been developed for the detection of aromatic hydrocarbons (i.e., benzene, toluene, ethylbenzene, p-xylene and naphthalene) in aqueous solutions. The PMMA was modified by introducing a plasticizer into the film and the hydrocarbon sensitivity was studied as a function of plasticizer type and concentration. Generally, the PMMA sensitivity for hydrocarbons was shown to be higher in the presence of a plasticizer. However, it was found that some of the plasticizers (i.e., diisooctyl azelate and n-butyl stearate) exhibit much better sensitivity compared to others (i.e., methyl laurate and di-n-butyl phthalate), suggesting that the response of the PMMA film can be tailored by varying the properties of the plasticizer. The relationship between plasticizer type and hydrocarbon sensitivity was investigated and this revealed that the size/molecular weight of the plasticizer molecule plays a significant role. Linear discriminant analysis (LDA) was performed to determine if the QCM sensor array comprising plasticizer–PMMA films are suitable for distinguishing between the various hydrocarbons. LDA modelling revealed that the sensor array can discriminate most of the hydrocarbon analytes investigated in this study.

Mass sensitive multi-sensor platform for receptor screening and quantification purposes

Quartz crystal microbalance (QCM) multi-sensor arrays coated with molecularly imprinted polymers (MIP) as recognition materials have been tested for screening and quantification. For receptor screening, six-electrode QCM sensor arrays containing MIP with variable ratios of vinylpyrrolidone–styrene–divinylbenzene copolymers were examined to identify the optimal monomer combination for chemical sensing of ethyl acetate in one measuring step. This revealed an optimum MIP that can detect vapours below 50 ppm. For quantification purposes, the QCM sensor array data were analysed chemometrically. Polystyrene–divinylbenzene imprinted polymers selectively detected volatile emissions from different herbs. The terpenes emission pattern revealed screening among isomeric terpenes with detection limits below 20 ppm. Furthermore, this strategy allows evaluating fresh and dried herbs and their levels of freshness and respective shelf lives.

Detection of Volatile Organic Compounds by Analyses of Polymer-Coated Quartz Crystal Microbalance Sensor Arrays

Detection of Volatile Organic Compounds by Analyses of Polymer-Coated Quartz Crystal Microbalance Sensor Arrays

Specific binding DNA-based piezoelectric quartz crystal microbalance biosensor array for the study of NF-κB

NF-κB is a protein complex found in almost all animal cell types that act as a transcription factor. Conventional methods for the study of NF-κB, however, are time-consuming, and most require radioactive labeling. The aim of this study was to develop a rapid method to study NF-κB by use of a direct specific binding DNA-based biosensor based on a quartz crystal microbalance (QCM). A specific DNA probe was designed and modified by the sulfhydryl group on the 5′-Terminal to be immobilized on the gold coated surface of 10 MHz piezoelectric quartz crystal to construct the QCM biosensor to detect NF-κB. We made calibration curves after immobilization of probe at an optimal concentration and then evaluated the performance characteristics of the sensor with a series of tests. In addition, we measured clinical samples with both QCM sensor array and ELISA to assess the QCM sensor. Under optimal conditions, the response frequency of piezoelectric biosensor was linearly dependent on NF-κB concentrations in the range of 0.25 ng/μL to 50 ng/μL with relative standard deviation (RSD) of intra-assay and inter-assay less than 10%. The QCM system we designed has the advantages of being rapid, simple operation, label-free, cheap, sensitive and could be a useful supplement to commercial assay methods in the study of NF-κB, such as NF-κB binding, NF-κB quantitation, NF-κB identification and interaction between NF-κB and DNA.