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virtual sensor array Based on Piezoelectric Cantilever Resonator for Identification of Volatile Organic Compounds

ACS sensorS 2022年第5期7卷 1555-1563页

作者： Li, Dongsheng Zhu, Boyi Pang, Kai Zhang, Qian Qu, Mengjiao Liu, Weiting Fu, YongQing Xie, Jin Zhejiang Univ State Key Lab Fluid Power & Mech Syst Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Dept Polymer Sci & Engn MOE Key Lab Macromol Synth & Functionalizat Hangzhou 310027 Peoples R China

Piezoelectric cantilever resonator is one of the most promising platforms for real-time sensing of volatile organic compounds (VOCs). However, it has been a great challenge to eliminate the cross-sensitivity of various VOCs for these cantilever-based VOC sensors. Herein, a virtual sensor array (VSA) is proposed on the basis of a sensing layer of GO film deposited onto an AlN piezoelectric cantilever with five groups of top electrodes for identification of various VOCs. Different groups of top electrodes are applied to obtain high amplitudes of multiple resonance peaks for the cantilever, thus achieving low limits of detection (LODs) to VOCs. Frequency shifts of multiple resonant modes and changes of impedance values are taken as the responses of the proposed VSA to VOCs, and these multidimensional responses generate a unique fingerprint for each VOC. On the basis of machine learning algorithms, the proposed VSA can accurately identify different types of VOCs and mixtures with accuracies of 95.8 and 87.5%, respectively. Furthermore, the VSA has successfully been applied to identify the emissions from healthy plants and "plants with late blight" with an accuracy of 89%. The high levels of identifications show great potentials of the VSA for diagnosis of infectious plant diseases by detecting VOC biomarkers

关键词： AlN piezoelectric cantilever machine learning plant diseases diagnosis virtual sensor array

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A single recognition unit-based virtual sensor array: Applying 3D fluorescence spectroscopy to inner filter effect-based sensing

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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024年 305卷 123470页

作者： Xue, Xiangfen Wei, Mingjie Yuan, Jing Huang, Xinyu Cao, Qinghua Xia, Changkun Niu, Xiangheng Yin, Xiulian Jiangsu Univ Sch Chem & Chem Engn Zhenjiang 212013 Peoples R China Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 212013 Peoples R China

A convenient, fast, low-cost detection and discrimination method is demanded for environmental monitoring but still it remains more technological challenges. Herein, we demonstrate that the inner filter effect (IFE), in combination with three-dimensional fluorescence spectroscopy, can offer a virtual sensor array (VSA) as a proper solution. And with the aid of pattern recognition techniques, it is feasible to recognize compounds with structural similarities economically and effectively. In this study, with the help of visual clustering plots of principal component analysis (PCA), a prediction model based on hierarchical strategy was made using support vector machine (SVM) method for the qualitative profiling of aromatic pollutants. The VSA was constructed by a single metal-organic framework (MOF) recognition unit (MOF-74 (Zn)) with the excitation wavelength as external regulatory factors. Pattern characteristics of four aromatics with very similar structures (phenylamine, chlorobenzene, nitrobenzene, and phenol), both single analyte and binary mixtures, were acquired. The primary constituents of multi-dimensional spectral signals were subsequently extracted and fed into a vector machine to construct a prediction model through 10-fold cross-validation optimization, resulting in a classification accuracy of 100% for single analytes and 96% for mixtures. Quantitative research has shown that, except for chlorobenzene, all three other analytes can be predicted in concentration within an acceptable error range, and the mixture can be predicted proportionally. Moreover, the VSA can be used to distinguish these pollutants in tap and river water also. We propose for the first time a new tack for the construction of VSA in a general manner, namely using three-dimensional full range fluorescence scanning for IFE based sensing to get multiple times of information resulting from different weak interaction between analyte and sensor for decision-making.

关键词： virtual sensor array Inner filter effect Three-dimensional fluorescence spectroscopy Principal component analysis Support vector machine Least-squares method

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virtual sensor array Based on Butterworth-Van Dyke Equivalent Model of QCM for Selective Detection of Volatile Organic Compounds

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ACS APPLIED MATERIALS & INTERFACES 2021年第39期13卷 47043-47051页

作者： Li, Dongsheng Xie, Zihao Qu, Mengjiao Zhang, Qian Fu, Yongqing Xie, Jin Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310027 Zhejiang Peoples R China Univ Northumbria Fac Engn & Environm Newcastle Upon Tyne NEI 8ST Tyne & Wear England

Recently virtual sensor arrays (VSAs) have been developed to improve the selectivity of volatile organic compound (VOC) sensors. However, most reported VSAs rely on detecting single property change of the sensing material after their exposure to VOCs, thus resulting in a loss of much valuable information. In this work, we propose a VSA with the high dimensionality of outputs based on a quartz crystal microbalance (QCM) and a sensing layer of MXene. Changes in both mechanical and electrical properties of the MXene film are utilized in the detection of the VOCs. We take the changes of parameters of the Butterworth-van Dyke model for the QCM-based sensor operated at multiple harmonics as the responses of the VSA to various VOCs. The dimensionality of the VSA's responses has been expanded to four independent outputs, and the responses to the VOCs have shown good linearity in multidimensional space. The response and recovery times are 16 and 54 s, respectively. Based on machine learning algorithms, the proposed VSA accurately identifies different VOCs and mixtures, as well as quantifies the targeted VOC in complex backgrounds (with an accuracy of 90.6%). Moreover, we demonstrate the capacity of the VSA to identify "patients with diabetic ketosis" from volunteers with an accuracy of 95%, based on the detection of their exhaled breath. The QCM-based VSA shows great potential for detecting VOC biomarkers in human breath for disease diagnosis.

关键词： VOCs sensor selectivity virtual sensor array QCM MXene breath analysis

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Polymer-based virtual sensor array Leveraging Fringing Field Capacitance for VOC Detection

Polymer-based Virtual Sensor Array Leveraging Fringing Field...

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IEEE sensors Conference

作者： Raj, Gian Carlo Antony Elnemr, Youssef Ezzat Munirathinam, Pavithra Birjis, Yumna Love, Calvin Emadi, Arezoo Univ Windsor Dept Elect & Comp Engn Windsor ON Canada

ISBN: (纸本)9798350303872

The detection of volatile organic compounds (VOCs) is crucial in various applications, from environmental monitoring to industrial safety. Through this paper we present a comparative analysis of a polymer-based virtual sensor array (VSA) for VOC detection, utilizing fringing field capacitance to enhance sensitivity and potentially reduce the size of sensor arrays required to differentiate VOC analytes. Polymer-based sensors exhibit changes in material permittivity in response to VOCs, and electrochemical impedance spectroscopy (EIS) measures the resultant change in capacitance. Principal component analysis (PCA) is used to extract subtle patterns from the multivariate EIS data for the identification and differentiation of different VOCs. Results demonstrate superior sensitivity and differentiation capability over conventional rectangular IDE reference design. This research demonstrates the potential of a polymer-based virtual sensor array leveraging fringing field capacitance in VOC detection.

关键词： volatile organic compounds VOC detection virtual sensor array fringing field capacitance polymer-based sensors electrochemical impedance spectroscopy principal component analysis

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virtual MOS sensor array Design for Ammonia Monitoring in Pig Barns

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sensorS 2025年第8期25卷 2617-2617页

作者： Parsiegel, Raphael Becker, Miguel Budag Try, Pieter Gebhard, Marion Westphalian Univ Appl Sci Dept Elect Engn & Appl Sci Grp Sensors & Actuators D-45897 Gelsenkirchen Germany

Animal welfare in barns is strongly influenced by air quality, with gaseous emissions like ammonia posing significant respiratory health risks. However, current state-of-the-art ammonia monitoring systems are labor-intensive and expensive. Metal Oxide Semiconductor (MOS) sensors offer a promising alternative due to their compatibility with sensor networks, enabling high-resolution ammonia monitoring across spatial and temporal scales. While MOS sensors exhibit high sensitivity to various volatile compounds, temperature-cycled operation is commonly employed to enhance selectivity, effectively creating virtual sensor arrays. This study aims to improve ammonia detection by designing a virtual sensor array through a cyclic data-driven approach, integrating machine learning with solid-state sensor modeling. The results of a two-week dataset with measurements of four different pig barns demonstrate ammonia sensing with a sampling rate of about 2/min and a range of 1-30 ppm. The method is robust and exhibits a 10% increase in normalized RMSE when comparing testing results of an unseen sensor module with results of the training dataset. A filter membrane boosts accuracy and prevents data loss due to contamination, such as flyspecks. Overall, the used MOS sensor BME688 is effective and economical for widespread continuous ammonia monitoring and localization of ammonia sources in pig barns.

关键词： livestock monitoring MOS sensor ammonia monitoring electronic nose temperature-cycled operation virtual sensor array smart sensor smart farming machine learning

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virtual sensor array based on MXene for selective detections of VOCs

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sensorS AND ACTUATORS B-CHEMICAL 2021年 331卷 129414-129414页

作者： Li, Dongsheng Liu, Guang Zhang, Qian Qu, Mengjiao Fu, Yong Qing Liu, Qingjun Xie, Jin Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Biosensor Natl Special Lab Key Lab Biomed Engn Educ MinistDept Biomed Engn Hangzhou 310027 Peoples R China Univ Northumbria Fac Engn & Environm Newcastle Upon Tyne NE1 8ST Tyne & Wear England

Two-dimensional transition metal carbides/nitrides, known as MXenes, have recently received significant attention for gas sensing applications. However, MXenes have strong adsorption to many types of volatile organic compounds (VOCs), and therefore gas sensors based on MXenes generally have low selectivity and poor performance in mixtures of VOCs due to cross-sensitivity issues. Herein, we developed a Ti3C2Tx-based virtual sensor array (VSA) which allows both highly accurate detection and identification of different VOCs, as well as concentration prediction of the target VOC in variable backgrounds. The VSA's responses from the broadband impedance spectra create a unique fingerprint of each VOC without a need for changing temperatures. Based on the methodologies of principal component analysis and linear discrimination analysis, we demonstrate highly accurate identifications for different types of VOCs and mixtures using this MXene based VSA. Furthermore, we demonstrate an accuracy of 93.2% for the prediction of ethanol concentrations in the presence of different concentrations of water and methanol. The high level of identification and concentration prediction shows a great potential of MXene based VSA for detection of VOCs of interest in the presence of known and unknown interferences.

关键词： MXene 2D material Cross-sensitivity virtual sensor array Multivariable VOC sensing Broadband impedance spectra

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HIGH DATA DIMENSIONALITY OF virtual sensor array BASED ON QCM AND MXENE FOR SELECTIVE VOC DETECTION 21

HIGH DATA DIMENSIONALITY OF VIRTUAL SENSOR ARRAY BASED ON QC...

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21st International Conference on Solid-State sensors, Actuators and Microsystems (Transducers)

作者： Li, Dongsheng Pang, Jintao Qu, Mengjiao Zhang, Qian Xie, Jin Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou Peoples R China

ISBN: (纸本)9780738125626

virtual sensor array (VSA) has been developed for selective detection of VOCs. Currently the most reported VSAs only detect the change of a single property of the sensing film, thus a serious waste of valuable information. Herein, we propose a VSA with a high data dimensionality based on QCM and a sensing layer of MXene. Mechanical and electrical properties of the MXene film are detected simultaneously by the QCM with appropriate sizes of sensing film and electrodes. We take changes of the extracted parameters from Butterworth-van-Dyke (BvD) equivalent circuit obtained at multiple harmonics as the response of the QCM-based VSA after exposure to various VOCs. By performing the principal component analysis (PCA) for the response of the VSA, we demonstrate the data dimensionality over 4-D of the VSA is achieved. And the proposed VSA has a potential to distinguish between different VOCs and quantify concentrations of target VOCs.

关键词： virtual sensor array High data dimensionality Selective VOC detection QCM MXene

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QCM virtual sensor array: Vapor identification and molecular weight approximation

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sensorS AND ACTUATORS B-CHEMICAL 2017年 246卷 952-960页

作者： Speller, Nicholas C. Siraj, Noureen McCarter, Kevin S. Vaughan, Stephanie Warner, Isiah M. Louisiana State Univ Dept Chem Baton Rouge LA 70803 USA Univ Arkansas Dept Chem Little Rock AR 72204 USA Louisiana State Univ Dept Expt Stat Baton Rouge LA 70803 USA

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 R-2 approximate to 0.99. This is the first report of a QCM sensor array that allows both identification and molecular weight approximation of organic vapors. (C) 2017 Elsevier B.V. All rights reserved.

关键词： QCM-D Harmonics virtual sensor array Ionic liquid Polymer Viscoelasticity

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Bulk acoustic wave resonator virtual sensor arrays for DMMP detection

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NANOTECHNOLOGY AND PRECISION ENGINEERING 2025年第4期8卷

作者： Zhao, Zeyu Huang, Shuyuan Li, Qi You, Rui Jiang, Yongqiang Duan, Huiqi Chen, Shaolong Chang, Ye Wang, Zilun Tianjin Univ State Key Lab Precis Measuring Technol & Instrumen Tianjin 300072 Peoples R China Acad Mil Med Sci State Key Lab Pathogen & Biosecur Beijing 100071 Peoples R China Tianjin Univ Sci & Technol Coll Elect Informat & Automat Tianjin Peoples R China

Accurate detection of dimethyl methylphosphonate (DMMP), a simulant for chemical warfare agents, is vital for both public safety and military defense. However, conventional detection methods suffer from low selectivity, owing to interference from structurally similar compounds. In this study, we present a highly sensitive and selective gas sensor utilizing a solid-mounted film bulk acoustic resonator based on carbon nanotubes functionalized with hexafluoroisopropanol (HFiP) to enhance DMMP detection. This approach leverages the strong hydrogen bonding between HFiP and DMMP molecules to significantly improve the sensor's adsorption capacity and selectivity. To further refine selectivity and at the same time solve the cross-sensitivity problem of sensitive membranes, we introduce a virtual sensor array design, generated by modulating the input power to the resonator, which enables the sensor to operate in multiple response modes across varying vibrational amplitudes. These multimodal responses are subjected to linear discriminant analysis, allowing precise differentiation of DMMP from other volatile organic compounds such as tributyl phosphate and dimethyl phthalate. Our results demonstrate superior performance in terms of both sensitivity and selectivity, offering a robust solution for detecting low-concentration DMMP in complex environments.

关键词： Dimethyl methylphosphonate virtual sensor array Solid-mounted film bulk acoustic resonator Linear discriminant analysis

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Selective room temperature nanostructured thin film alcohol sensor as a virtual sensor array

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sensorS AND ACTUATORS B-CHEMICAL 2013年 176卷 1096-1102页

作者： Beckers, N. A. Taschuk, M. T. Brett, M. J. Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada Natl Inst Nanotechnol Edmonton AB T6G 2M9 Canada

Nanostructured SiO2 thin films fabricated via glancing angle deposition on interdigitated electrodes were used as room temperature alcohol sensors. Both frequency dependent capacitance and impedance were used to analyze sensor response to methanol, ethanol, 1-propanol, 2-propanol, and 1-butanol. sensor responsivity was examined across the entire percent vapour saturation range for the same set of alcohols and the detection limit for ethanol, as an example, was derived. The response and recovery times for ethanol were determined from a pulse test and the responsivity curves, giving values of 66 s and 76 s, respectively. sensor lifetime was examined for the same set of alcohols with and without irradiation from a UV-LED. We observed that sensor aging for the detection of ethanol and 1-butanol was greatly reduced under irradiation from the UV-LED whereas the UV-LED had little effect on aging for methanol, 1-propanol and 2-propanol. Using the frequency dependent responsivity curves of our sensors, we developed an algorithm that enables a single sensor to distinguish between methanol, ethanol and 2-propanol in a blind protocol test. In five out of seven trials, the algorithm successfully identified both the alcohol and concentration thereby demonstrating room temperature single sensor selectivity. (C) 2012 Elsevier B. V. All rights reserved.

关键词： Alcohol gas sensor Nanostructured thin films virtual sensor array

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