scholarly journals Discrimination Improvement of a Gas Sensors’ Array Using High-Frequency Quartz Crystal Microbalance Coated with Polymeric Films

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6972
Author(s):  
Marcos Rodríguez-Torres ◽  
Víctor Altuzar ◽  
Claudia Mendoza-Barrera ◽  
Georgina Beltrán-Pérez ◽  
Juan Castillo-Mixcóatl ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Quartz Crystal Microbalance ◽  
Quartz Crystal ◽  
Sensor Arrays ◽  
Principal Component ◽  
Polymeric Films ◽  
Static System ◽  
Similar System ◽  
Casting Technique ◽  
Sensors Array

The discrimination improvement of an array of four highly sensitive 30 MHz gas quartz crystal microbalance (QCM) sensors was performed and compared to a similar system based on a 12-MHz QCM. The sensing polymeric films were ethyl cellulose (EC), poly-methyl methacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) and they were coated over the AT-cut QCM devices by the drop casting technique. All the sensors had almost the same film thickness (0.2 μm). The fabricated QCM sensor arrays were exposed to three different concentrations, corresponding to 5, 10, and 15 μL, of ethanol, ethyl acetate, and heptane vapors. The steady state sensor responses were measured in a static system at a temperature of 20 °C and relative humidity of 22%. Our results showed that the 30-MHz sensors have a higher sensitivity than 12-MHz ones (around 5.73 times), independently of the sensing film and measured sample. On the other hand, principal component analysis and discriminant analysis were performed using the raw data of the responses. An improvement of the classification percentage between 12 MHz and 30 MHz sensors was found. However, it was not sufficient, especially for low concentrations. Furthermore, using partition coefficient and discriminant analysis (DA), an improvement of 100% classification of the three samples was achieved for the case of the 30-MHz sensor array.

scholarly journals Sensor Arrays Based on Polycyclic Aromatic Hydrocarbons: Chemiresistors versus Quartz-Crystal Microbalance

2013 ◽  
Vol 5 (22) ◽  
pp. 11641-11653 ◽  
Author(s):  
Nadav Bachar ◽  
Lucy Liberman ◽  
Fairouz Muallem ◽  
Xinliang Feng ◽  
Klaus Müllen ◽  
...  
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Quartz Crystal Microbalance ◽  
Aromatic Hydrocarbons ◽  
Quartz Crystal ◽  
Sensor Arrays ◽  
Polycyclic Aromatic

scholarly journals Low-Power Detection of Food Preservatives by a Novel Nanowire-Based Sensor Array

Foods ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 226 ◽  
Author(s):  
Dario Zappa
Keyword(s):  
Metal Oxide ◽  
Shelf Life ◽  
Sensor Array ◽  
Sensor Arrays ◽  
Principal Component ◽  
Industrial Applications ◽  
Food Preservatives ◽  
Electronic Noses ◽  
Long Time ◽  
Sensors Array

Food preservatives are compounds that are used for the treatment of food to improve the shelf life. In the food industry, it is necessary to monitor all processes for both safety and quality of the product. An electronic nose (or e-nose) is a biomimetic olfactory system that could find numerous industrial applications, including food quality control. Commercial electronic noses are based on sensor arrays composed by a combination of different sensors, which include conductometric metal oxide devices. Metal oxide nanowires are considered among the most promising materials for the fabrication of novel sensing devices, which can enhance the overall performances of e-noses in food applications. The present work reports the fabrication of a novel sensor array based on SnO2, CuO, and WO3 nanowires deposited on top of μHPs provided by ams Sensor Solutions Germany GmbH. The array was tested for the discrimination of four typical compounds added to food products or used for their treatment to increase the shelf life: ethanol, acetone, nitrogen dioxide, and ozone. Results are very promising; the sensors array was able to operate for a long time, consuming less than 50 mW for each single sensor, and principal component analysis (PCA) confirmed that the device was able to discriminate between different compounds.

scholarly journals Headspace Volatile Evaluation of Carrot Samples—Comparison of GC/MS and AuNPs-hpDNA-Based E-Nose

Foods ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 293 ◽  
Author(s):  
Sara Gaggiotti ◽  
Marcello Mascini ◽  
Paola Pittia ◽  
Flavio Della Pelle ◽  
Dario Compagnone
Keyword(s):  
Gas Chromatography ◽  
Quartz Crystal ◽  
Solid Phase ◽  
Sensor Arrays ◽  
Reference Method ◽  
Principal Component ◽  
Headspace Volatile ◽  
Different Temperatures ◽  
Quartz Crystal Microbalances ◽  
Spme Headspace

The performances of a quartz crystal microbalances (QCMs) based on an electronic nose (E-nose), modified with hairpin-DNA (hpDNA) for carrot aroma profiling has been evaluated. Solid phase micro-extraction (SPME) headspace sampling, combined with gas chromatography (GC), was used as a reference method. The changes in carrot aroma profiles stored at different temperatures (−18 °C, 4 °C, 25 °C, and 40 °C) were monitored during time up to 26 days. The principal component analysis of the data evidenced the different aroma patterns related to the presence of different key compounds. The output data achieved with the hpDNA-based E-nose were able to detect aroma patterns similar to gas chromatography with mass spectrometry (GC-MS). This work demonstrates that hpDNA has different sizes of loops that can be used for the development of sensor arrays able to detect aroma patterns in food and their changes with advantages in terms of easiness of usage, rapidity, and cost of analysis versus classical methods.

scholarly journals An Improved Comparison of Chemometric Analyses for the Identification of Acids and Bases With Colorimetric Sensor Arrays

2018 ◽  
Vol 10 (2) ◽  
pp. 36 ◽  
Author(s):  
Michael James Kangas ◽  
Christina L Wilson ◽  
Raychelle M Burks ◽  
Jordyn Atwater ◽  
Rachel M Lukowicz ◽  
...  
Keyword(s):  
Image Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Sensor Arrays ◽  
Principal Component ◽  
Colorimetric Sensor ◽  
Support Vector ◽  
Chemometric Methods ◽  
Data Set ◽  
Linear Discriminant

Colorimetric sensor arrays incorporating red, green, and blue (RGB) image analysis use value changes from multiple sensors for the identification and quantification of various analytes. RGB data can be easily obtained using image analysis software such as ImageJ. Subsequent chemometric analysis is becoming a key component of colorimetric array RGB data analysis, though literature contains mainly principal component analysis (PCA) and hierarchical cluster analysis (HCA). Seeking to expand the chemometric methods toolkit for array analysis, we explored the performance of nine chemometric methods were compared for the task of classifying 631 solutions (0.1 to 3 M) of acetic acid, malonic acid, lysine, and ammonia using an eight sensor colorimetric array. PCA and LDA (linear discriminant analysis) were effective for visualizing the dataset. For classification, linear discriminant analysis (LDA), (k nearest neighbors) KNN, (soft independent modelling by class analogy) SIMCA, recursive partitioning and regression trees (RPART), and hit quality index (HQI) were very effective with each method classifying compounds with over 90% correct assignments. Support vector machines (SVM) and partial least squares – discriminant analysis (PLS-DA) struggled with ~85 and 39% correct assignments, respectively. Additional mathematical treatments of the data set, such as incrementally increasing the exponents, did not improve the performance of LDA and KNN. The literature precedence indicates that the most common methods for analyzing colorimetric arrays are PCA, LDA, HCA, and KNN. To our knowledge, this is the first report of comparing and contrasting several more diverse chemometric methods to analyze the same colorimetric array data.

scholarly journals Ionic Liquid-Based Quartz Crystal Microbalance Sensors for Organic Vapors: A Tutorial Review

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 194
Author(s):  
Bishnu P. Regmi ◽  
Puspa L. Adhikari ◽  
Beni B. Dangi
Keyword(s):  
Ionic Liquids ◽  
Quartz Crystal Microbalance ◽  
Quartz Crystal ◽  
Sensor Arrays ◽  
Chemical Properties ◽  
Short Review ◽  
Future Research ◽  
Virtual Sensor ◽  
Research Areas ◽  
Biomedical Diagnostics

Organic vapor sensors are used in diverse applications ranging from environmental monitoring to biomedical diagnostics. Among a number of these sensors, quartz crystal microbalance (QCM) sensors prepared by coating ionic liquids (ILs) or their composites are promising devices for the analysis of volatile organic compounds (VOCs) in complex chemical mixtures. Ionic liquids are remarkable materials, which exhibit tunable physico-chemical properties, chemical and thermal stability, multiple interactions with diverse group of molecules, and enormous structural variability. Moreover, ILs exhibit viscoelastic properties, and hence these materials are ideal for creation of QCM virtual sensor arrays. While the scientific literature on IL-coated QCM sensors is rapidly growing, there is still much to learn. This manuscript provides a comprehensive review on the development of IL-coated QCM sensors and multi-sensor arrays as well as their applications for the analysis of VOCs in complex mixtures. Furthermore, IL-coated QCM virtual sensor arrays and their applications are presented. A short overview of some of the QCM designs, future research areas, and recommendations are also discussed. This short review is a necessary first step towards standardization and further development of QCM for the analysis of VOCs.

scholarly journals Coating-Based Quartz Crystal Microbalance Detection Methods of Environmentally Relevant Volatile Organic Compounds

Chemosensors ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 153
Author(s):  
Rocío L. Pérez ◽  
Caitlan E. Ayala ◽  
Jong-Yoon Park ◽  
Jin-Woo Choi ◽  
Isiah M. Warner
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Quartz Crystal Microbalance ◽  
Quartz Crystal ◽  
Sensor Arrays ◽  
Detection Methods ◽  
Electronic Systems ◽  
Atmospheric Conditions ◽  
Volatile Organic ◽  
Quartz Crystal Resonators

Volatile organic compounds (VOCs) that evaporate under standard atmospheric conditions are of growing concern. This is because it is well established that VOCs represent major contamination risks since release of these compounds into the atmosphere can contribute to global warming, and thus, can also be detrimental to the overall health of worldwide populations including plants, animals, and humans. Consequently, the detection, discrimination, and quantification of VOCs have become highly relevant areas of research over the past few decades. One method that has been and continues to be creatively developed for analyses of VOCs is the Quartz Crystal Microbalance (QCM). In this review, we summarize and analyze applications of QCM devices for the development of sensor arrays aimed at the detection of environmentally relevant VOCs. Herein, we also summarize applications of a variety of coatings, e.g., polymers, macrocycles, and ionic liquids that have been used and reported in the literature for surface modification in order to enhance sensing and selective detection of VOCs using quartz crystal resonators (QCRs) and thus QCM. In this review, we also summarize novel electronic systems that have been developed for improved QCM measurements.

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