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Special Issue "Multisensor Systems for Chemical Analysis"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Chemical Sensors".

Deadline for manuscript submissions: closed (30 September 2020).

Special Issue Editors

Dr. Dmitry Kirsanov
E-Mail Website
Guest Editor
Institute of Chemistry, Saint-Petersburg State University, Universitetskiy pr.26, Peterhof, 198504 Saint Petersburg, Russia
Interests: chemical sensors; sensor arrays; chemometrics
Dr. Andrey Legin
E-Mail Website
Guest Editor
Institute of Chemistry, Saint-Petersburg State University, Universitetskiy pr.26, Peterhof, 198504 Saint Petersburg, Russia
Interests: electronic tongues; multisensor systems

Special Issue Information

Dear Colleagues,

The field of research dealing with multisensor systems in chemical analysis is developing rapidly. In addition to traditional applications of electronic tongues and noses in quality assessment of various food products, there is a distinct growth in the application of chemical sensor arrays in medical diagnostics, environmental studies, industrial technological monitoring, and other fields. The concept of using several cross-sensitive sensors together with chemometric data processing instead of dealing with super-selective (and super-expensive) analytical instruments has proven to be very productive.

We are glad to announce this Special Issue entitled “Multisensor Systems for Chemical Analysis”. It is an effort to highlight the current state-of-the-art in the field of chemical multisensor arrays, their development, and application for a variety of real-world analytical tasks.

Dr. Dmitry Kirsanov
Dr. Andrey Legin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multisensor systems
  • sensor arrays
  • electronic tongue
  • electronic nose

Published Papers (5 papers)

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Research

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Article
Characterization of Biodegraded Ignitable Liquids by Headspace–Ion Mobility Spectrometry
Sensors 2020, 20(21), 6005; https://doi.org/10.3390/s20216005 - 23 Oct 2020
Cited by 2 | Viewed by 549
Abstract
The detection of ignitable liquids (ILs) can be crucial when it comes to determining arson cases. Such identification of ILs is a challenging task that may be affected by a number of factors. Microbial degradation is considered one of three major processes that [...] Read more.
The detection of ignitable liquids (ILs) can be crucial when it comes to determining arson cases. Such identification of ILs is a challenging task that may be affected by a number of factors. Microbial degradation is considered one of three major processes that can alter the composition of IL residues. Since biodegradation is a time related phenomenon, it should be studied at different stages of development. This article presents a method based on ion mobility spectroscopy (IMS) which has been used as an electronic nose. In particular, ion mobility sum spectrum (IMSS) in combination with chemometric techniques (hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA)) has been applied for the characterization of different biodegraded ILs. This method intends to use IMSS to identify a range of ILs regardless of their degree of biodegradation. Three ILs (diesel, gasoline and kerosene) from three different commercial brands were evaluated after remaining in a soil substrate for several lengths of time (0, 2, 5, 13 and 38 days). The HCA results showed the samples’ trend to fall into categories characterized by ILs type and biodegradation time. The LDAs allowed a 99% successful classification of the samples according to the IL type. This is the first time that an HS-IMS technique has been used to detect ILs that have undergone biodegradation processes. The results show that IMS may be a promising alternative to the current standard method based on gas-chromatography for the analysis of biodegraded ILs. Furthermore, no pretreatment of the samples nor the use of a solvent is required. Full article
(This article belongs to the Special Issue Multisensor Systems for Chemical Analysis)
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Article
Optimization of Sensors to be Used in a Voltammetric Electronic Tongue Based on Clustering Metrics
Sensors 2020, 20(17), 4798; https://doi.org/10.3390/s20174798 - 25 Aug 2020
Cited by 2 | Viewed by 630
Abstract
Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former [...] Read more.
Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former allows us to visually compare the performance of the different sensors, while the latter allows us to numerically assess the impact that the inclusion/removal of the different sensors has on the discrimination ability of the ET. The proposed methodology is based on the measurement of a pure stock solution of each of the compounds under study, and the posterior analysis by PCA/CVA with stepwise iterative removal of the sensors that demote the clustering when retained as part of the array. To illustrate and assess the potential of such an approach, the quantification of paracetamol, ascorbic acid, and uric acid mixtures were chosen as the study case. Initially, an array of eight different electrodes was considered, from which an optimal array of four sensors was derived to build the quantitative ANN model. Finally, the performance of the optimized ET was benchmarked against the results previously reported for the analysis of the same mixtures, showing improved performance. Full article
(This article belongs to the Special Issue Multisensor Systems for Chemical Analysis)
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Article
Analysis of Phenolic Content in Grape Seeds and Skins by Means of a Bio-Electronic Tongue
Sensors 2020, 20(15), 4176; https://doi.org/10.3390/s20154176 - 27 Jul 2020
Cited by 1 | Viewed by 675
Abstract
A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase [...] Read more.
A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron mediators. The presence of the phenoloxydase promotes the selectivity and specificity towards phenols. The results of multivariate analysis allowed discriminating seeds and skins according to their polyphenolic content. Partial least squares (PLS) has been used to establish regression models with parameters related to phenolic content measured by spectroscopic methods i.e., total poliphenol content (TPC) and Folin–Ciocalteu (FC) indexes. It has been shown that electronic tongue can be successfully used to predict parameters of interest with high correlation coefficients (higher than 0.99 in both calibration and prediction) and low residual errors. These values can even be improved using genetic algorithms for multivalent analysis. In this way, a fast and simple tool is available for the evaluation of these values. This advantage may be due to the fact that the electrochemical signals are directly related to the phenolic content. Full article
(This article belongs to the Special Issue Multisensor Systems for Chemical Analysis)
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Other

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Letter
Aspergillus Species Discrimination Using a Gas Sensor Array
Sensors 2020, 20(14), 4004; https://doi.org/10.3390/s20144004 - 18 Jul 2020
Cited by 4 | Viewed by 679
Abstract
The efficiency of electronic noses in detecting and identifying microorganisms has been proven by several studies. Since volatile compounds change with the growth of colonies, the identification of strains is highly dependent on the growing conditions. In this paper, the effects of growth [...] Read more.
The efficiency of electronic noses in detecting and identifying microorganisms has been proven by several studies. Since volatile compounds change with the growth of colonies, the identification of strains is highly dependent on the growing conditions. In this paper, the effects of growth were investigated with different species of Aspergillus, which is one of the most studied microorganisms because of its implications in environmental and food safety. For this purpose, we used an electronic nose previously utilized for volatilome detection applications and based on eight porphyrins-functionalized quartz microbalances. The volatile organic compounds (VOCs) released by cultured fungi were measured at 3, 5, and 10 days after the incubation. The signals from the sensors showed that the pattern of VOCs evolve with time. In particular, the separation between the three studied strains progressively decreases with time. The three strains could still be identified despite the influence of culture time. Linear Discriminant Analysis (LDA) showed an overall accuracy of 88% and 71% in the training and test sets, respectively. These results indicate that the presence of microorganisms is detectable with respect to background, however, the difference between the strains changes with the incubation time. Full article
(This article belongs to the Special Issue Multisensor Systems for Chemical Analysis)
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Letter
Differential Sensing of Saccharides Based on an Array of Fluorinated Benzosiloxaborole Receptors
Sensors 2020, 20(12), 3540; https://doi.org/10.3390/s20123540 - 22 Jun 2020
Cited by 1 | Viewed by 720
Abstract
Fluorinated benzosiloxaboroles–silicon congeners of benzoxaboroles, were synthesized and tested as molecular receptors for mono- and disaccharides. The receptors differed in the Lewis acidity of the boron center as well as in the number of potential binding sites. The calculated stability constants indicated different [...] Read more.
Fluorinated benzosiloxaboroles–silicon congeners of benzoxaboroles, were synthesized and tested as molecular receptors for mono- and disaccharides. The receptors differed in the Lewis acidity of the boron center as well as in the number of potential binding sites. The calculated stability constants indicated different binding affinity of benzosiloxaborole derivatives towards selected saccharides, enabling their classification using a receptor array-based sensing. Unique fluorescence fingerprints were created on the basis of competitive interactions of the studied receptors with both Alizarin Red S (ARS) and tested saccharide molecules. Detailed chemometric analysis of the obtained fluorescence data (based on partial least squares-discriminant analysis and hierarchical clustering analysis) provided the differential sensing of common saccharides, in particular the differentiation between glucose and fructose. In addition, DFT calculations were carried out to shed light on the binding mechanism under different pH conditions. Full article
(This article belongs to the Special Issue Multisensor Systems for Chemical Analysis)
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