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Special Issue "I3S 2017 Selected Papers"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: 28 February 2018

Special Issue Editors

Guest Editor
Prof. Dr. Nicole Jaffrezic-Renault

Institute of Analytical Sciences, UMR CNRS 5280, Department LSA, 5 Rue de La Doua, 69100 Villeurbanne, France
Website | E-Mail
Phone: +33472448306
Fax: +33 472 43 12 06
Interests: biosensors; impedance; immunosensors; conductometric sensors; enzymatic sensors; affinity sensors
Guest Editor
Prof. Dr. Evgeny Katz

Department of Chemistry & Biomolecular Science, Clarkson University, 8 Clarkson Avenue, Box 5810, Potsdam, New York 13699-5810, USA
Website | E-Mail
Phone: 1-315-268-4421
Fax: +1 315 268 6610
Interests: bioelectronics; bionanotechnology; bioelectrochemistry; biosensors; enzymes; self-assembling; monolayers; modified electrodes

Special Issue Information

Dear Colleagues,

This Special Issue was created in collaboration with the 5th International Symposium on Sensor Science (I3S 2017), held from 27 to 29 September 2017 in Barcelona, Spain. It comprises 5 topical sessions that covers the most exciting aspects of sensor science (see below for a list of topics). The conference participants are cordially invited to contribute a full manuscript to this special issue and receive a 20% discount on the publishing fees.

Session 1: Biosensors
Session Chair: Prof. Dr. Evgeny Katz, Clarkson University, Potsdam, NY, USA

Session 2: Chemosensors
Session Chair: Prof. Dr. Vladimir M. Mirsky, Brandenburg University of Technology Cottbus, Senftenberg, Germany

Session 3: Bio-inspired and Bio-based Strategies for Sensing and Fluidics
Session Chair: Prof. Dr. Dermot Diamond, Dublin City University, Dublin, Ireland

Session 4: Sensors for Structures
Session Chair: Prof. Dr. Jandro L. Abot, The Catholic University of America, Washington, DC, USA

Session 5: Sensor Applications
Session Chair: Dr. Stefano Mariani, Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy

Prof. Dr. Nicole Jaffrezic-Renault
Prof. Dr. Evgeny Katz
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 monthly 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 1800 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.

Published Papers (7 papers)

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Displaying articles 1-7
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Research

Open AccessArticle Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks
Sensors 2018, 18(2), 606; doi:10.3390/s18020606
Received: 29 November 2017 / Revised: 10 February 2018 / Accepted: 13 February 2018 / Published: 16 February 2018
PDF Full-text (4430 KB) | HTML Full-text | XML Full-text
Abstract
Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a
[...] Read more.
Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Improvement in Limit of Detection of Enzymatic Biogas Sensor Utilizing Chromatography Paper for Breath Analysis
Sensors 2018, 18(2), 440; doi:10.3390/s18020440
Received: 1 December 2017 / Revised: 19 January 2018 / Accepted: 25 January 2018 / Published: 2 February 2018
PDF Full-text (1360 KB) | HTML Full-text | XML Full-text
Abstract
Breath analysis is considered to be an effective method for point-of-care diagnosis due to its noninvasiveness, quickness and simplicity. Gas sensors for breath analysis require detection of low-concentration substances. In this paper, we propose that reduction of the background current improves the limit
[...] Read more.
Breath analysis is considered to be an effective method for point-of-care diagnosis due to its noninvasiveness, quickness and simplicity. Gas sensors for breath analysis require detection of low-concentration substances. In this paper, we propose that reduction of the background current improves the limit of detection of enzymatic biogas sensors utilizing chromatography paper. After clarifying the cause of the background current, we reduced the background current by improving the fabrication process of the sensors utilizing paper. Finally, we evaluated the limit of detection of the sensor with the sample vapor of ethanol gas. The experiment showed about a 50% reduction of the limit of detection compared to previously-reported sensor. This result presents the possibility of the sensor being applied in diagnosis, such as for diabetes, by further lowering the limit of detection. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy
Sensors 2018, 18(2), 354; doi:10.3390/s18020354
Received: 20 December 2017 / Revised: 16 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
PDF Full-text (2169 KB) | HTML Full-text | XML Full-text
Abstract
This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties
[...] Read more.
This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)6]3−/[Fe(CN)6]4− as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM−1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia
Sensors 2018, 18(1), 289; doi:10.3390/s18010289
Received: 18 December 2017 / Revised: 17 January 2018 / Accepted: 18 January 2018 / Published: 19 January 2018
PDF Full-text (3184 KB) | HTML Full-text | XML Full-text
Abstract
This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity
[...] Read more.
This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., x- and y-axis) by increasing the MMI in the x- and y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Feasibility of Detecting Natural Frequencies of Hydraulic Turbines While in Operation, Using Strain Gauges
Sensors 2018, 18(1), 174; doi:10.3390/s18010174
Received: 19 December 2017 / Revised: 8 January 2018 / Accepted: 9 January 2018 / Published: 10 January 2018
PDF Full-text (11428 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Nowadays, hydropower plays an essential role in the energy market. Due to their fast response and regulation capacity, hydraulic turbines operate at off-design conditions with a high number of starts and stops. In this situation, dynamic loads and stresses over the structure are
[...] Read more.
Nowadays, hydropower plays an essential role in the energy market. Due to their fast response and regulation capacity, hydraulic turbines operate at off-design conditions with a high number of starts and stops. In this situation, dynamic loads and stresses over the structure are high, registering some failures over time, especially in the runner. Therefore, it is important to know the dynamic response of the runner while in operation, i.e., the natural frequencies, damping and mode shapes, in order to avoid resonance and fatigue problems. Detecting the natural frequencies of hydraulic turbine runners while in operation is challenging, because they are inaccessible structures strongly affected by their confinement in water. Strain gauges are used to measure the stresses of hydraulic turbine runners in operation during commissioning. However, in this paper, the feasibility of using them to detect the natural frequencies of hydraulic turbines runners while in operation is studied. For this purpose, a large Francis turbine runner (444 MW) was instrumented with several strain gauges at different positions. First, a complete experimental strain modal testing (SMT) of the runner in air was performed using the strain gauges and accelerometers. Then, the natural frequencies of the runner were estimated during operation by means of analyzing accurately transient events or rough operating conditions. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Amplified Detection of the Aptamer–Vanillin Complex with the Use of Bsm DNA Polymerase
Sensors 2018, 18(1), 49; doi:10.3390/s18010049
Received: 30 November 2017 / Revised: 19 December 2017 / Accepted: 20 December 2017 / Published: 26 December 2017
PDF Full-text (2022 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The electrochemical detection of interactions between aptamers and low-molecular-weight targets often lacks sensitivity. Signal amplification improves the detection of the aptamer-analyte complex; Bsm DNA polymerase was used to amplify the signal from the interaction of vanillin and its aptamer named Van_74 on an
[...] Read more.
The electrochemical detection of interactions between aptamers and low-molecular-weight targets often lacks sensitivity. Signal amplification improves the detection of the aptamer-analyte complex; Bsm DNA polymerase was used to amplify the signal from the interaction of vanillin and its aptamer named Van_74 on an ion-sensitive field-effect transistor (ISFET)-based biosensor. The aptamer was immobilized on the ISFET sensitive surface. A short DNA probe was hybridized with the aptamer and dissociated from it upon vanillin addition. A free probe interacted with a special DNA molecular beacon initiated the Bsm DNA polymerase reaction that was detected by ISFET. A buffer solution suitable for both aptamer action and Bsm DNA polymerase activity was determined. The ISFET was shown to detect the Bsm DNA polymerase reaction under the selected conditions. Vanillin at different concentrations (1 × 10−6–1 × 10−8 M) was detected using the biosensor with signal amplification. The developed detection system allowed for the determination of vanillin, starting at a 10−8 M concentration. Application of the Bsm DNA polymerase resulted in a 15.5 times lower LoD when compared to the biosensor without signal amplification (10.1007/s00604-017-2586-4). Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Analytical Parameters of an Amperometric Glucose Biosensor for Fast Analysis in Food Samples
Sensors 2017, 17(11), 2620; doi:10.3390/s17112620
Received: 28 September 2017 / Revised: 2 November 2017 / Accepted: 6 November 2017 / Published: 14 November 2017
PDF Full-text (1817 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Amperometric biosensors based on the use of glucose oxidase (GOx) are able to combine the robustness of electrochemical techniques with the specificity of biological recognition processes. However, very little information can be found in literature about the fundamental analytical parameters of these sensors.
[...] Read more.
Amperometric biosensors based on the use of glucose oxidase (GOx) are able to combine the robustness of electrochemical techniques with the specificity of biological recognition processes. However, very little information can be found in literature about the fundamental analytical parameters of these sensors. In this work, the analytical behavior of an amperometric biosensor based on the immobilization of GOx using a hydrogel (Chitosan) onto highly ordered titanium dioxide nanotube arrays (TiO2NTAs) has been evaluated. The GOx–Chitosan/TiO2NTAs biosensor showed a sensitivity of 5.46 μA·mM−1 with a linear range from 0.3 to 1.5 mM; its fundamental analytical parameters were studied using a commercial soft drink. The obtained results proved sufficient repeatability (RSD = 1.9%), reproducibility (RSD = 2.5%), accuracy (95–105% recovery), and robustness (RSD = 3.3%). Furthermore, no significant interferences from fructose, ascorbic acid and citric acid were obtained. In addition, the storage stability was further examined, after 30 days, the GOx–Chitosan/TiO2NTAs biosensor retained 85% of its initial current response. Finally, the glucose content of different food samples was measured using the biosensor and compared with the respective HPLC value. In the worst scenario, a deviation smaller than 10% was obtained among the 20 samples evaluated. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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