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Chemometrics in Sensors Technology
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Chemometrics in Sensors Technology

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

Deadline for manuscript submissions: closed (10 July 2022) | Viewed by 9834

Special Issue Editors

Dr. Fabio Zaza

E-Mail Website
Guest Editor
ENEA- Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Rome, Italy
Interests: nanomaterials; gas sensors; biosensors; chemometrics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fabio Leccese

E-Mail Website
Guest Editor
Ricercatore di Misure Elettriche ed Elettroniche, Università degli Studi "Roma Tre", Rome, Italy
Interests: measurement chains; sensors; AUV; reliability; integrated logistic support; neural networks; power quality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Chemometrics is the chemical discipline that uses mathematical and statistical approaches to design experiments and provide relevant chemical information by analyzing complex experimental datasets. This discipline provides a useful tool for selecting operating conditions for sensor devices, optimizing the synthesis process of sensing materials, computing mathematical models for multivariate calibration of sensor devices, and performing pattern recognition methods for sensor array data analysis.

Quality by design is a tool used for optimizing multifactor processes via the design of experiments and the multivariate analysis of collected data. Since the characteristics of sensing materials depend on synthesis factors and the performance of sensor devices depends on operating conditions, quality by design ensures the quality of sensor devices because it selects synthesis parameters for materials with suitable properties and sensor operating parameters to perform analyses under useful experimental settings.

Multivariate analysis is a method used for performing a multifactor calibration for more accurate analysis considering many factors affecting the experimental signal output from the sensor.

Chemometrics plays a key role in electronics and in the nose. These devices are composed of three main components: a pattern recognition analyzer, a sensor array, and a signal processor. The former is software for the chemometric analysis of sensor array data. Numerous chemometric methods for sensor array data analysis are available to discriminate between different samples, such as principal component analysis, discriminant function analysis, hierarchical cluster analysis, soft independent modeling by class analogy, partial least squares, artificial neural networks, and support vector machines.

Dr. Fabio Zaza
Prof. Dr. Fabio Leccese
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 submissions that pass pre-check are 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 2600 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

  • quality by design
  • electronic tongue
  • electronic nose
  • multivariate calibration
  • pattern recognition
  • differential sensing
  • principal component analysis
  • artificial neural networks
  • support vector machines

Published Papers (3 papers)

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Research

9 pages, 12175 KiB  
Article
Colorimetric Sensor Based on Hydroxypropyl Cellulose for Wide Temperature Sensing Range
by Hoon Yi, Sang-Hyeon Lee, Dana Kim, Hoon Eui Jeong and Changyoon Jeong
Sensors 2022, 22(3), 886; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030886 - 24 Jan 2022
Cited by 6 | Viewed by 4977
Abstract
Recently, temperature monitoring with practical colorimetric sensors has been highlighted because they can directly visualize the temperature of surfaces without any power sources or electrical transducing systems. Accordingly, several colorimetric sensors that convert the temperature change into visible color alteration through various physical [...] Read more.
Recently, temperature monitoring with practical colorimetric sensors has been highlighted because they can directly visualize the temperature of surfaces without any power sources or electrical transducing systems. Accordingly, several colorimetric sensors that convert the temperature change into visible color alteration through various physical and chemical mechanisms have been proposed. However, the colorimetric temperature sensors that can be used at subzero temperatures and detect a wide range of temperatures have not been sufficiently explored. Here, we present a colorimetric sensory system that can detect and visualize a wide range of temperatures, even at a temperature below 0 °C. This system was developed with easily affordable materials via a simple fabrication method. The sensory system is mainly fabricated using hydroxypropyl cellulose (HPC) and ethylene glycol as the coolant. In this system, HPC can self-assemble into a temperature-responsive cholesteric liquid crystalline mesophase, and ethylene glycol can prevent the mesophase from freezing at low temperatures. The colorimetric sensory system can quantitatively visualize the temperature and show repeatability in the temperature change from −20 to 25 °C. This simple and reliable sensory system has great potential as a temperature-monitoring system for structures exposed to real environments. Full article
(This article belongs to the Special Issue Chemometrics in Sensors Technology)
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18 pages, 5971 KiB  
Article
Development of an Optical Method to Monitor Nitrification in Drinking Water
by Sharif Hossain, David Cook, Christopher W. K. Chow and Guna A. Hewa
Sensors 2021, 21(22), 7525; https://0-doi-org.brum.beds.ac.uk/10.3390/s21227525 - 12 Nov 2021
Cited by 10 | Viewed by 2028
Abstract
Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH2Cl) residual. The decay of monochloramine releases ammonia (NH3), which is converted to nitrite (NO2−) and nitrate [...] Read more.
Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH2Cl) residual. The decay of monochloramine releases ammonia (NH3), which is converted to nitrite (NO2−) and nitrate (NO3−) through a biological oxidation process. During the course of monochloramine decay and the production of nitrite and nitrate, the spectral fingerprint is observed to change within the wavelength region sensitive to these species. In addition, chloraminated drinking water will contain natural organic matter (NOM), which also has a spectral fingerprint. To assess the nitrification status, the combined nitrate and nitrite absorbance fingerprint was isolated from the total spectra. A novel method is proposed here to isolate their spectra and estimate their combined concentration. The spectral fingerprint of pure monochloramine solution at different concentrations indicated that the absorbance difference between two concentrations at a specific wavelength can be related to other wavelengths by a linear function. It is assumed that the absorbance reduction in drinking water spectra due to monochloramine decay will follow a similar pattern as in ultrapure water. Based on this criteria, combined nitrate and nitrite spectra were isolated from the total spectrum. A machine learning model was developed using the support vector regression (SVR) algorithm to relate the spectral features of pure nitrate and nitrite with their concentrations. The model was used to predict the combined nitrate and nitrite concentration for a number of test samples. Out of these samples, the nitrified sample showed an increasing trend of combined nitrate and nitrite productions. The predicted values were matched with the observed concentrations, and the level of precision by the method was ± 0.01 mg-N L−1. This method can be implemented in chloraminated distribution systems to monitor and manage nitrification. Full article
(This article belongs to the Special Issue Chemometrics in Sensors Technology)
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13 pages, 3382 KiB  
Article
Self-Powered Flexible Sour Sensor for Detecting Ascorbic Acid Concentration Based on Triboelectrification/Enzymatic-Reaction Coupling Effect
by Tianming Zhao, Qi Wang and An Du
Sensors 2021, 21(2), 373; https://0-doi-org.brum.beds.ac.uk/10.3390/s21020373 - 07 Jan 2021
Cited by 9 | Viewed by 2382
Abstract
Artificial sensory substitution systems can mimic human sensory organs through replacing the sensing process of a defective sensory receptor and transmitting the sensing signal into the nervous system. Here, we report a self-powered flexible gustation sour sensor for detecting ascorbic acid concentration. The [...] Read more.
Artificial sensory substitution systems can mimic human sensory organs through replacing the sensing process of a defective sensory receptor and transmitting the sensing signal into the nervous system. Here, we report a self-powered flexible gustation sour sensor for detecting ascorbic acid concentration. The material system comprises of Na2C2O4-Ppy with AAO modification, PDMS and Cu wire mesh. The working mechanism is contributed to the triboelectrification/enzymatic-reaction coupling effect, and the device can collect weak energy from body movements and directly output triboelectric current without any external power-units. The triboelectric output is affected by AA concentration, and the response is up to 34.82% against 15.625 mM/L of AA solution. Furthermore, a practical application in detecting ascorbic acid concentration of different drinks has been demonstrated. This work can encourage the development of wearable flexible electronics and this self-powered sour sensor has the potential that can be acted as a kind of gustatory receptors to build electronic tongues. Full article
(This article belongs to the Special Issue Chemometrics in Sensors Technology)
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