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Sensors
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Applications of Spectroscopic Chemical Sensing in Challenging Environments
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Applications of Spectroscopic Chemical Sensing in Challenging Environments

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 7776

Special Issue Editors

Dr. Christopher Michael Jones
*
E-Mail Website
Guest Editor
Halliburton Energy Services
Interests: optical spectroscopy; chemical sensing; harsh environment sensing; chemometrics; multivariate optical computing; remote sensing; geochemistry
* Guest Editor would like to thank Michael L. Myrick for his help in running this SI
Prof. Dr. Michael L. Myrick

E-Mail Website
Co-Guest Editor
Department of Chemistry and Biochemistry, University of South Carolina, Columbia, USA
Interests: optical spectroscopy; chemometrics; instrumentation; method development

Special Issue Information

Dear Colleagues,

This Special Issue of Sensors will be dedicated to spectroscopic sensing for the identification of chemical components or the quantitative measurement of their concentration in challenging environments. Challenging environments include industrial and environmental settings, biomedical situations, planetary or other space fields, remote sensing determinations, harsh environments, or other environments that present measurement challenges. Examples of environmental measurement challenges include: lack of accessibility, intense electric or magnetic interference, ionizing radiation, intense pressure, high or low temperatures, shock, vibration, matrix complexity, delicate environments such as biological systems, and the need for endurance. Providing power, ruggedization, high-speed sampling, and communication and dealing with sample heterogeneity or condition-dependent spectroscopy, low-power operation, and integrated processing are additional examples of challenges, if they are due to the unique environment in which an instrument or sensor has to operate. Spectroscopic sensors are those that rely on fundamental spectroscopic characteristics of a sample, such as infrared, Raman, electronic absorption, fluorescence, multiphoton, or wave mixing, microwave, THz, x-ray, nuclear, NMR, or other characteristics. Processing techniques will also be considered. Papers on miniaturization, integrated or compressed sensing, reduction of dimensions, and extensions to higher dimensions are encouraged.

Dr. Christopher Michael Jones
Prof. Dr. Michael L. Myrick
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

  • Chemical Sensors
  • Spectroscopy
  • Challenging Environments
  • Harsh Environments

Published Papers (2 papers)

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Research

17 pages, 4649 KiB  
Communication
Identification of Multi-Class Drugs Based on Near Infrared Spectroscopy and Bidirectional Generative Adversarial Networks
by Anbing Zheng, Huihua Yang, Xipeng Pan, Lihui Yin and Yanchun Feng
Sensors 2021, 21(4), 1088; https://doi.org/10.3390/s21041088 - 05 Feb 2021
Cited by 11 | Viewed by 2240
Abstract
Drug detection and identification technology are of great significance in drug supervision and management. To determine the exact source of drugs, it is often necessary to directly identify multiple varieties of drugs produced by multiple manufacturers. Near-infrared spectroscopy (NIR) combined with chemometrics is [...] Read more.
Drug detection and identification technology are of great significance in drug supervision and management. To determine the exact source of drugs, it is often necessary to directly identify multiple varieties of drugs produced by multiple manufacturers. Near-infrared spectroscopy (NIR) combined with chemometrics is generally used in these cases. However, existing NIR classification modeling methods have great limitations in dealing with a large number of categories and spectra, especially under the premise of insufficient samples, unbalanced samples, and sensitive identification error cost. Therefore, this paper proposes a NIR multi-classification modeling method based on a modified Bidirectional Generative Adversarial Networks (Bi-GAN). It makes full utilization of the powerful feature extraction ability and good sample generation quality of Bi-GAN and uses the generated samples with obvious features, an equal number between classes, and a sufficient number within classes to replace the unbalanced and insufficient real samples in the courses of spectral classification. 1721 samples of four kinds of drugs produced by 29 manufacturers were used as experimental materials, and the results demonstrate that this method is superior to other comparative methods in drug NIR classification scenarios, and the optimal accuracy rate is even more than 99% under ideal conditions. Full article
(This article belongs to the Special Issue Applications of Spectroscopic Chemical Sensing in Challenging Environments)
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29 pages, 6635 KiB  
Article
Quantitative Long-Term Monitoring of the Circulating Gases in the KATRIN Experiment Using Raman Spectroscopy
by Max Aker, Konrad Altenmüller, Armen Beglarian, Jan Behrens, Anatoly Berlev, Uwe Besserer, Benedikt Bieringer, Klaus Blaum, Fabian Block, Beate Bornschein, Lutz Bornschein, Matthias Böttcher, Tim Brunst, Thomas C. Caldwell, Suren Chilingaryan, Wonqook Choi, Deseada D. Díaz Barrero, Karol Debowski, Marco Deffert, Martin Descher, Peter J. Doe, Otokar Dragoun, Guido Drexlin, Stephan Dyba, Frank Edzards, Klaus Eitel, Enrico Ellinger, Ralph Engel, Sanshiro Enomoto, Mariia Fedkevych, Arne Felden, Joseph F. Formaggio, Florian Fränkle, Gregg B. Franklin, Fabian Friedel, Alexander Fulst, Kevin Gauda, Woosik Gil, Ferenc Glück, Robin Größle, Rainer Gumbsheimer, Volker Hannen, Norman Haußmann, Klaus Helbing, Stephanie Hickford, Roman Hiller, David Hillesheimer, Dominic Hinz, Thomas Höhn, Thibaut Houdy, Anton Huber, Alexander Jansen, Christian Karl, Jonas Kellerer, Luke Kippenbrock, Manuel Klein, Christoph Köhler, Leonard Köllenberger, Andreas Kopmann, Marc Korzeczek, Alojz Kovalík, Bennet Krasch, Holger Krause, Luisa La Cascio, Thierry Lasserre, Thanh-Long Le, Ondřej Lebeda, Bjoern Lehnert, Alexey Lokhov, Moritz Machatschek, Emma Malcherek, Alexander Marsteller, Eric L. Martin, Matthias Meier, Christin Melzer, Susanne Mertens, Klaus Müller, Simon Niemes, Patrick Oelpmann, Alexander Osipowicz, Diana S. Parno, Alan W.P. Poon, Jose M. Lopez Poyato, Florian Priester, Oliver Rest, Marco Röllig, Carsten Röttele, R.G. Hamish Robertson, Caroline Rodenbeck, Milos Ryšavỳ, Rudolf Sack, Alejandro Saenz, Peter Schäfer, Anna Schaller (née Pollithy), Lutz Schimpf, Klaus Schlösser, Magnus Schlösser, Lisa Schlüter, Michael Schrank, Bruno Schulz, Michal Sefčík, Hendrik Seitz-Moskaliuk, Valérian Sibille, Daniel Siegmann, Martin Slezák, Felix Spanier, Markus Steidl, Michael Sturm, Menglei Sun, Helmut H. Telle, Larisa A. Thorne, Thomas Thümmler, Nikita Titov, Igor Tkachev, Drahoš Vénos, Kathrin Valerius, Ana P. Vizcaya Hernández, Marc Weber, Christian Weinheimer, Christiane Weiss, Stefan Welte, Jürgen Wendel, John F. Wilkerson, Joachim Wolf, Sascha Wüstling, Weiran Xu, Yung-Ruey Yen, Sergey Zadoroghny and Genrich Zelleradd Show full author list remove Hide full author list
Sensors 2020, 20(17), 4827; https://doi.org/10.3390/s20174827 - 26 Aug 2020
Cited by 11 | Viewed by 5039
Abstract
The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and [...] Read more.
The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and after only a few weeks of data recording, analysis of these data showed the success of KATRIN, improving on the known neutrino mass limit by a factor of about two. This success very much could be ascribed to the fact that most of the system components met, or even surpassed, the required specifications during long-term operation. Here, we report on the performance of the laser Raman (LARA) monitoring system which provides continuous high-precision information on the gas composition injected into the experiment’s windowless gaseous tritium source (WGTS), specifically on its isotopic purity of tritium—one of the key parameters required in the derivation of the electron neutrino mass. The concentrations cx for all six hydrogen isotopologues were monitored simultaneously, with a measurement precision for individual components of the order 10−3 or better throughout the complete KATRIN data taking campaigns to date. From these, the tritium purity, εT, is derived with precision of <10−3 and trueness of <3 × 10−3, being within and surpassing the actual requirements for KATRIN, respectively. Full article
(This article belongs to the Special Issue Applications of Spectroscopic Chemical Sensing in Challenging Environments)
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