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Gas Sensors: Progress, Perspectives and Challenges

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 922

Special Issue Editors


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Guest Editor
Institute of Physics CSE, Silesian University of Technology, Gliwice, Poland
Interests: photoelectron spectroscopy; molecular electronics; phthalocyanines; ultra-thin film technologies; organic photovoltaics; scanning microscopies

E-Mail Website
Guest Editor
Institute of Physics CSE, Silesian University of Technology, Gliwice, Poland
Interests: resistance and acoustic gas sensors; detection of the amount of trace of battlefield poisonous substances; sensor structures—semiconductor materials, layered configurations

Special Issue Information

Dear Colleagues,

The research on gas sensors has been of big interest for many decades due to the broad range of applications in many fields, such as environmental protection, combustion gas detection, medical diagnosis, civil safety, and food quality control. Yet, this area is still rapidly expanding. Thanks to the development of materials science and nanotechnology, new sensing materials are being constantly searched, as the modifications of well-known sensing materials are applied to improve the sensitivity, selectivity, and response times and decrease sensor operating temperature. Also, the rapid improvement of experimental techniques combined with computational power increase allow us to understand better mechanisms of particular gas detection. Thus, more efficient devices can be designed.

The Special Issue will provide a forum for the latest research activities in the field of gas sensors and review articles on the latest progress in this area. Both review articles and original research papers are solicited in, though not limited to, the following areas:

  • New materials for gas sensors;
  • New sensing techniques;
  • Novel approaches for gas sensor design and testing;
  • Models and computational simulations for the gas-sensing material interaction;
  • Processes and fabrication technologies for gas sensors.

Dr. Maciej Krzywiecki
Dr. Paulina Powroźnik
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

  • materials for gas sensors
  • gas sensor design
  • sensing techniques
  • modelling
  • simulations

Published Papers (1 paper)

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Research

24 pages, 35023 KiB  
Article
Calibration of a Low-Cost Methane Sensor Using Machine Learning
by Hazel Louise Mitchell, Simon J. Cox and Hugh G. Lewis
Sensors 2024, 24(4), 1066; https://doi.org/10.3390/s24041066 - 06 Feb 2024
Viewed by 725
Abstract
In order to combat greenhouse gas emissions, the sources of these emissions must be understood. Environmental monitoring using low-cost wireless devices is one method of measuring emissions in crucial but remote settings, such as peatlands. The Figaro NGM2611-E13 is a low-cost methane detection [...] Read more.
In order to combat greenhouse gas emissions, the sources of these emissions must be understood. Environmental monitoring using low-cost wireless devices is one method of measuring emissions in crucial but remote settings, such as peatlands. The Figaro NGM2611-E13 is a low-cost methane detection module based around the TGS2611-E00 sensor. The manufacturer provides sensitivity characteristics for methane concentrations above 300 ppm, but lower concentrations are typical in outdoor settings. This study investigates the potential to calibrate these sensors for lower methane concentrations using machine learning. Models of varying complexity, accounting for temperature and humidity variations, were trained on over 50,000 calibration datapoints, spanning 0–200 ppm methane, 5–30 °C and 40–80% relative humidity. Interaction terms were shown to improve model performance. The final selected model achieved a root-mean-square error of 5.1 ppm and an R2 of 0.997, demonstrating the potential for the NGM2611-E13 sensor to measure methane concentrations below 200 ppm. Full article
(This article belongs to the Special Issue Gas Sensors: Progress, Perspectives and Challenges)
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