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Nanomaterial-Based Gas Sensors for Environmental, Agroalimentary, Safety and Industrial Applications
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Nanomaterial-Based Gas Sensors for Environmental, Agroalimentary, Safety and Industrial Applications

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

Deadline for manuscript submissions: closed (10 October 2023) | Viewed by 4626

Special Issue Editors

Prof. Dr. Giorgio Sberveglieri

E-Mail Website
Guest Editor
Department of Information Engineering (DII), University of Brescia, Via Branze 38, I25133 Brescia, Italy
Interests: chemical sensors; nanomaterials; materials characterizations; nanowire; carbon nanofibers; electrochemical capacitors; screen printing; heterojunctions; RGTO; VLS
Special Issues, Collections and Topics in MDPI journals
Dr. Veronica Sberveglieri

E-Mail Website
Guest Editor
1. CNR-IBBR, Institute of Bioscience and Bioresources, 50019 Sesto Fiorentino (FI), Italy
2. Department of Life Science, University of Modena and Reggio Emilia, 41121 Modena, Italy
Interests: chemical sensor systems; food quality and safety; food traceability; food authenticity; machine learning; IoT; new sensing materials; VOCs; environmental quality; indoor and outdoor
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, gas sensors have been widely used in different fields, such as human health, environmental monitoring, automotive, and IoT in general.

The aim of this Special Issue is to highlight research with the potential to advance in new directions regarding new nanomaterials applied in gas sensor technology/devices.

In particular, we plan to focus our attention on gas sensor applications for environmental (indoor and outdoor), agroalimentary (from raw materials to processed), safety, and industrial applications.

We cordially invite you to submit original research systematically examining new sensing materials or preparation/integration methods. 

Sensors can support, help, and increase the food sector’s abilities, as well as increasingly become more user-friendly and closer to real needs.

The covered topics will be extended to sensing devices, networks, and an array of gas sensors.

Potential gas sensor topics include, but are not limited to, the following:

  • Quality of line/at line control from farm to fork;
  • Shelf-life measurement;
  • Risk assessment in indoor and outdoor situations;
  • IoT—Internet of Things;
  • Monitoring the presence of harmful chemical compounds (neoformation and the lack of);
  • Quality of line/at line control from farm to fork;
  • Shelf-life measurement;
  • Risk assessment in indoor and outdoor situations;
  • IoT—Internet of Things;
  • Monitoring the presence of harmful chemical compounds (neoformation and the lack of);
  • Online control in the process industry chain;
  • Geographical and quality characterization in raw materials.

Prof. Dr. Giorgio Sberveglieri
Dr. Veronica Sberveglieri
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.

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Published Papers (2 papers)

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Research

13 pages, 10395 KiB  
Article
Leak Detection and Localization in Multi-Grid Space Using Improved Gaussian Plume Model
by Daquan Li, Gaigai Liu and Zhaoyong Mao
Sensors 2023, 23(13), 6209; https://doi.org/10.3390/s23136209 - 7 Jul 2023
Cited by 3 | Viewed by 1674
Abstract
Leak detection and localization of liquid or gas is of great significance to avoid potential danger and reduce the waste of resources. Leak detection and localization methods are varied and uniquely suited to specific application scenarios. The existing methods are primarily applied to [...] Read more.
Leak detection and localization of liquid or gas is of great significance to avoid potential danger and reduce the waste of resources. Leak detection and localization methods are varied and uniquely suited to specific application scenarios. The existing methods are primarily applied to conventional pressurized pipelines and open areas, and there are few methods suitable for multi-grid spaces. In this paper, a gas diffusion model applied to multi-grid space is constructed, and a method for leak detection and localization using the concentration gradient of characteristic gas is proposed according to the prediction behavior. The Gaussian plume model is selected due to its advantages of simplicity and the interpretation of gas diffusion behavior is closer to reality; the expression of the improved model is also obtained. To verify the correctness of the model and the applicability of the localization method, taking the coolant leakage in the circuit system as an example, three experiments with different source strengths were repeated. The fitting correlation coefficients between the gas concentration data of the three experiments and the model are 0.995, 0.997 and 0.997, respectively. The experimental results show that the model has a strong correlation with the real plume behavior, and it is reasonable to use the gas concentration gradient for the localization of the leak source. This study provides a reference for future research on the leak detection and localization of gas- or liquid-containing volatile substances in a complex multi-grid space. Full article
(This article belongs to the Special Issue Nanomaterial-Based Gas Sensors for Environmental, Agroalimentary, Safety and Industrial Applications)
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11 pages, 2589 KiB  
Article
Real Time Monitoring of Wine Vinegar Supply Chain through MOX Sensors
by Dario Genzardi, Giuseppe Greco, Estefanía Núñez-Carmona and Veronica Sberveglieri
Sensors 2022, 22(16), 6247; https://doi.org/10.3390/s22166247 - 19 Aug 2022
Cited by 10 | Viewed by 2174
Abstract
Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are [...] Read more.
Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are converted in ethanol and lower metabolites by the yeast action, generally Saccharomyces cerevisiae. This was performed through a technique that is expanding more and more, the so-called “pied de cuve”. The second step is an acetic fermentation where acetic acid bacteria (AAB) action causes the conversion of ethanol into acetic acid. Overall, the aim of this research is to follow wine vinegar production step by step through the volatiloma analysis by metal oxide semiconductor MOX sensors developed by Nano Sensor Systems S.r.l. This work is based on wine vinegar monitored from the grape must to the formed vinegar. The monitoring lasted 4 months and the analyses were carried out with a new generation of Electronic Nose (EN) engineered by Nano Sensor Systems S.r.l., called Small Sensor Systems Plus (S3+), equipped with an array of six gas MOX sensors with different sensing layers each. In particular, real-time monitoring made it possible to follow and to differentiate each step of the vinegar production. The principal component analysis (PCA) method was the statistical multivariate analysis utilized to process the dataset obtained from the sensors. A closer look to PCA graphs affirms how the sensors were able to cluster the production steps in a chronologically correct manner. Full article
(This article belongs to the Special Issue Nanomaterial-Based Gas Sensors for Environmental, Agroalimentary, Safety and Industrial Applications)
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