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Low-Cost Chemosenors for Applications in Environment, Health, Food, and Industry Process Control

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

Deadline for manuscript submissions: 15 September 2024 | Viewed by 5225

Special Issue Editor

School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: sensors; food analysis; proteomics; nontargeted detection; chemometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Low-cost sensing refers to the use of affordable sensors to detect and measure the presence of chemicals. These sensors can be used in a wide variety of applications, including environmental monitoring, healthcare, food quality and safety, and industrial process control. Low-cost sensing technologies include, but are not limited to, the following: gas sensors in applications such as air quality monitoring, leak detection in industrial settings, or breath analysis in medical diagnostics; pH sensors used from water quality testing to food and beverage production; biosensors that use enzymes or antibodies to detect specific chemical compounds in medical diagnostics; colorimetric sensors that respond to a specific chemical reaction for integrated test kits; electronic noses with an array of chemical sensors to mimic the function of the human nose, identifying complex smells and tastes for food quality control or disease diagnosis.

Low-cost sensing can democratize access to important data and enable more widespread monitoring of chemical substances. However, like other low-cost sensing technologies, they may have limitations in terms of their accuracy, sensitivity, and selectivity compared to more expensive, laboratory-grade instruments. To overcome such disadvantages, recent developments in low-cost sensing have been driven by advances in materials science, nanotechnology, and information technologies, with key trends such as nanomaterials, printed electronics, paper-based sensors, wearable devices, the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) making sensing more accessible, affordable, and effective, opening up new possibilities for monitoring and managing chemical substances in commercial products, the environment, and our bodies.

This Special Issue will encompass original research and reviews to benefit interested readers with knowledge of the state-of-the-art in low-cost sensing.

You may choose our Joint Special Issue in Chemosensors.

Dr. Weiying Lu
Guest Editor

Manuscript Submission Information

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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

  • low-cost
  • chemosensors
  • sensors
  • food analysis
  • gas sensor
  • pH sensor
  • medical diagnostics
  • colorimetric sensors
  • electronic nose
  • healthcare
  • environmental monitoring

Published Papers (7 papers)

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Research

Jump to: Review

11 pages, 2008 KiB  
Article
The Application of Commercial Surface Acoustic Wave Radio Communication Filters as Transducers for DMMP Sensors
by Michał Grabka, Krzysztof Jasek, Mateusz Pasternak and Zygfryd Witkiewicz
Sensors 2024, 24(13), 4299; https://doi.org/10.3390/s24134299 - 2 Jul 2024
Viewed by 416
Abstract
In the present study, we used two popular radio communication SAW resonators as a base for gas sensors and tested their performance. Taking into account issues related to sensor sensitivity, the possibility of applying a sensor layer, the availability of devices, and other [...] Read more.
In the present study, we used two popular radio communication SAW resonators as a base for gas sensors and tested their performance. Taking into account issues related to sensor sensitivity, the possibility of applying a sensor layer, the availability of devices, and other related issues, we selected two popular single-port resonators with center frequencies of 315 and 433 MHz (models R315 and R433, respectively) for testing purposes. Both resonators were equipped with a sensitive film of hexafluoroisopropanol-substituted polydimethylsiloxane, a material that selectively absorbs molecules with a high ability to form basic hydrogen bonds. Fabricated sensors were used to detect trace amounts of dimethyl methylphosphonate (DMMP) vapor, which has often been used in similar studies as a nerve chemical warfare agent simulant. Sensors using both devices loaded with sensor layers of an optimal thickness rapidly reacted to a gas containing DMMP at a concentration of 3 mg/m3, generating a stable analytical signal ranging from several to several dozen kilohertz. In the case of R433, the frequency signal was 20.5 kHz at 1 min from the beginning of exposure to DMMP. The obtained results showed that the used transducers exhibited good performance as a base for gas sensors. Finally, their suitability for sensing applications was confirmed by a comparison with the results obtained in previous similar studies. Full article
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17 pages, 3289 KiB  
Article
Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar
by Giulia Magnani, Chiara Giliberti, Davide Errico, Mattia Stighezza, Simone Fortunati, Monica Mattarozzi, Andrea Boni, Valentina Bianchi, Marco Giannetto, Ilaria De Munari, Stefano Cagnoni and Maria Careri
Sensors 2024, 24(11), 3586; https://doi.org/10.3390/s24113586 - 2 Jun 2024
Viewed by 762
Abstract
The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with [...] Read more.
The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices. Full article
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23 pages, 6711 KiB  
Article
Linear and Non-Linear Modelling Methods for a Gas Sensor Array Developed for Process Control Applications
by Riadh Lakhmi, Marc Fischer, Quentin Darves-Blanc, Rouba Alrammouz, Mathilde Rieu and Jean-Paul Viricelle
Sensors 2024, 24(11), 3499; https://doi.org/10.3390/s24113499 - 29 May 2024
Viewed by 366
Abstract
New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H2, CO, CH4, and CO [...] Read more.
New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H2, CO, CH4, and CO2. Because of the non-selectivity of the sensors, a multi-sensor matrix has been built in this work based on commercial sensors having very different transduction principles, and, therefore, providing richer information. To treat the data provided by the sensor array and extract gas mixture composition (nature and concentration), linear (Multi Linear Regression—Ordinary Least Square “MLR-OLS” and Multi Linear Regression—Partial Least Square “MLR-PLS”) and non-linear (Artificial Neural Network “ANN”) models have been built. The MLR-OLS model was disqualified during the training phase since it did not show good results even in the training phase, which could not lead to effective predictions during the validation phase. Then, the performances of MLR-PLS and ANN were evaluated with validation data. Good concentration predictions were obtained in both cases for all the involved analytes. However, in the case of methane, better prediction performances were obtained with ANN, which is consistent with the fact that the MOX sensor’s response to CH4 is logarithmic, whereas only linear sensor responses were obtained for the other analytes. Finally, prediction tests performed on one-year aged sensor platforms revealed that PLS model predictions on aged platforms mainly suffered from concentration offsets and that ANN predictions mainly suffered from a drop of sensitivity. Full article
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15 pages, 3098 KiB  
Article
A Non-Disposable Electrochemical Sensor Based on Laser-Synthesized Pd/LIG Nanocomposite-Modified Screen-Printed Electrodes for the Detection of H2O2
by Ruijie Song, Jianwei Zhang, Ge Yang, Yu Wu, Jun Yu and Huichao Zhu
Sensors 2024, 24(7), 2043; https://doi.org/10.3390/s24072043 - 22 Mar 2024
Cited by 1 | Viewed by 873
Abstract
There have been many studies on the significant correlation between the hydrogen peroxide content of different tissues or cells in the human body and the risk of disease, so the preparation of biosensors for detecting hydrogen peroxide concentration has been a hot topic [...] Read more.
There have been many studies on the significant correlation between the hydrogen peroxide content of different tissues or cells in the human body and the risk of disease, so the preparation of biosensors for detecting hydrogen peroxide concentration has been a hot topic for researchers. In this paper, palladium nanoparticles (PdNPs) and laser-induced graphene (LIG) were prepared by liquid-phase pulsed laser ablation and laser-induced technology, respectively. The complexes were prepared by stirring and used for the modification of screen-printed electrodes to develop a non-enzymatic hydrogen peroxide biosensor that is low cost and mass preparable. The PdNPs prepared with anhydrous ethanol as a solvent have a uniform particle size distribution. The LIG prepared by laser direct writing has good electrical conductivity, and its loose porous structure provides more adsorption sites. The electrochemical properties of the modified electrode were characterized by cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy. Compared with bare screen-printed electrodes, the modified electrodes are more sensitive for the detection of hydrogen peroxide. The sensor has a linear response range of 5 µM–0.9 mM and 0.9 mM–5 mM. The limit of detection is 0.37 µM. The above conclusions indicate that the hydrogen peroxide electrochemical biosensor prepared in this paper has great advantages and potential in electrochemical catalysis. Full article
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12 pages, 3300 KiB  
Article
Room Temperature NH3 Selective Gas Sensors Based on Double-Shell Hierarchical SnO2@polyaniline Composites
by Yuan Qu, Haotian Zheng, Yuhua Lei, Ziwen Ding, Siqi Li, Song Liu and Wei Ji
Sensors 2024, 24(6), 1824; https://doi.org/10.3390/s24061824 - 12 Mar 2024
Cited by 1 | Viewed by 906
Abstract
Morphology and structure play a crucial role in influencing the performance of gas sensors. Hollow structures, in particular, not only increase the specific surface area of the material but also enhance the collision frequency of gases within the shell, and have been studied [...] Read more.
Morphology and structure play a crucial role in influencing the performance of gas sensors. Hollow structures, in particular, not only increase the specific surface area of the material but also enhance the collision frequency of gases within the shell, and have been studied in depth in the field of gas sensing. Taking SnO2 as an illustrative example, a dual-shell structure SnO2 (D-SnO2) was prepared. D-SnO2@Polyaniline (PANI) (DSPx, x represents D-SnO2 molar content) composites were synthesized via the in situ oxidative polymerization method, and simultaneously deposited onto a polyethylene terephthalate (PET) substrate to fabricate an electrode-free, flexible sensor. The impact of the SnO2 content on the sensing performance of the DSPx-based sensor for NH3 detection at room temperature was discussed. The results showed that the response of a 20 mol% D-SnO2@PANI (DSP20) sensor to 100 ppm NH3 at room temperature is 37.92, which is 5.1 times higher than that of a pristine PANI sensor. Moreover, the DSP20 sensor demonstrated a rapid response and recovery rate at the concentration of 10 ppm NH3, with response and recovery times of 182 s and 86 s. Full article
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13 pages, 3558 KiB  
Article
Synergistically Enhanced Electrochemical Sensing of Food Adulterant in Milk Sample at Erbium Vanadate/Graphitic Carbon Nitride Composite
by U. G. Anushka Sanjeewani and Sea-Fue Wang
Sensors 2024, 24(6), 1808; https://doi.org/10.3390/s24061808 - 11 Mar 2024
Viewed by 737
Abstract
Dimetridazole (DMZ), a nitroimidazole derivative, is a notable antibiotic that has garnered growing interest in the medical community owing to its noteworthy pharmacological and toxicological properties. Increasing interest is being directed toward developing high-performance sensors for continuous monitoring of DMZ in food samples. [...] Read more.
Dimetridazole (DMZ), a nitroimidazole derivative, is a notable antibiotic that has garnered growing interest in the medical community owing to its noteworthy pharmacological and toxicological properties. Increasing interest is being directed toward developing high-performance sensors for continuous monitoring of DMZ in food samples. This research investigated an electrochemical sensor-based nano-sized ErVO4 attached to a sheet-like g-CN-coated glassy carbon electrode to determine dimetridazole (DMZ). The chemical structure and morphological characterization of synthesized ErVO4@g-CN were analyzed with XRD, FTIR, TEM, and EDS. Irregular shapes of ErVO4 nanoparticles are approximately 15 nm. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) were followed to examine the electrochemical performance in pH 7 phosphate buffer solution for higher performance. This electrochemical sensor showed a low detection limit (LOD) of 1 nM over a wide linear range of 0.5 to 863.5 µM. Also, selectivity, stability, repeatability, and reproducibility studies were investigated. Furthermore, this electrochemical sensor was applied to real-time milk sample analysis for the detection of analytes. Full article
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Review

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18 pages, 4995 KiB  
Review
Enhancing Sensitivity in Gas Detection: Porous Structures in Organic Field-Effect Transistor-Based Sensors
by Soohwan Lim, Ky Van Nguyen and Wi Hyoung Lee
Sensors 2024, 24(9), 2862; https://doi.org/10.3390/s24092862 - 30 Apr 2024
Viewed by 706
Abstract
Gas detection is crucial for detecting environmentally harmful gases. Organic field-effect transistor (OFET)-based gas sensors have attracted attention due to their promising performance and potential for integration into flexible and wearable devices. This review examines the operating mechanisms of OFET-based gas sensors and [...] Read more.
Gas detection is crucial for detecting environmentally harmful gases. Organic field-effect transistor (OFET)-based gas sensors have attracted attention due to their promising performance and potential for integration into flexible and wearable devices. This review examines the operating mechanisms of OFET-based gas sensors and explores methods for improving sensitivity, with a focus on porous structures. Researchers have achieved significant enhancements in sensor performance by controlling the thickness and free volume of the organic semiconductor layer. Additionally, innovative fabrication techniques like self-assembly and etching have been used to create porous structures, facilitating the diffusion of target gas molecules, and improving sensor response and recovery. These advancements in porous structure fabrication suggest a promising future for OFET-based gas sensors, offering increased sensitivity and selectivity across various applications. Full article
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