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Recent Advancements in Olfaction and Electronic Nose

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

Deadline for manuscript submissions: 5 July 2024 | Viewed by 17729

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Special Issue Editors

Prof. Dr. Jun Wang

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Guest Editor

College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, China
Interests: colorimetric sensor; fluorometric sensor; electrochemical sensor; electronic nose
Special Issues, Collections and Topics in MDPI journals

Dr. Zhenbo Wei

E-Mail Website
Guest Editor

Department of Biosystems Engineering, Zhejiang University, Hangzhou 310058, China
Interests: nanocomposites; modified electrode; pattern recognition; intelligent flavor sensing system; food quality detection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The electronic nose (e-nose), which was proposed by Dodd and Persaud at Warwick University in 1982, is an array of gas sensors associated with a pattern-recognition framework that identifies and classifies odorant and non-odorant chemicals. The sensor array is the most important part of the e-nose, and the types of sensors include oxide semiconductors (MOSs), electrochemical (EC) sensors, field-effect transistors (FETs), conducting polymers (CPs), quartz crystal microbalances (QCMs), solid-state electrochemical sensors (SSESs), surface acoustic wave (SAW) sensors, optical sensors, biosensors, etc. In the past several decades, e-nose systems based on those sensors were proven to be promising tools in many fields, such as the standardization and visualization of smell, the diagnosis of diseases, the quality assessment of foods and beverages, the monitoring of environmental pollutants, process monitoring, the detection of explosives/toxicants/drugs, and scent-related industries including perfume/cosmetics/wine/coffee. However, there are still many challenges in various essential aspects, such as environmental influence, sensor sensitivity, feature extraction, drift noise, reliability and repeatability, time consumption, identification models, in-site detection, etc.

The aim of the present Special Issue is to report recent advances in electronic nose for addressing these challenges, including progress in sensor materials development, achievements in intelligent signal processing algorithms and methods, novel measurement techniques, practical applications, etc.

This Special Issue on “Recent Advancements in Olfaction and Electronic Nose” will include but is not limited to the following topics:

Fabrication of new-style gas sensors;
Development of new-style electronic nose systems;
Signal normalization, standardization, optimization, and baseline correction;
Chemometric approaches in feature extraction and data fusion;
Pattern recognition methods for classification and prediction.

Prof. Dr. Jun Wang
Dr. Zhenbo Wei
Guest Editors

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Published Papers (10 papers)

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Research

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12 pages, 7995 KiB

Open AccessArticle

CoFe₂O₄ on Mica Substrate as Flexible Ethanol Gas Sensor in Self-Heating Mode

by Jong Hun Kim, Yeong Uk Choi, Jong Hoon Jung and Jae-Hun Kim

Sensors 2024, 24(6), 1927; https://doi.org/10.3390/s24061927 - 17 Mar 2024

Viewed by 591

Abstract

In this study, a novel flexible ethanol gas sensor was created by the deposition of a CoFe₂O₄ (CFO) thin film on a thin mica substrate using the pulsed laser deposition technique. Transition electron microscopy (TEM) investigations clearly demonstrated the successful growth of CFO on the mica, where a well-defined interface was observed. Ethanol gas-sensing studies showed optimal performance at 200 °C, with the highest response of 19.2 to 100 ppm ethanol. Operating the sensor in self-heating mode under 7 V applied voltage, which corresponds to a temperature of approximately 200 °C, produced a maximal response of 19.2 to 100 ppm ethanol. This aligned with the highest responses observed during testing at 200 °C, confirming the sensor’s accuracy and sensitivity to ethanol under self-heating conditions. In addition, the sensor exhibited good selectivity to ethanol and excellent flexibility, maintaining its high performance after bending and tilting up to 5000 times. As this is the first report on flexible self-heated CFO gas sensors, we believe that this research holds great promise for the future development of high-quality sensors based on this approach. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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14 pages, 2955 KiB

Open AccessArticle

Two-Dimensional SERS Sensor Array for Identifying and Visualizing the Gas Spatial Distributions of Two Distinct Odor Sources

by Lin Chen, Hao Guo, Cong Wang, Bin Chen, Fumihiro Sassa and Kenshi Hayashi

Sensors 2024, 24(3), 790; https://doi.org/10.3390/s24030790 - 25 Jan 2024

Viewed by 663

Abstract

The spatial distribution of gas emitted from an odor source provides valuable information regarding the composition, size, and localization of the odor source. Surface-enhanced Raman scattering (SERS) gas sensors exhibit ultra-high sensitivity, molecular specificity, rapid response, and large-area detection. In this paper, a SERS gas sensor array was developed for visualizing the spatial distribution of gas evaporated from benzaldehyde and 4-ethylbenzaldehyde odor sources. The SERS spectra of the gas were collected by scanning the sensor array using an automatic detection system. The non-negative matrix factorization algorithm was employed to extract feature and concentration information at each spot on the sensor array. A heatmap image was generated for visualizing the gas spatial distribution using concentration information. Gaussian fitting was applied to process the image for localizing the odor source. The size of the odor source was estimated using the processed image. Moreover, the spectra of benzaldehyde, 4-ethylbenzaldehyde, and their gas mixture were simultaneously detected using one SERS sensor array. The feature information was recognized using a convolutional neural network with an accuracy of 98.21%. As a result, the benzaldehyde and 4-ethylbenzaldehyde odor sources were identified and visualized. Our research findings have various potential applications, including odor source localization, environmental monitoring, and healthcare. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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17 pages, 2710 KiB

Open AccessArticle

Aromatic Fingerprints: VOC Analysis with E-Nose and GC-MS for Rapid Detection of Adulteration in Sesame Oil

by Nadia Sadat Aghili, Mansour Rasekh, Hamed Karami, Omid Edriss, Alphus Dan Wilson and Jose Ramos

Sensors 2023, 23(14), 6294; https://doi.org/10.3390/s23146294 - 11 Jul 2023

Cited by 11 | Viewed by 1915

Abstract

Food quality assurance is an important field that directly affects public health. The organoleptic aroma of food is of crucial significance to evaluate and confirm food quality and origin. The volatile organic compound (VOC) emissions (detectable aroma) from foods are unique and provide a basis to predict and evaluate food quality. Soybean and corn oils were added to sesame oil (to simulate adulteration) at four different mixture percentages (25–100%) and then chemically analyzed using an experimental 9-sensor metal oxide semiconducting (MOS) electronic nose (e-nose) and gas chromatography–mass spectroscopy (GC-MS) for comparisons in detecting unadulterated sesame oil controls. GC-MS analysis revealed eleven major VOC components identified within 82–91% of oil samples. Principle component analysis (PCA) and linear detection analysis (LDA) were employed to visualize different levels of adulteration detected by the e-nose. Artificial neural networks (ANNs) and support vector machines (SVMs) were also used for statistical modeling. The sensitivity and specificity obtained for SVM were 0.987 and 0.977, respectively, while these values for the ANN method were 0.949 and 0.953, respectively. E-nose-based technology is a quick and effective method for the detection of sesame oil adulteration due to its simplicity (ease of application), rapid analysis, and accuracy. GC-MS data provided corroborative chemical evidence to show differences in volatile emissions from virgin and adulterated sesame oil samples and the precise VOCs explaining differences in e-nose signature patterns derived from each sample type. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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16 pages, 9529 KiB

Open AccessArticle

Adaptive Peptide Molecule as the Promising Highly-Efficient Gas-Sensor Material: In Silico Study

by Alexander A. Petrunin, Maxim K. Rabchinskii, Victor V. Sysoev and Olga E. Glukhova

Sensors 2023, 23(13), 5780; https://doi.org/10.3390/s23135780 - 21 Jun 2023

Cited by 1 | Viewed by 909

Abstract

Gas sensors are currently employed in various applications in fields such as medicine, ecology, and food processing, and serve as monitoring tools for the protection of human health, safety, and quality of life. Herein, we discuss a promising direction in the research and development of gas sensors based on peptides—biomolecules with high selectivity and sensitivity to various gases. Thanks to the technique developed in this work, which uses a framework based on the density-functional tight-binding theory (DFTB), the most probable adsorption centers were identified and used to describe the interaction of some analyte molecules with peptides. The DFTB method revealed that the physical adsorption of acetone, ammonium, benzene, ethanol, hexane, methanol, toluene, and trinitrotoluene had a binding energy in the range from −0.28 eV to −1.46 eV. It was found that peptides may adapt to the approaching analyte by changing their volume up to a maximum value of approx. 13%, in order to confine electron clouds around the adsorbed molecule. Based on the results obtained, the prospects for using the proposed peptide configurations in gas sensor devices are good. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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22 pages, 4457 KiB

Open AccessArticle

Gas Adsorption Response of Piezoelectrically Driven Microcantilever Beam Gas Sensors: Analytical, Numerical, and Experimental Characterizations

by Lawrence Nsubuga, Lars Duggen, Tatiana Lisboa Marcondes, Simon Høegh, Fabian Lofink, Jana Meyer, Horst-Günter Rubahn and Roana de Oliveira Hansen

Sensors 2023, 23(3), 1093; https://doi.org/10.3390/s23031093 - 17 Jan 2023

Cited by 3 | Viewed by 1413

Abstract

This work presents an approach for the estimation of the adsorbed mass of 1,5-diaminopentane (cadaverine) on a functionalized piezoelectrically driven microcantilever (PD-MC) sensor, using a polynomial developed from the characterization of the resonance frequency response to the known added mass. This work supplements the previous studies we carried out on the development of an electronic nose for the measurement of cadaverine in meat and fish, as a determinant of its freshness. An analytical transverse vibration analysis of a chosen microcantilever beam with given dimensions and desired resonance frequency (>10 kHz) was conducted. Since the beam is considered stepped with both geometrical and material non-uniformity, a modal solution for stepped beams, extendable to clamped-free beams of any shape and structure, is derived and used for free and forced vibration analyses of the beam. The forced vibration analysis is then used for transformation to an equivalent electrical model, to address the fact that the microcantilever is both electronically actuated and read. An analytical resonance frequency response to the mass added is obtained by adding simulated masses to the free end of the beam. Experimental verification of the resonance frequency response is carried out, by applying known masses to the microcantilever while measuring the resonance frequency response using an impedance analyzer. The obtained response is then transformed into a resonance frequency to the added mass response polynomial using a polynomial fit. The resulting polynomial is then verified for performance using different masses of cantilever functionalization solution. The functionalized cantilever is then exposed to different concentrations of cadaverine while measuring the resonance frequency and mass of cadaverine adsorbed estimated using the previously obtained polynomial. The result is that there is the possibility of using this approach to estimate the mass of cadaverine gas adsorbed on a functionalized microcantilever, but the effectiveness of this approach is highly dependent on the known masses used for the development of the response polynomial model. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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22 pages, 6803 KiB

Open AccessArticle

Development of a Low-Cost Electronic Nose with an Open Sensor Chamber: Application to Detection of Ciboria batschiana

by Piotr Borowik, Tomasz Grzywacz, Rafał Tarakowski, Miłosz Tkaczyk, Sławomir Ślusarski, Valentyna Dyshko and Tomasz Oszako

Sensors 2023, 23(2), 627; https://doi.org/10.3390/s23020627 - 05 Jan 2023

Cited by 5 | Viewed by 2028

Abstract

In the construction of electronic nose devices, two groups of measurement setups could be distinguished when we take into account the design of electronic nose chambers. The simpler one consists of placing the sensors directly in the environment of the measured gas, which has an important advantage, in that the composition of the gas is not changed as the gas is not diluted. However, that has an important drawback in that it is difficult to clean sensors between measurement cycles. The second, more advanced construction, contains a pneumatic system transporting the gas inside a specially designed sensor chamber. A new design of an electronic nose gas sensor chamber is proposed, which consists of a sensor chamber with a sliding chamber shutter, equipped with a simple pneumatic system for cleaning the air. The proposal combines the advantages of both approaches to the sensor chamber designs. The sensors can be effectively cleared by the flow of clean air, while the measurements are performed in the open state when the sensors are directly exposed to the measured gas. Airflow simulations were performed to confirm the efficiency of clean air transport used for sensors’ cleaning. The demonstrated electronic nose applies eight Figaro Co. MOS TGS series sensors, in which a transient response caused by a change of the exposition to measured gas, and change of heater voltage, was collected. The new electronic nose was tested as applied to the differentiation between the samples of Ciboria batschiana fungi, which is one of the most harmful pathogens of stored acorns. The samples with various coverage, thus various concentrations of the studied odor, were measured. The tested device demonstrated low noise and a good level of repetition of the measurements, with stable results during several hours of repetitive measurements during an experiment lasting five consecutive days. The obtained data allowed complete differentiation between healthy and infected samples. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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27 pages, 9438 KiB

Open AccessArticle

The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data

by Nikola Anđelić, Sandi Baressi Šegota, Ivan Lorencin and Zlatan Car

Sensors 2023, 23(1), 169; https://doi.org/10.3390/s23010169 - 24 Dec 2022

Cited by 4 | Viewed by 1649

Abstract

Fire is usually detected with fire detection systems that are used to sense one or more products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or gas. Smoke detectors are mostly used in residential areas while fire alarm systems (heat, smoke, flame, and fire gas detectors) are used in commercial, industrial and municipal areas. However, in addition to smoke, heat, infrared, ultraviolet light radiation, or gas, other parameters could indicate a fire, such as air temperature, air pressure, and humidity, among others. Collecting these parameters requires the development of a sensor fusion system. However, with such a system, it is necessary to develop a simple system based on artificial intelligence (AI) that will be able to detect fire with high accuracy using the information collected from the sensor fusion system. The novelty of this paper is to show the procedure of how a simple AI system can be created in form of symbolic expression obtained with a genetic programming symbolic classifier (GPSC) algorithm and can be used as an additional tool to detect fire with high classification accuracy. Since the investigation is based on an initially imbalanced and publicly available dataset (high number of samples classified as 1-Fire Alarm and small number of samples 0-No Fire Alarm), the idea is to implement various balancing methods such as random undersampling/oversampling, Near Miss-1, ADASYN, SMOTE, and Borderline SMOTE. The obtained balanced datasets were used in GPSC with random hyperparameter search combined with 5-fold cross-validation to obtain symbolic expressions that could detect fire with high classification accuracy. For this investigation, the random hyperparameter search method and 5-fold cross-validation had to be developed. Each obtained symbolic expression was evaluated on train and test datasets to obtain mean and standard deviation values of accuracy (

A C C

), area under the receiver operating characteristic curve (

A U C

), precision, recall, and

F 1 - s c o r e

. Based on the conducted investigation, the highest classification metric values were achieved in the case of the dataset balanced with SMOTE method. The obtained values of

\bar{A C C} \pm S D (A C C)

\bar{A U C} \pm S D (A C U)

\bar{P r e c i s i o n} \pm S D (P r e c i s i o n)

\bar{R e c a l l} \pm S D (R e c a l l)

, and

\bar{F 1 - s c o r e} \pm S D (F 1 - s c o r e)

are equal to

0.998 \pm 4.79 \times 10^{- 5}

0.998 \pm 4.79 \times 10^{- 5}

0.999 \pm 5.32 \times 10^{- 5}

0.998 \pm 4.26 \times 10^{- 5}

, and

0.998 \pm 4.796 \times 10^{- 5}

, respectively. The symbolic expression using which best values of classification metrics were achieved is shown, and the final evaluation was performed on the original dataset. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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11 pages, 9379 KiB

Open AccessArticle

Study on a Flexible Odor-Releasing Device for Olfactory Training

by Huisheng Peng, Cheng Yang, Feitong Jian and Shuo Wu

Sensors 2022, 22(23), 9519; https://doi.org/10.3390/s22239519 - 06 Dec 2022

Viewed by 1352

Abstract

Olfactory training has been shown to be effective in treating olfactory dysfunction. However, there are hardly any devices that can regularly and quantificationally release odors for olfactory training. A new odor-releasing device, which is low-cost, customizable, semi-automatic, and flexible, was developed in this study. The operation of the device can be easily achieved by the examiner, or even by the participant, simply by pressing a few buttons. A controller system with 15 individual relays was employed to master the working logic for the whole process. The device allows the examiner to isolate from the participants using the Bluetooth module in the control board. The odorants and their concentrations stored in the scent bottles can be customized by the specific requirements of different participants. The odors for training are provided by ultrasonic atomizers, which have simple structures, but powerful features. The flow rates of the odors can also be controlled by altering the rotation speed of the fans. Final experiments on practical odor generation further proved the potential of the developed device for olfactory training. More attention should be paid to the improvements of odor generation devices for olfactory training. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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35 pages, 2975 KiB

Open AccessReview

Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors

by Ali Khorramifar, Hamed Karami, Larisa Lvova, Alireza Kolouri, Ewa Łazuka, Magdalena Piłat-Rożek, Grzegorz Łagód, Jose Ramos, Jesús Lozano, Mohammad Kaveh and Yousef Darvishi

Sensors 2023, 23(12), 5716; https://doi.org/10.3390/s23125716 - 19 Jun 2023

Cited by 7 | Viewed by 2805

Abstract

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors’ applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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19 pages, 1572 KiB

Open AccessHypothesis

The Luminescence Hypothesis of Olfaction

by Kenneth Willeford

Sensors 2023, 23(3), 1333; https://doi.org/10.3390/s23031333 - 25 Jan 2023

Cited by 3 | Viewed by 2888

Abstract

A new hypothesis for the mechanism of olfaction is presented. It begins with an odorant molecule binding to an olfactory receptor. This is followed by the quantum biology event of inelastic electron tunneling as has been suggested with both the vibration and swipe card theories. It is novel in that it is not concerned with the possible effects of the tunneled electrons as has been discussed with the previous theories. Instead, the high energy state of the odorant molecule in the receptor following inelastic electron tunneling is considered. The hypothesis is that, as the high energy state decays, there is fluorescence luminescence with radiative emission of multiple photons. These photons pass through the supporting sustentacular cells and activate a set of olfactory neurons in near-simultaneous timing, which provides the temporal basis for the brain to interpret the required complex combinatorial coding as an odor. The Luminescence Hypothesis of Olfaction is the first to present the necessity of or mechanism for a 1:3 correspondence of odorant molecule to olfactory nerve activations. The mechanism provides for a consistent and reproducible time-based activation of sets of olfactory nerves correlated to an odor. The hypothesis has a biological precedent: an energy feasibility assessment is included, explaining the anosmia seen with COVID-19, and can be confirmed with existing laboratory techniques. Full article

(This article belongs to the Special Issue Recent Advancements in Olfaction and Electronic Nose)

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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: A pattern recognition method on PC for rotten detection of lemon fruits
Authors: Ruiz-Canales, A; Martínez Muñoz, G.; Conesa Celdrán, A.; Cánovas Flores, I.; Martín, D.; Oates, M.
Affiliation: 1Engineering Department, Miguel Hernández University of Elche, 03312 Orihuela, Spain 2Technological Institute of Food and Agriculture CICYTEX-INTAEX. Junta of Extremadura, Badajoz, Spain.
Abstract: The electronic nose is a device that allows identifying compounds and classifying samples by their smell. This device has a fundamental role, since it is an improvement to other sensory methods or to gas chromatography. This study was carried out with a low-cost electronic nose prototype based on in eight MQ metal oxide sensors in order to characterize samples of lemons treated with sodium benzoate at different concentrations (0.5% and 0.1% sodium benzoate concentration). The MQ sensors are designed so that each of the sensors is sensitive to one or more chemicals, such as alcohol which is the MQ3 sensor, and to detect the presence of a variety of chemicals in the air. In turn, there are more MQ, but for the experiment carried out with lemons, the parameter that we have taken into account the most is MQ135, which is the one that detects the following gases: ammonia, hydrogen sulphide and benzene. Signal data were studied to obtain a pattern recognition of rotten in lemon fruits. Network analysis were used obtain a calibration of measures among the stage of lemons. A PC application running on an Android was developed to calibrate the pattern recognition.

Title: Environmental applications of electronic nose systems based on MOX gas sensors
Authors: Ali khorramifar 1; Hamed Karami 2*; Larisa Lvova 3*; Alireza Kolouri 1; Ewa Łazuka 4; Grzegorz Łagód 5; Jesús Lozano 6; Mohammad Kaveh 2; Yousef Darvishi 7
Affiliation: 1 Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199, Iran; a.khorramifar@uma.ac.ir (A.Kh), Alirezakolouri@uma.ac.ir (A.K) 2 Department of Petroleum Engineering, Knowledge University, Erbil 44001, Iraq, hamed.wur.nl@gmail.com (H.K.); sirwankaweh@gmail.com (M.K). 3 Department of Chemical Science and Technologies, University of Rome “Tor Vergata”, 00133 Rome, Italy; larisa.lvova@uniroma2.it (L.L). 4 Faculty of Technology Fundamentals, Lublin University of Technology, Lublin, Poland; e.lazuka@pollub.pl (E. Ł). 5 Faculty of Environmental Engineering, Lublin University of Technology, Lublin, Poland g.lagod@pollub.pl (G.Ł). 6 Department of Electric Technology, Electronics and Automation, University of Extremadura, Avda. de Elvas S/n, 06006 Badajoz, Spain, jesuslozano@unex.es (J.L). 7 Department of Biosystems Engineering, University of Tehran, Tehran P.O. Box 113654117, Iran; sdarvishi@ut.ac.ir (Y.D).
Abstract: Nowadays, the electronic nose (e-nose) has gained a huge attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. E-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors, (MOXs), can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application e.g. in facility of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can, anyway be corrected through appropriate data processing methods applications.

Title: Adaptive peptide molecule as the promising highly-efficient gas-sensor material: in silico study
Authors: Alexander A. Petrunin; Maxim K. Rabchinskii; Victor V. Sysoev; Olga E. Glukhova
Affiliation: Institute of Physics, Saratov State University, Astrakhanskaya Street 83, 410012 Saratov, Russia; Department of Physics, Yuri Gagarin State Technical University of Saratov, 77 Polytechnicheskaya St., 410054 Saratov, Russia
Abstract: Gas sensors are currently employed in various applications, as medicine, ecology, food industry, and serve as monitoring tools to care about safety, healthy and life quality of humans. Herein, we discuss a promising direction in the R&D of gas sensors based on peptides - biomolecules with high selectivity and sensitivity to various gases. Thanks to the technique developed in this work in framework of tight-binding density functional theory (DFTB), the most probable adsorption centers were identified to describe the interaction of some analyte molecules with peptides. The DFTB method revealed that the binding energy characterizing the physical adsorption of acetone, ammonium, benzene, ethanol, hexane, methanol, toluene, and trinitrotoluene is in the range from –0.28 eV to –1.46 eV. It has been found that peptides may adapt to the analyte approaching via changing their volume, by a maximum value of approx. 13 %, in order to confine electron clouds around the adsorbed molecule. Based on the results obtained, the prospects for using the proposed peptide configurations in gas sensor devices are predicted.

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