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14 pages, 6763 KiB

Open AccessArticle

Mo-Doped LaFeO₃ Gas Sensors with Enhanced Sensing Performance for Triethylamine Gas

by Chenyu Shen, Hongjian Liang, Ziyue Zhao, Suyi Guo, Yuxiang Chen, Zhenquan Tan, Xue-Zhi Song and Xiaofeng Wang

Sensors 2024, 24(15), 4851; https://doi.org/10.3390/s24154851 - 25 Jul 2024

Viewed by 782

Abstract

Triethylamine is a common volatile organic compound (VOC) that plays an important role in areas such as organic solvents, chemical industries, dyestuffs, and leather treatments. However, exposure to triethylamine atmosphere can pose a serious threat to human health. In this study, gas-sensing semiconductor [...] Read more.

Triethylamine is a common volatile organic compound (VOC) that plays an important role in areas such as organic solvents, chemical industries, dyestuffs, and leather treatments. However, exposure to triethylamine atmosphere can pose a serious threat to human health. In this study, gas-sensing semiconductor materials of LaFeO₃ nano materials with different Mo-doping ratios were synthesized by the sol–gel method. The crystal structures, micro morphologies, and surface states of the prepared samples were characterized by XRD, SEM, and XPS, respectively. The gas-sensing tests showed that the Mo doping enhanced the gas-sensing performance of LaFeO₃. Especially, the 4% Mo-doped LaFeO₃ exhibited the highest response towards triethylamine (TEA) gas, a value approximately 11 times greater than that of pure LaFeO₃. Meantime, the 4% Mo-doped LaFeO₃ sensor showed a remarkably robust linear correlation between the response and the concentration (R² = 0.99736). In addition, the selectivity, stability, response/recovery time, and moisture-proof properties were evaluated. Finally, the gas-sensing mechanism is discussed. This study provides an idea for exploring a new type of efficient and low-cost metal-doped LaFeO₃ sensor to monitor the concentration of triethylamine gas for the purpose of safeguarding human health and safety. Full article

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

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14 pages, 5670 KiB

Open AccessArticle

Development of a Smartwatch with Gas and Environmental Sensors for Air Quality Monitoring

by Víctor González, Javier Godoy, Patricia Arroyo, Félix Meléndez, Fernando Díaz, Ángel López, José Ignacio Suárez and Jesús Lozano

Sensors 2024, 24(12), 3808; https://doi.org/10.3390/s24123808 - 12 Jun 2024

Cited by 1 | Viewed by 4367

Abstract

In recent years, there has been a growing interest in developing portable and personal devices for measuring air quality and surrounding pollutants, partly due to the need for ventilation in the aftermath of COVID-19 situation. Moreover, the monitoring of hazardous chemical agents is [...] Read more.

In recent years, there has been a growing interest in developing portable and personal devices for measuring air quality and surrounding pollutants, partly due to the need for ventilation in the aftermath of COVID-19 situation. Moreover, the monitoring of hazardous chemical agents is a focus for ensuring compliance with safety standards and is an indispensable component in safeguarding human welfare. Air quality measurement is conducted by public institutions with high precision but costly equipment, which requires constant calibration and maintenance by highly qualified personnel for its proper operation. Such devices, used as reference stations, have a low spatial resolution since, due to their high cost, they are usually located in a few fixed places in the city or region to be studied. However, they also have a low temporal resolution, providing few samples per hour. To overcome these drawbacks and to provide people with personalized and up-to-date air quality information, a personal device (smartwatch) based on MEMS gas sensors has been developed. The methodology followed to validate the performance of the prototype was as follows: firstly, the detection capability was tested by measuring carbon dioxide and methane at different concentrations, resulting in low detection limits; secondly, several experiments were performed to test the discrimination capability against gases such as toluene, xylene, and ethylbenzene. principal component analysis of the data showed good separation and discrimination between the gases measured. Full article

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

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18 pages, 6488 KiB

Open AccessArticle

Early Identification of Rotten Potatoes Using an Electronic Nose Based on Feature Discretization and Ensemble Convolutional Neural Network

by Haonan Lin, Zhenbo Wei, Changqing Chen, Yun Huang and Jianxi Zhu

Sensors 2024, 24(10), 3105; https://doi.org/10.3390/s24103105 - 14 May 2024

Cited by 2 | Viewed by 1074

Abstract

The early identification of rotten potatoes is one of the most important challenges in a storage facility because of the inconspicuous symptoms of rot, the high density of storage, and environmental factors (such as temperature, humidity, and ambient gases). An electronic nose system [...] Read more.

The early identification of rotten potatoes is one of the most important challenges in a storage facility because of the inconspicuous symptoms of rot, the high density of storage, and environmental factors (such as temperature, humidity, and ambient gases). An electronic nose system based on an ensemble convolutional neural network (ECNN, a powerful feature extraction method) was developed to detect potatoes with different degrees of rot. Three types of potatoes were detected: normal samples, slightly rotten samples, and totally rotten samples. A feature discretization method was proposed to optimize the impact of ambient gases on electronic nose signals by eliminating redundant information from the features. The ECNN based on original features presented good results for the prediction of rotten potatoes in both laboratory and storage environments, and the accuracy of the prediction results was 94.70% and 90.76%, respectively. Moreover, the application of the feature discretization method significantly improved the prediction results, and the accuracy of prediction results improved by 1.59% and 3.73%, respectively. Above all, the electronic nose system performed well in the identification of three types of potatoes by using the ECNN, and the proposed feature discretization method was helpful in reducing the interference of ambient gases. Full article

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

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15 pages, 4416 KiB

Open AccessArticle

Optimization of Temperature Modulation for Gas Classification Based on Bayesian Optimization

by Tatsuya Iwata, Yuki Okura, Maaki Saeki and Takefumi Yoshikawa

Sensors 2024, 24(9), 2941; https://doi.org/10.3390/s24092941 - 6 May 2024

Viewed by 2857

Abstract

This study proposes an optimization method for temperature modulation in chemiresistor-type gas sensors based on Bayesian optimization (BO), and its applicability was investigated. As voltage for a sensor heater, our previously proposed waveform was employed, and the parameters determining the voltage range were [...] Read more.

This study proposes an optimization method for temperature modulation in chemiresistor-type gas sensors based on Bayesian optimization (BO), and its applicability was investigated. As voltage for a sensor heater, our previously proposed waveform was employed, and the parameters determining the voltage range were optimized. Employing the Bouldin–Davies index (DBI) as an objective function (OBJ), BO was utilized to minimize the DBI calculated from a feature matrix built from the collected data followed by pre-processing. The sensor responses were measured using five test gases with five concentrations, amounting to 2500 data points per parameter set. After seven trials with four initial parameter sets (ten parameter sets were tested in total), the DBI was successfully reduced from 2.1 to 1.5. The classification accuracy for the test gases based on the support vector machine tends to increase with decreasing the DBI, indicating that the DBI acts as a good OBJ. Additionally, the accuracy itself increased from 85.4% to 93.2% through optimization. The deviation from the tendency that the accuracy increases with decreasing the DBI for some parameter sets was also discussed. Consequently, it was demonstrated that the proposed optimization method based on BO is promising for temperature modulation. Full article

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

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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

Cited by 1 | Viewed by 1282

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 [...] Read more.

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

Cited by 1 | Viewed by 1387

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 [...] Read more.

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 18 | Viewed by 3128

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 [...] Read more.

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 1399

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 [...] Read more.

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 5 | Viewed by 2018

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 [...] Read more.

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 - 5 Jan 2023

Cited by 8 | Viewed by 2876

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 [...] Read more.

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 9 | Viewed by 2486

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 [...] Read more.

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 - 6 Dec 2022

Cited by 1 | Viewed by 1926

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 [...] Read more.

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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Review

Jump to: Research, Other

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 29 | Viewed by 4825

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 [...] Read more.

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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Other

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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 4 | Viewed by 3948

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 [...] Read more.

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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