Metal oxide resistive-type nano-scale gas sensors have been investigated for their low cost, high sensitivity, and environmentally friendly fabrication. In these sensors, electrical resistance ...measurements are used to detect the presence of gas. In n-type metal oxides, resistance is increased by coverage of adsorbed oxygen and lowered by removal of adsorbed oxygen through reactions with reducing gasses. The sensitivity and selectivity of these sensors have been improved by incorporation of heterostructures. Heterostructures may improve sensor performance through facilitating catalytic activity, increasing adsorption, and creating a charge carrier depletion layer that produces a larger modulation in resistance. Synergistic effects in these gas sensors describe the improved sensor signal due to these combined effects which act to amplify the reception and transduction of the sensor signal. Receptive mechanisms may be improved by increasing adsorption and reactivity. Transduction mechanisms may be improved by restriction of the major charge conduction channels which helps to maximize resistance modulation. In this review, the synergistic effect achieved by combining these two mechanisms are examined. Fundamental properties of the metal oxide surface are used to provide insight for the large body of experimental evidence available for metal oxide resistive-type gas sensors. This review aims to connect experimental evidence to conceptual mechanistic descriptions by examining adsorption processes, charge transfer, reaction mechanisms, morphology, and ambient gas interactions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Resistive-type semiconducting metal oxide (SMOX) sensors offer exciting possibilities for designing sensing systems that can detect extremely low concentrations of gasses relevant for industrial ...applications, environmental monitoring, and human health and safety. Research on this technology has produced sensors with high response, but the ability to predictively design sensing systems for specific applications requires improvements in selective detection. Gas selectivity is necessary to differentiate between multiple gas species that may be present in a given application. This has prevented wide-spread use of this technology in real-world settings. In this work, studies on gas selectivity in semiconducting metal oxide sensors are reviewed with specific emphasis on heterojunctions and fundamental sensing mechanisms. Concepts relating both to receptive and transduction sensor mechanisms are explained. The effects due to gas surface interactions and electronic equilibration are compared and discussed. Both modeling efforts and experimental literature are presented to explain fundamental mechanisms that control sensor behavior. Sensor selectivity is examined to further both fundamental understanding as well as increase real-world applications of semiconducting metal oxides.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Recently one dimensional (1-D) nanostructured metal-oxides have attracted much attention because of their potential applications in gas sensors. 1-D nanostructured metal-oxides provide high surface ...to volume ratio, while maintaining good chemical and thermal stabilities with minimal power consumption and low weight. In recent years, various processing routes have been developed for the synthesis of 1-D nanostructured metal-oxides such as hydrothermal, ultrasonic irradiation, electrospinning, anodization, sol-gel, molten-salt, carbothermal reduction, solid-state chemical reaction, thermal evaporation, vapor-phase transport, aerosol, RF sputtering, molecular beam epitaxy, chemical vapor deposition, gas-phase assisted nanocarving, UV lithography and dry plasma etching. A variety of sensor fabrication processing routes have also been developed. Depending on the materials, morphology and fabrication process the performance of the sensor towards a specific gas shows a varying degree of success. This article reviews and evaluates the performance of 1-D nanostructured metal-oxide gas sensors based on ZnO, SnO(2), TiO(2), In(2)O(3), WO(x), AgVO(3), CdO, MoO(3), CuO, TeO(2) and Fe(2)O(3). Advantages and disadvantages of each sensor are summarized, along with the associated sensing mechanism. Finally, the article concludes with some future directions of research.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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•The photo-energy actived gas sensor was developed for the detection of NO2 by using the SnS2 nanosheets as the gas sensing material.•The gas sensor exhibits a high response and an ...excellent selectivity to 8 ppm NO2 under the green light illumination at room temperature.•The intrinsic mechanism of the SnS2 based sensor could be attributed to the photo-generated electron-hole pairs.
The visible-light activated gas sensor has been successfully fabricated for detecting NO2 by using two dimensional (2D) structured SnS2 nanosheet as the chemiresistive sensing material. Under the light illumination, the SnS2 nanosheet based chemiresistive gas sensor exhibits a high response and excellent selectivity to NO2 at room temperature. Influences of light wavelength, light intensity, operating temperatures and humidity on the sensing characteristics are investigated in details. It suggests that photo-energy activation can effectively activate the SnS2 sensor and the green light is the most effective to achieve superior sensing property of the SnS2 sensor at room temperature in terms of the excellent sensitivity and a better response/recovery speeds. The sensor also demonstrated an excellent selectivity to NO2 over several possible interferants such as SO2, CO2, NH3, acetone, methanol, ethanol and formaldehyde, and a good stability for about six months activated by the green light. The sensing mechanism is intimately related to the extra photo-generated electrons which subsequently attract more NO2 at its 2D surface. A simple Langmuir - Hinshelwood dynamics model is proposed to explain the effect of the visible light irradiation on the absorption/desorption speed of gas molecules.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
An inexpensive single-step carbon-assisted thermal evaporation method for the growth of SnO2-core/ZnO-shell nanostructures is described, and the ethanol sensing properties are presented. The ...structure and phases of the grown nanostructures are investigated by field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) techniques. XRD analysis indicates that the core-shell nanostructures have good crystallinity. At a lower growth duration of 15 min, only SnO2 nanowires with a rectangular cross-section are observed, while the ZnO shell is observed when the growth time is increased to 30 min. Core-shell hierarchical nanostructures are present for a growth time exceeding 60 min. The growth mechanism for SnO2-core/ZnO-shell nanowires and hierarchical nanostructures are also discussed. The sensitivity of the synthesized SnO2-core/ZnO-shell nanostructures towards ethanol sensing is investigated. Results show that the SnO2-core/ZnO-shell nanostructures deposited at 90 min exhibit enhanced sensitivity to ethanol. The sensitivity of SnO2-core/ZnO-shell nanostructures towards 20 ppm ethanol gas at 400 °C is about ~5-times that of SnO2 nanowires. This improvement in ethanol gas response is attributed to high active sensing sites and the synergistic effect of the encapsulation of SnO2 by ZnO nanostructures.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Metal oxide nano-structures on microhotplate platforms have attracted a great deal of interest in gas sensor research for their potential to create both highly responsive and extremely portable gas ...sensors. Much of the current research on these sensors has focused upon the creation of hierarchical nanostructures, as van der Waals attraction between nanoparticles leads to agglomeration that impair sensor performance. In this research article, ink-jet printing onto microhotplates was explored as a method of avoiding nanoparticle agglomeration to produce an open film microstructure. Scanning electron microscopy was used to study the deposited thin nanoparticle film featuring an open microstructure free of large agglomeration. Sensor response and response times of ink-jet printed SnO2 nanoparticles were found to be comparable to hierarchical particle films when exposed to methane and carbon monoxide in a background of dry air. Both the SnO2 nanoparticles and microspheres had superior response compared to SnO2 micron-size particles due to increased surface area of the nano-structures. This implies that proper control of the microstructure of the SnO2 nanoparticle films produces similar gas sensor performance to SnO2 hierarchical structures and has the potential for use in reproducibly manufacturing high-performance gas sensors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•A functional database has been developed which allows users to input and search for data on resistive-type sensors.•Common synthesis methods, morphologies, and sensor fabrication techniques have ...been identified in literature and incorporated for easy sensor data input.•Users can search for relevant publications and export data to compare sensor performance across multiple studies.•This database provides the capability to identify the optimal operating temperature which was demonstrated in this paper for SnO2 sensors tested for 5 common gas analytes.•Future prospects on the potential of this database to improve research in this field are discussed.
A new database has been established which will allow the gas sensor researcher to quickly and effectively compare published data to evaluate the state-of-the-art, identify deficiencies in the field, and discover trends in properties and performance that would otherwise be unidentifiable from the efforts of any one research group. This Open-access Database Of Resistive-type Sensors (ODORS) will remain openly accessible through a web browser at (www.odorsdatabase.com). The interface allows the user to search for, filter, and sort results based on materials composition, gas analyte, response magnitude, morphology, synthesis method, and many other relevant properties. The database has been established with data from over 150 recently published papers, but its further growth will rely on researchers around the world submitting their own published data via an easy-to-use form also available on the website. It is to the benefit of all researchers that they submit their own published data for inclusion in the database to increase discoverability and citations of their papers and exposure to their work.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract The poultry sector in Pakistan is contributing mainly in bridging gap between demand and supply for protein. Mycoplasma gallisepticum is an emerging bacterium causing serious problems in ...poultry industry of Pakistan. A cross-sectional study was conducted to evaluate the M. gallisepticum load in poultry populated regions of Pakistan. Total 600 serum and 600 swab samples were collected, 200 from each broiler, layers and breeders poultry in Rawalpindi and Abbottabad districts. Serum samples were analyzed through ELISA for seroprevalence. Swabs were cultured on Frey’s medium followed by PCR and partial mgc2 gene sequencing. Results of seroprevalence of M. gallisepticum showed that layers (75%, n=150) are more positive as compared to breeders (70%, n=140) and broilers (50%, n=100). Typical colonies of the M. gallisepticum were observed in breeder (26.5%), followed by layer (21%) and broilers (9%). A total of 37.1% (n=42) samples were identified positive through PCR out of total 113 cultured based positive samples. A total of six M. gallisepticum isolates of current study showed 98-99 percent similarity with previously reported isolates on the basis of mgc2 gene partial sequencing. The M. gallisepticum was found highly prevalent in different poultry breads. Results of this study would add into basic data and provide a direction for livestock sector to strengthen a control strategy for mycoplasmosis in poultry farms.
Resumo O setor avícola do Paquistão está contribuindo principalmente para preencher a lacuna entre a demanda e a oferta de proteína. Mycoplasma gallisepticum é uma bactéria emergente que causa sérios problemas na indústria avícola do Paquistão. Um estudo transversal foi conduzido para avaliar a carga de M. gallisepticum em regiões de avicultura do Paquistão. Um total de 600 amostras de soro e 600 amostras de esfregaço foi coletado, 200 de cada frango de corte, poedeiras e aves reprodutoras nos distritos de Rawalpindi e Abbottabad. Amostras de soro foram analisadas por ELISA para soroprevalência. As zaragatoas foram cultivadas em meio Frey, seguido de PCR e sequenciação parcial do gene mgc2. Os resultados da soroprevalência de M. gallisepticum mostraram que as poedeiras (75%, n = 150) são mais positivas em comparação com matrizes (70%, n = 140) e frangos de corte (50%, n = 100). Colônias típicas de M. gallisepticum foram observadas em reprodutoras (26,5%), seguidas de poedeiras (21%) e frangos de corte (9%). Um total de 37,1% (n = 42) das amostras foi identificado como positivas por PCR de um total de 113 amostras positivas baseadas em cultura. Um total de seis isolados de M. gallisepticum do estudo atual mostrou 98-99% de similaridade com isolados relatados anteriormente com base no sequenciamento parcial do gene mgc2. O M. gallisepticum foi encontrado com alta prevalência em diferentes pães de aves. Os resultados deste estudo acrescentariam dados básicos e forneceriam orientação para o setor pecuário fortalecer uma estratégia de controle da micoplasmose em granjas avícolas.
In this research work, the sensitivity of TiO2 nanoparticles towards C2H5OH, H2 and CH4 gases was investigated. The morphology and phase content of the particles was preserved during sensing tests by ...prior heat treatment of the samples at temperatures as high as 750 °C and 1000 °C. Field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) analysis were employed to characterize the size, morphology and phase content of the particles. For sensor fabrication, a film of TiO2 was printed on a Au interdigitated alumina substrate. The sensing temperature was varied from 450 °C to 650 °C with varying concentrations of target gases. Results show that the sensor has ultrahigh response towards ethanol (C2H5OH) compared to hydrogen (H2) and methane (CH4). The optimum sensing temperature was found to be 600 °C. The response and recovery times of the sensor are 3 min and 15 min, respectively, for 20 ppm C2H5OH at the optimum operating temperature of 600 °C. It is proposed that the catalytic action of TiO2 with C2H5OH is the reason for the ultrahigh response of the sensor.
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A four-sensor array with neural networks was developed to identify formaldehyde in three possible interfering volatile organic vapors, such as acetone, ethanol, and toluene. The sensor array ...consisted of four metal oxide-based gas sensors: two of them are commercial SnO 2 sensors, other two sensors are made in our laboratory. The responses of the sensors to each gas and to the mixture of two or all of them were tested and evaluated. It was found that every sensor has response to these four kinds of gases, and the response value of each sensor to the mixture gases was lower than the simple added value of the responses to each gas. This phenomenon is due to the properties of gas and the sensing materials. For recognizing formaldehyde in the background of ethanol, acetone, and toluene in air, 108 gas samples were tested taking into account of possible practical concentrations. Among these samples, 91 samples were used for training the pattern recognition methods and 17 samples for testing the robustness. Three neural networks were used in this report, including back propagation neural network support vector machines (SVM) and extreme learning machine (ELM) with principal component analysis (PCA). The PCA helps to improve the accuracy of the ELM by preprocessing the sensor data, while the SVM method achieves the best accuracy. The ELM method indicates a better way to train the sensor array and to identify the particular gas species with very less training time and good accuracy.