SnO2-based Sensors Research Articles

Orthogonal Sensor Array By Material Design

Introduction Since the introduction of gas sensor arrays in 1982 [1], they have been tested in numerous fields but still suffer from weak sensitivity and selectivity in gas mixtures [2]. To account for that, the focus lays on new evaluation algorithms (e.g. artificial neural networks with deep learning) following recent advances in computing capabilities [3]. However, often the underlying hardware (i.e. sensors) is the limiting factor. As a result, the often applied “black box” approach correlating sensor signals with chemical perception (e.g., woody taste of wine) holds high risk of bogus correlations as the relevant analyte, responsible for the actual odor, aroma or disease, might not be generating the measured sensor outputs in the first place [2].Here, the effect of orthogonality by selective material design on array performance is investigated experimentally with a basic multivariate linear regression model. This is done by systematically replacing non-selective SnO2-based sensors in an array by distinctly-selective Si:MoO3 and Si:WO3 for ammonia [4] and acetone [5], respectively. The arrays are tested with 60 random combinations of ammonia, acetone and ethanol in the ppb to low ppm range at dry conditions. Next, array size and composition is varied systematically to understand the contribution of each sensor on analyte prediction. Finally, the stability of the extracted regression coefficients is evaluated. Method Flame spray pyrolysis was used to generate sensing materials with distinct selectivities (i.e. Pt:SnO2, Pd:SnO2, Si:SnO2, Si:MoO3 and Si:WoO3). These sensors were combined to arrays and applied to 60 different gas mixtures consisting of randomly combined concentrations of ammonia (250, 500, 800, 1200, 1600 and 2000 ppb), acetone (250, 400, 600, 800, 1200 and 1800 ppb) and ethanol (50, 100, 150, 200, 400 and 600 ppb) corresponding to typical human breath concentrations. In specific, a purely SnO2-based (i.e. Pd:SnO2, Pt:SnO2 and Si:SnO2) array and one with distinctly different sensing materials (i.e. Si:WO3, Si:MoO3 and Si:SnO2) were chosen, denoted as conventional and orthogonal array, respectively. A multivariate linear regression was applied to predict the analyte concentrations, whereas a 6-fold cross-validation was used to separate the data points into calibration and test sets to assess the performance and prevent overfitting. The effect of array size and composition was investigated by evaluating the significance and stability of the regression coefficients [6] and quantifying the accuracy and precision of the arrays. Results and Conclusions Figure 1 shows the average estimation error of the conventional (Pd:SnO2, Pt:SnO2 and Si:SnO2) and orthogonal (Si:WO3, Si:MoO3 and Si:SnO2) arrays in 60 different 3-analyte gas mixtures. The conventional array estimates all analytes with large average errors. For example, for ammonia an average error of 687 ppb is obtained whereas the actual concentrations ranged from 250 to 2000 ppb. Apparently, the influence acetone and ethanol at varying concentrations prevented an accurate ammonia estimation. This is similar when estimating acetone or ethanol with smaller but still significant errors of 177 and 158 ppb, respectively. In contrast, the orthogonal array estimates all analyte concentrations more accurately. In fact, average estimation errors of 123, 45 and 67 ppb are obtained for ammonia, acetone and ethanol, respectively [7].Most likely, the conventional array with the non-specific SnO2 sensors result in a high degree of collinearity. Such arrays feature low discrimination power resulting in weak analyte estimations and strong sensitivity to small changes in background gases, humidity or temperature [8], as demonstrated experimentally here. When exchanging such collinear sensors (e.g, Pt:SnO2 and Pd:SnO2) with distinctly selective ones (Si:WO3 and Si:MoO3) the degree of orthogonality is increased resulting in accurate array estimations.As a result, we provide experimental evidence that sensor array performance depends largely on the orthogonality and thus selectivity of its constituent sensors. Utilizing distinctly selective sensors in arrays improved discrimination power and stability of the regression coefficients, necessary for accurate and precise analyte predictions in gas mixtures. Such orthogonal arrays are needed in breath analysis [9] or human search and rescue [10] due to the low concentrations and high number of interferants.

Cellulose Nanocrystal-Templated Tin Dioxide Thin Films for Gas Sensing.

Porous tin dioxide is an important low-cost semiconductor applied in electronics, gas sensors, and biosensors. Here, we present a versatile template-assisted synthesis of nanostructured tin dioxide thin films using cellulose nanocrystals (CNCs). We demonstrate that the structural features of CNC-templated tin dioxide films strongly depend on the precursor composition. The precursor properties were studied by using low-temperature nuclear magnetic resonance spectroscopy of tin tetrachloride in solution. We demonstrate that it is possible to optimize the precursor conditions to obtain homogeneous precursor mixtures and therefore highly porous thin films with pore dimensions in the range of 10-20 nm (ABET = 46-64 m2 g-1, measured on powder). Finally, by exploiting the high surface area of the material, we developed a resistive gas sensor based on CNC-templated tin dioxide. The sensor shows high sensitivity to carbon monoxide (CO) in ppm concentrations and low cross-sensitivity to humidity. Most importantly, the sensing kinetics are remarkably fast; both the response to the analyte gas and the signal decay after gas exposure occur within a few seconds, faster than in standard SnO2-based CO sensors. This is attributed to the high gas accessibility of the very thin porous film.

Highly selective ppb-level H2S sensor for spendable detection of exhaled biomarker and pork freshness at low temperature: Mesoporous SnO2 hierarchical architectures derived from waste scallion root

Herein, we firstly reported a waste scallion root biotemplate strategy to massively fabricate mesoporous SnO2 hierarchical architectures, which can realize precise detection of ppb-level H2S gas in highly humid atmosphere (RH = 85%). The hierarchical skeleton is made up of the crosslinked nanoparticles of about 13 nm with a layer of nanospheres uniformly loaded on the surface of small-sized particles. Such specially structural characteristic can ensure that SnO2 sensing materials possess large specific surface area and good mesoporous connectivity, enhancing the response and selectivity towards trace H2S in a wide range of 0.5–1000 ppb at low working temperature of 92 °C. Especially, detection limit of 0.5 ppb is the lowest among all reported SnO2-based H2S sensors. Meanwhile, we also monitored the change of trace H2S gas concentration in exhaled breath of healthy human, the decay process of fresh pork in 72 h and the simulated environment of halitosis under high humidity, and the sensor exhibited satisfactory results. Therefore, the mesoporous SnO2 hierarchical structure could be used as a spendable sensing material of detecting ppb-level H2S for the applications in meat freshness monitoring and halitosis diagnosis.

Atomic-scale structure and chemical sensing application of ultrasmall size-selected Pt nanoparticles supported on SnO2

SnO2-based chemoresistive sensors integrated in complementary metal-oxide-semiconductor technology were functionalized with ultrasmall Pt nanoparticles, resulting in carbon monoxide sensing properties with minimized humidity interference.

Sensing mechanism of Sb, S doped SnO2 (1 1 0) surface for CO

First-principles calculation based on density functional theory (DFT) was employed to study the adsorption of CO molecules on various SnO2 (1 1 0) surface. For comparison, the adsorption of CO on perfect SnO2, Sb-doped SnO2 and Sb, S co-doped SnO2 surfaces are considered. Adsorption energy, electron population and density of states show that the sensing properties of SnO2-based sensors in terms of the CO response were improved by Sb, S co-doping.

Multilevel Effective Heterojunctions Based on SnO2/ZnO 1D Fibrous Hierarchical Structure with Unique Interface Electronic Effects.

One-step single-spinneret electrospinning synthesis of 1D fibrous hierarchical structure can not only prevent the agglomeration or restacking of fibers or particles and enlarge surface active area but also promote the directional migration of electrons in materials and achieve effective regulation of resistances. Herein, tunable SnO2 and SnO2/ZnO fibrous hierarchical structures with in situ growth of monodisperse spherical-like particles on surface provide a new sight for adjusting component distribution, surface absorption and chemical reaction, electronic transmission path, and electron transfer efficiency. Compared with SnO2 porous fibers and SnO2 hierarchical structures, the optimal SnO2/ZnO sensors exhibit superior gas-sensing response value of 366-100 ppm ethanol at 260 °C as well as excellent gas selectivity and long-term stability, in which the enhanced gas-sensing mechanism is primarily derived from multilevel effective heterojunctions with unique interface electronic effects. Especially, these SnO2-based sensors can achieve favorable linear relationship of the response and gas concentration for sensitive trace detection in cosmetics for the first time, providing a new strategy to design composite materials for quantitative analysis of volatiles in the cosmetics evaluation process.

A visible-light activated gas sensor based on perylenediimide-sensitized SnO2 for NO2 detection at room temperature

A visible-light activated gas sensor has been successfully fabricated by impregnating perylenediimide into a SnO2 nanofilm. The perylenediimide/SnO2 heterojunction sensor exhibits a higher sensing performance in comparison to the SnO2-based sensor. Moreover, under the assistance of visible-light illumination, the hybrid sensor can work efficiently at room temperature for low concentration NO2 detection through increased sensitivity and reduction of the response and recovery times. These desirable sensing features can be attributed to the advanced heterostructure, since it not only enables the sensor to be activated by the visible-light but also has advantages for electron separation. Finally, the excellent selectivity and reproducibility of the hybrid sensor were also demonstrated. Our experimental results suggest that this hybrid sensor could be a promising candidate for room-temperature gas sensing applications.

Nanosized materials CeO2/SnO2 and CeO2/SnO2-Sb2O5 for adsorption semiconductor sensors to detect hydrogen in air

Nanosized materials based on SnO2 and SnO2 – Sb2O5 with different concentrations of added cerium were synthesized by a sol-gel method. Semiconductor gas sensors on the base of the materials were created and their characteristics (electrical resistance in air, response to hydrogen, dynamic properties) were studied. It is shown that cerium addition significantly improves the sensor response due to high catalytic activities of Ce-containing nanosized oxide materials in the H2 oxidation reaction. SnO2-based sensors were found to demonstrate higher sensitivity to hydrogen than SnO2-Sb2O5 based sensors. Possible mechanism concerning formation of the sensitivity of the Ce-containing sensors to H2 is proposed.

Recent Advances of SnO2-Based Sensors for Detecting Fault Characteristic Gases Extracted From Power Transformer Oil.

Tin oxide SnO2-based gas sensors have been widely used for detecting typical fault characteristic gases extracted from power transformer oil, namely, H2, CO, CO2, CH4, C2H2, C2H4, and C2H6, due to the remarkable advantages of high sensitivity, fast response, long-term stability, and so on. Herein, we present an overview of the recent significant improvement in fabrication and application of high performance SnO2-based sensors for detecting these fault characteristic gases. Promising materials for the sensitive and selective detection of each kind of fault characteristic gas have been identified. Meanwhile, the corresponding sensing mechanisms of SnO2-based gas sensors of these fault characteristic gases are comprehensively discussed. In the final section of this review, the major challenges and promising developments in this domain are also given.

Detection of Catecholamine Neurotransmitters by Nanostructured SnO2-Based Electrochemical Sensors: A Review of Recent Progress

Detection of Catecholamine Neurotransmitters by Nanostructured SnO2-Based Electrochemical Sensors: A Review of Recent Progress

Selectivity and Cross-Sensitivity of Transfer-Free Fabricated Nanocrystalline Graphene Field-Effect Gas Sensors

In the course of an increasing awareness for the protection of public health a higher demand for environmental gas sensors, especially for the detection of volatile organic compounds and toxic gases, has been noted. Reasonably-priced devices to cover this demand can be solid-state gas sensors that can be easily fabricated and scaled using planar processing. Furthermore, an appropriate choice of materials may enable the possibility of monolithic integration within silicon CMOS circuitry thus providing the chance of co-integrating read-out and signal processing electronics on the same chip. As a two-dimensional carbon nanomaterial graphene shows a high surface-to-volume ratio and promising electronic properties for the detection of gaseous species. Detection capabilities down to a single molecule have been demonstrated by Schedin et al. [1], using a pristine graphene flake made from mechanical cleavage of highly ordered pyrolytic graphite. In this contribution we port on a novel method for graphene-based sensor fabrication. By means of a CMOS compatible method we have fabricated hundreds of transfer-free nanocrystalline graphene field-effect transistors (ncGFETs) on silicon dioxide [2], which can be used for detection of gaseous species. Under application of a HP4156A semiconductor parameter analyzer the gaseous sensitivity of our ncGFETs is electrically characterized in terms of backgate FET input characteristics as well as in a resistive configuration. For the resistive configuration the backgate bias has been fixed near the charge neutrality point of our nanocrystalline graphene devices at VBG = 0V. All measurements were done using our self-constructed vacuum probing station that can be systematically flooded with calibrated gas mixtures. The gas concentration is then derived from the vacuum pressure using the ideal gas law. Sensitivities of our ncGFETs to different volume concentrations of various toxic gases including ammonia (NH3), nitrogen dioxide (NO2), and carbon monoxide (CO) will be presented. E.g. for devices heated to 425K a sensitivity S of roughly 80% is S = (G-G0)/G0 achieved for 4 parts-per-million-volume (ppmv) of ammonia whereat NO2 already shows a sensitivity of 100% for a concentration of 4 parts-per-trillion-volume (pptv = 10-6 ppmv). The higher sensitivity of our ncGFETs compared to other graphene devices is attributed to modifications of grain boundary potential barriers, which is the dominating mechanism in e.g. SnO2-based Taguchi-type sensors [3]. Furthermore, the influence of water vapor (H2O (g)) on our devices is discussed. Nevertheless, the cross-sensitivity of Taguchi-type sensors, like our ncGFETs, remains a problem. Speciation of gas molecules is feasible by the use of sensor arrays consisting of devices with different sensitivities and electronic characteristics towards different gas species. Therefore, in order to modify the sensitivities towards the different gas species of our ncGFETs towards the different gas species we have characterized the sensitivity and responsivity at various temperatures. Furthermore, during exposure to the different gases the analysis of the backgate ncGFET input characteristics shows shifts of the charge neutrality point, as well as changes in the hysteresis of our devices. A novel method to selectively discriminate between various gaseous species, which is based on the analysis of the hysteresis in the ncGFETs will be presented and discussed. [1]F. Schedin, A. K. Geim, S. V. Morozov, E. W. Hill, P. Blake, M. I. Katsnelson and K. S. Novoselov, Nat Mater, 6, 652 (2007). [2] D. Noll and U. Schwalke, 2017 12th Ieee International Conference on Design & Technology of Integrated Systems in Nanoscale Era (Dtis 2017) (2017). [3] R. K. Srivastava, P. Lal, R. Dwivedi and S. K. Srivastava, Sensor Actuat B-Chem, 21, 213 (1994). Figure 1

Gas-sensing properties of composites of Y-zeolite and SnO2

Y-zeolite was first modified by means of ions exchange with Al, Ca and Na, respectively. The modified materials were characterized by using X-ray diffraction (XRD), scanning electron microscopy (SEM) and inductively coupled plasma optical emission spectrometry (ICP-OES). Gas sensors were fabricated by SnO2 and coating Y-zeolites on the outside of SnO2 surface, respectively. It was found that the responses of the composites of all types of zeolite- and SnO2-based sensors became lower comparing with that of the pure SnO2-based one response of SnO2 sensor to ethanol vapor. It indicates a suppression effect of zeolites on the response to ethanol vapor. In contrast, the response of the composite-sensing materials of the modified Y-zeolite/SnO2-based sensors except the Ca-modified one to acetone indicates a significantly improved response, 2–3 times higher than that of pure SnO2-based sensor which is smaller than the one of SnO2 sensor. The possible mechanism of the effects of the Y-zeolites on the response of the sensors has been discussed.

Ordered Mesoporous Tin Oxide Semiconductors with Large Pores and Crystallized Walls for High-Performance Gas Sensing.

Owing to their distinct chemical and physical properties, mesoporous metal oxide semiconductors have shown great application potential in catalysis, electrochemistry, energy conversion, and energy storage. In this study, mesoporous crystalline SnO2 materials have been synthesized through an evaporation-induced co-assembly (EICA) method using poly(ethylene oxide)-b-polystyrene diblock copolymers as the template, tin chlorides as the tin sources, and tetrahydrofuran as the solvent. By controlling conditions of the co-assembly process and employing a carbon-supported thermal treatment strategy, highly ordered mesoporous SnO2 materials with a hexagonal mesostructure (space group P63/mmc) and crystalline pore walls can be obtained. The mesoporous SnO2 is employed for fabricating gas sensor nanodevices which exhibit an excellent sensing performance toward H2S with high sensitivity (170, 50 ppm) and superior stability, owing to its high surface area (98 m2/g), well-connected mesopores of ca. 18.0 nm, and high density of active sites in the crystalline pore walls. The chemical mechanism study reveals that both SO2 and SnS2 are generated during the gas sensing process on the SnO2-based sensors.

Kinetic approach to receptor function in chemiresistive gas sensor modeling of tin dioxide. Steady state consideration

Kinetic approach in phenomenological modeling of SnO2 chemiresistive gas sensor is proposed. It is based on a new perception of chemisorbed oxygen forms and consistent account of main reaction rates into a balance equation of particles on (110) surface. So-called receptor function was considered for dry and humid atmosphere and in the presence of CO. Transducer function was calculated within an electron filtering model. Numerical simulation of the surface coverage by oxygen and major gas sensing characteristics of SnO2 within 150–600 °C temperature range showed sufficient agreement with experimental behavior of nanocrystalline SnO2-based sensors. Model allows interpretation of some of the important features in these characteristics.

Selective detection of individual gases and CO/H2 mixture at low concentrations in air by single semiconductor metal oxide sensors working in dynamic temperature mode

Highly selective detection of various individual gases (CO, H2, CH4, C3H8, NO, NO2, H2S, SO2) at low concentrations (0.01–667ppm) in air by a single SnO2-based metal oxide sensor (MOX-sensor) is presented. The sensor operates in dynamic temperature mode combined with a number of adaptive signal processing algorithms. Artificial neural networks were proven to be more effective among the other adaptive algorithms implemented in this study. Identification of individual gases by a single sensor, averaged over all the gases and concentrations, resulted in only 13.2% false recognitions. Most of the failures were attributed to NO2 detection in 0.01–0.1ppm concentrations range.The ability of a single sensor to identify gas mixtures in a complex background was tested on the example of CO+H2 mixture in air, which simulates smoldering in the early stages of fire. The algorithm showed the ability to identify and quantify CO+H2 mixture with less than 10% error rate, even in constant presence of background gas (NO2 1.4ppm). Chemical modification of SnO2, increasing sensor response and sensitivity to individual components of the mixture, was proven to be beneficial for improvement of identification and quantification of gas mixture. Significant improvement in quantification accuracy (decrease in relative error from 7 to 2.5%) was achieved by utilizing a 3 sensor array in combination with an adaptive data processing algorithm, compared to the use of a single sensor alone. The prominent negative effect of humidity (Rh 30%, 25°C) on the performance of adaptive algorithms, sensor signal processing, system selectivity, and gas mixture identification is demonstrated.

Semiconductor-type SnO2-based NO2 sensors operated at room temperature under UV-light irradiation

NO2-sensing properties of typical oxide (SnO2, In2O3, or WO3)-based semiconductor gas sensors were measured at 30°C with and without UV-light irradiation (main wavelength: 365nm), and effects of noble-metal (Pd or Pt) loading, UV-light intensity (0–134mWcm−2) and relative humidity in target gas (0–80%RH) on their NO2-sensing properties were investigated in this study. The UV-light irradiation effectively reduced the resistances of all sensors, enhanced their NO2 responses in some cases, and tended to accelerate their response and recovery speeds in dry air, because the UV-light irradiation promoted the adsorption and desorption of NO2-species on the surface. The SnO2 sensor showed the largest NO2 response in dry air, among all the pristine oxide sensors, especially under weak UV-light irradiation (≤35mWcm−2), together with relatively fast response and recovery speeds. The Pd or Pt loading onto SnO2 enhanced the NO2 response of the SnO2 sensor and accelerated their response and recovery speeds in dry air, while XPS analysis indicated that most of the Pd and Pt nanoparticles loaded on the surface were oxidized after heat treatment at 500°C. Among all the sensors, the 0.05wt% Pd-loaded SnO2 sensor showed the largest NO2 response under weak UV-light irradiation (≤35mWcm−2), together with relatively fast response and recovery speeds. The addition of moisture to the target gas had adverse effects on the NO2 responses and the response speeds of the SnO2 and 0.05wt% Pd-loaded SnO2 sensors, but the weak UV-light irradiation (7mWcm−2) largely reduced the dependence of the NO2 response of the 0.05Pd/SnO2 sensor on relative humidity while maintaining the large NO2 response, probably because the weak UV-light irradiation promotes the desorption of physisorbed water molecules and then the effective adsorption of NO2 on the 0.05Pd/SnO2 surface.

Calcination Method Synthesis of SnO2/g-C3N4 Composites for a High-Performance Ethanol Gas Sensing Application.

The SnO2/g-C3N4 composites were synthesized via a facile calcination method by using SnCl4·5H2O and urea as the precursor. The structure and morphology of the as-synthesized composites were characterized by the techniques of X-ray diffraction (XRD), the field-emission scanning electron microscopy and transmission electron microscopy (SEM and TEM), energy dispersive spectrometry (EDS), thermal gravity and differential thermal analysis (TG-DTA), and N2-sorption. The analysis results indicated that the as-synthesized samples possess the two dimensional structure. Additionally, the SnO2 nanoparticles were highly dispersed on the surface of the g-C3N4nanosheets. The gas-sensing performance of the as-synthesized composites for different gases was tested. Moreover, the composite with 7 wt % g-C3N4 content (SnO2/g-C3N4-7) SnO2/g-C3N4-7 exhibits an admirable gas-sensing property to ethanol, which possesses a higher response and better selectivity than that of the pure SnO2-based sensor. The high surface area of the SnO2/g-C3N4 composite and the good electronic characteristics of the two dimensional graphitic carbon nitride are in favor of the elevated gas-sensing property.

Osoblyvosti detektuvannya vidnovlyuval'nykh haziv sensoramy na osnovi In2O3 i SnO2 u volohiy atmosferi

Osoblyvosti detektuvannya vidnovlyuval'nykh haziv sensoramy na osnovi In2O3 i SnO2 u volohiy atmosferi

Applicability of superposition for responses of resistive sensors in a diluted mixed gas environment

The potential for using superposition to predict the response of resistive-type gas sensors when they are exposed to more than a single gas was tested using two SnO2-based sensors. It is proposed that the selectivity of resistive-type gas sensors could be improved, or individual gas concentrations extracted, based on the observed response values of the sensors and a mathematical formulation. In this study, the behavior of several resistive gas sensors was tested in a mixed-gas environment of toluene and acetone, using a GASENTEST, which is an automatic gas sensor testing machine developed for this study. The measured responses were compared with calculated responses based on our mathematical formula. Additionally, the actual concentrations of the input gases were compared to the gas concentrations calculated from the observed response of the sensors.

Gas-sensing properties and mechanisms of Cu-doped SnO2 spheres towards H2S

We report on the synthesis of pristine and Cu-doped SnO2 spheres using a facile hydrothermal method and investigate their microstructures and gas-sensing response. We focus on how Cu doping can have an impact on gas-sensing behavior of SnO2-based sensors toward H2S. We find that Cu doping can enhance significantly the gas response of SnO2 toward H2S, the origin of which can be clarified with a proposed adsorption model. First-principles calculations reveal that adsorption energy of H2S on Cu-doped surface is lower than that on undoped one and the interaction between adsorbed H2S and Cu-doped surface is stronger than that between adsorbed H2S and pure surface, which consequently improves gas-sensing performances of SnO2 toward H2S. Such a combined experimental and calculational study offers an explanation on how Cu doping affects gas-sensing performances of SnO2.