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

Atomistic Descriptions of Gas-Surface Interactions on Tin Dioxide

Historically, in gas sensing literature, the focus on “mechanisms” has been on oxygen species chemisorbed (ionosorbed) from the ambient atmosphere, but what these species actually represent and the location of the adsorption site on the surface of the solid are typically not well described. Recent advances in computational modelling and experimental surface science provide insights on the likely mechanism by which oxygen and other species interact with the surface of SnO2, providing insight into future directions for materials design and optimisation. This article reviews the proposed models of adsorption and reaction of oxygen on SnO2, including a summary of conventional evidence for oxygen ionosorption and recent operando spectroscopy studies of the atomistic interactions on the surface. The analysis is extended to include common target and interfering reducing gases, such as CO and H2, cross-interactions with H2O vapour, and NO2 as an example of an oxidising gas. We emphasise the importance of the surface oxygen vacancies as both the preferred adsorption site of many gases and in the self-doping mechanism of SnO2.

Structure, Surface Morphology, Chemical Composition, and Sensing Properties of SnO2 Thin Films in an Oxidizing Atmosphere

We conducted experiments on SnO₂ thin layers to determine the dependencies between the stoichiometry, electrochemical properties, and structure. This study focused on features such as the film structure, working temperature, layer chemistry, and atmosphere composition, which play a crucial role in the oxygen sensor operation. We tested two kinds of resistive SnO₂ layers, which had different grain dimensions, thicknesses, and morphologies. Gas-sensing layers fabricated by two methods, a rheotaxial growth and thermal oxidation (RGTO) process and DC reactive magnetron sputtering, were examined in this work. The crystalline structure of SnO₂ films synthesized by both methods was characterized using XRD, and the crystallite size was determined from XRD and AFM measurements. Chemical characterization was carried out using X-ray photoelectron (XPS) and Auger electron (AES) spectroscopy for the surface and the near-surface film region (in-depth profiles). We investigated the layer resistance for different oxygen concentrations within a range of 1-4%, in a nitrogen atmosphere. Additionally, resistance measurements within a temperature range of 423-623 K were analyzed. We assumed a flat grain geometry in theoretical modeling for comparing the results of measurements with the calculated results.

A New Hydrogen Sensor Fault Diagnosis Method Based on Transfer Learning With LeNet-5

The fault safety monitoring of hydrogen sensors is very important for their practical application. The precondition of traditional machine learning methods for sensor fault diagnosis is that enough fault data with the same distribution and feature space under the same working environment must exist. Widely used fault diagnosis methods are not suitable for real working environments because they are easily complicated by environmental conditions such as temperature, humidity, shock, and vibration. Under the influence of such complex conditions, the acquisition of sensor fault data is limited. In order to improve fault diagnosis accuracy under complex environmental conditions, a novel method of transfer learning (TL) with LeNet-5 is proposed in this paper. Firstly, LeNet-5 is applied to learn the features of the data-rich datasets of gas sensor faults in a normal environment and to adjust the parameters accordingly. The parameters of the LeNet-5 are transferred from the task in the normal environment to a task in a complex environment by using the TL method. Then, the migrated LeNet-5 is used for the fault diagnosis of gas sensors with a small amount of fault data in a complex environment. Finally, a prototype hydrogen sensor array is designed and implemented for experimental verification. The gas sensor fault diagnosis accuracy of the traditional LeNet-5 was 88.48 ± 1.04%, while the fault diagnosis accuracy of TL with LeNet-5 was 92.49 ± 1.28%. The experimental results show that the method adopted presents an excellent solution for the fault diagnosis of a hydrogen sensor using a small quantity of fault data obtained under complex environmental conditions.

High sensitivity room temperature sulfur dioxide sensor based on conductive poly(p-phenylene)/ZSM-5 nanocomposite

Recently, there has been growing interests in the development of composite materials as the new alternative gas sensing materials for replacing metal oxide based sensors which require the elevated operating temperature. Herein, we reported the fabrication and testing of new sensing composite materials based on the conductive poly(p-phenylene) (PPP) nanoparticle and zeolites for sulfur dioxide (SO₂) detection at room temperature under the effects of doping, zeolite type, zeolite content, SO₂ concentration as well as interferences and humidity. The relative electrical conductivity response depended critically on the doping agent type, doping ratio, and doping temperature. The addition of porous zeolites into the doped-PPP (dPPP) matrix induced the improvement in selectivity and sensing performances towards SO₂ as it promoted more surface area for SO₂ adsorption and its new synergistic effect with the conductive dPPP, related to the additional conductive polymer doping from the dissolution of the SO₂ in intrazeolitic water as identified and reported here. Among all materials, the dPPP/ZSM-5 composite with perchloric acid (HClO₄) as the doping agent, the doping ratio of 50:1, the doping temperature of 70 °C, and the zeolite content of 30% exhibited the highest relative response of 25.42 towards 500 mg L^-1 SO₂ with good repeatability. This composite provided the SO₂ sensitivity of 0.0483 L mg^-1 with R² of 0.9927 and the limit of detection (LOD) of 5 mg L^-1 as determined from the electrical conductivity signal to noise ratio. The present sensing material is a potential candidate in the practical detection of SO₂ at room temperature.

First-Principles Insight into Pd-Doped ZnO Monolayers as a Promising Scavenger for Dissolved Gas Analysis in Transformer Oil

ZnO monolayers with desirable n-type semiconducting properties are full of potential for sensing applications. In this work, we investigate using first-principles theory the adsorption and sensing behaviors of Pd-doped ZnO (Pd-ZnO) monolayers with two typical dissolved gases, namely, H2 and C2H2, to explore their sensing use for dissolved gas analysis in transformer oil. For Pd doping on the pristine ZnO monolayer, the TO site is identified as the most stable configuration with an E b of -1.44 eV. For the adsorption of H2 and C2H2, chemisorption is determined given the large adsorption energy (E ad) and formation of new bonds. Analyses of the charge density difference and density of state provide evidence of the strong binding force of Pd-H and Pd-C bonds, while band structure analysis provides the sensing mechanism of the Pd-ZnO monolayer as a resistance-type sensor for H2 and C2H2 detection with high electrical responses. Also, analysis of the work function (WF) provides the possibility of selective detection of H2 and C2H2 using a Pd-ZnO monolayer-based field-effect transistor sensor given the opposite changing trend of the WF after their adsorption. Our work may broaden the application of ZnO-based gas sensors for application in the field of electrical engineering.

Recent Advances of SnO2-Based Sensors for Detecting Volatile Organic Compounds

SnO₂ based sensors has received extensive attention in the field of toxic gas detection due to their excellent performances with high sensitivity, fast response, long-term stability. Volatile organic compounds (VOCs), originate from industrial production, fuel burning, detergent, adhesives, and painting, are poisonous gases with significant effects on air quality and human health. This mini-review focuses on significant improvement of SnO₂ based sensors in VOCs detection in recent years. In this review, the sensing mechanism of SnO₂-based sensors detecting VOCs are discussed. Furthermore, the improvement strategies of the SnO₂ sensor from the perspective of nanomaterials are presented. Finally, this paper summarizes the sensing performances of these SnO₂ nanomaterial sensors in VOCs detection, and the future development prospect and challenges is proposed.

Volatile Organic Compounds Gas Sensors Based on Molybdenum Oxides: A Mini Review

As a typical n-type semiconductor, MoO₃ has been widely applied in the gas-detection field due to its competitive physicochemical properties and ecofriendly characteristics. Volatile organic compounds (VOCs) are harmful to the atmospheric environment and human life, so it is necessary to quickly identify the presence of VOCs in the air. This review briefly introduced the application progress of an MoO₃-based sensor in VOCs detection. We mainly emphasized the optimization strategies of a high performance MoO₃, which consists of morphology-controlled synthesis and electronic properties functional modification. Besides the general synthesis methods, its gas-sensing properties and mechanism were briefly discussed. In conclusion, the application status of MoO₃ in gas-sensing and the challenges still to be solved were summarized.

Application of WO3 Hierarchical Structures for the Detection of Dissolved Gases in Transformer Oil: A Mini Review

Oil-immersed power transformers are considered to be one of the most crucial and expensive devices used in power systems. Hence, high-performance gas sensors have been extensively explored and are widely used for detecting fault characteristic gases dissolved in transformer oil which can be used to evaluate the working state of transformers and thus ensure the reliable operation of power grids. Hitherto, as a typical n-type metal-oxide semiconductor, tungsten trioxide (WO₃) has received considerable attention due to its unique structure. Also, the requirements for high quality gas detectors were given. Based on this, considerable efforts have been made to design and fabricate more prominent WO₃ based sensors with higher responses and more outstanding properties. Lots of research has focused on the synthesis of WO₃ nanomaterials with different effective and controllable strategies. Meanwhile, the various morphologies of currently synthesized nanostructures from 0-D to 3-D are discussed, along with their respective beneficial characteristics. Additionally, this paper focused on the gas sensing properties and mechanisms of the WO₃ based sensors, especially for the detection of fault characteristic gases. In all, the detailed analysis has contributed some beneficial guidance to the exploration on the surface morphology and special hierarchical structure of WO₃ for highly sensitive detection of fault characteristic gases in oil-immersed transformers.

Influence of Mg Doping Levels on the Sensing Properties of SnO2 Films

This work presents the effect of magnesium (Mg) doping on the sensing properties of tin dioxide (SnO2) thin films. Mg-doped SnO2 films were prepared via a spray pyrolysis method using three doping concentrations (0.8 at.%, 1.2 at.%, and 1.6 at.%) and the sensing responses were obtained at a comparatively low operating temperature (160 °C) compared to other gas sensitive materials in the literature. The morphological, structural and chemical composition analysis of the doped films show local lattice disorders and a proportional decrease in the average crystallite size as the Mg-doping level increases. These results also indicate an excess of Mg (in the samples prepared with 1.6 at.% of magnesium) which causes the formation of a secondary magnesium oxide phase. The films are tested towards three volatile organic compounds (VOCs), including ethanol, acetone, and toluene. The gas sensing tests show an enhancement of the sensing properties to these vapors as the Mg-doping level rises. This improvement is particularly observed for ethanol and, thus, the gas sensing analysis is focused on this analyte. Results to 80 ppm of ethanol, for instance, show that the response of the 1.6 at.% Mg-doped SnO2 film is four times higher and 90 s faster than that of the 0.8 at.% Mg-doped SnO2 film. This enhancement is attributed to the Mg-incorporation into the SnO2 cell and to the formation of MgO within the film. These two factors maximize the electrical resistance change in the gas adsorption stage, and thus, raise ethanol sensitivity.

Using Pd-Doped γ-Graphyne to Detect Dissolved Gases in Transformer Oil: A Density Functional Theory Investigation

To realize a high response and high selectivity gas sensor for the detection dissolved gases in transformer oil, in this study, the adsorption of four kinds of gases (H₂, CO, C₂H₂, and CH₄) on Pd-graphyne was investigated, and the gas sensing properties were evaluated. The energetically-favorable structure of Pd-Doped γ-graphyne was first studied, including through a comparison of different adsorption sites and a discussion of the electronic properties. Then, the adsorption of these four molecules on Pd-graphyne was explored. The adsorption structure, adsorption energy, electron transfer, electron density distribution, band structure, and density of states were calculated and analyzed. The results show that Pd prefers to be adsorbed on the middle of three C≡C bonds, and that the band gap of γ-graphyne becomes smaller after adsorption. The CO adsorption exhibits the largest adsorption energy and electron transfer, and effects an obvious change to the structure and electronic properties to Pd-graphyne. Because of the conductance decrease after adsorption of CO and the acceptable recovery time at high temperatures, Pd-graphyne is a promising gas sensing material with which to detect CO with high selectivity. This work offers theoretical support for the design of a nanomaterial-based gas sensor using a novel structure for industrial applications.