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Using density functional theory, the adsorption behavior of three toxic gases Cl2, NO and SO2 on Cr3 cluster doped GaSe monolayer was studied in this paper. In order to discuss the adsorption characteristics, the adsorption models were established, the adsorption parameters were calculated and the electronic properties were analyzed. Through the results it is found that Cr3 cluster doping greatly improved the adsorption capacity of GaSe monolayer to three toxic gases. Compared with intrinsic GaSe monolayer, the adsorption energy of Cr3 doped GaSe monolayer for Cl2, NO and SO2 increased from −0.842 eV to −6.671 eV, −0.568 eV to −3.546 eV and −0.686 eV to −3.608 eV, respectively. As can be seen, all three kinds of adsorption on Cr3-GaSe monolayer are chemisorption. After gas adsorption, the conductivity of the three systems decreased in different degrees making Cr3-GaSe as a resistive gas sensor possible. In addition, the recovery time of the three gases on the Cr3-GaSe monolayer is extremely long, which indicates that it is difficult for the gases to desorb from the adsorption material surface, and this material has a positive effect on the removal of toxic gases. Therefore, Cr3-GaSe monolayer, as the substrate material of disposable resistive sensors and scavengers, has huge potential in the area of toxic gases detection and removal.

High-performance sensors for toxic gases have been the goal of research in the industry. In this paper, the adsorption of seven toxic target gases, NO, NO2, NH3, H2S, CO, CH4 and HCHO, on the intrinsic and modified In2O3 (110) surface is investigated based on Density functional theory (DFT). Relevant parameters such as adsorption energy, charge transfer, adsorption distance and band gap are calculated and a combination of density of states (DOS), deformation charge density (DCD) and frontier molecular orbital theory are employed to investigate the application of In2O3 (110) in gas sensing. Theoretical recovery times were also calculated to provide a basis for the reusability of In2O3 (110) gas sensors. Our calculations show that the intrinsic In2O3 (110) surface responds to several toxic gases, while the Ag dopant enhances the adsorption of In2O3 on NO2 while suppressing its response to HCHO and H2S gases, making Ag-doped In2O3 (110) a promising candidate for a highly selective sensor for NO2.

The adsorption properties of Ag embedded HfS2 (Ag-HfS2) monolayers to SF6 decomposition gases (SO2, H2S, HF, SOF2 and SO2F2) were investigated based on density functional theory (DFT). The embedded Ag atoms are stably bound to the sulfur vacancies of the monolayer HfS2, and still maintain the semiconducting properties by analyzing the deformation charge density (DCD), the band structure and the density of states (DOS). The adsorption geometry, charge transfer and DOS of these five gas molecules on Ag-HfS2 monolayer are discussed in detail. The adsorption studies on the gases show that the Ag-HfS2 monolayer has excellent sensitivity for H2S and SO2F2 gases, with adsorption energies of 1.088 and 2.998 eV, respectively. And estimated the gas desorption time in Ag-HfS2 monolayer to screen its application in gas sensitive materials and gas sensors. The results of this study may open up new ideas for researchers to explore highly active HFS2-based two-dimensional nanomaterials.

Transition metal dichalcogenides (TMDs) have been widely explored for their excellent gas sensing properties, especially high sensitivity and stability at room temperature. MoTe2 exhibits good sensitivity and selectivity to some nitrogen-containing gases (i.e., NO2, NH3) and has received extensive attention in gas sensing. In addition, increasingly complex production environments place demands on high-quality gas sensors. Therefore, worldwide efforts are devoted to designing and manufacturing MoTe2-based gas sensors with faster response and recovery speed. This paper summarizes the research progress of MoTe2-based gas sensing, focuses on the practical measures to improve the response and recovery speed of MoTe2-based sensors, and discusses the mechanism. This provides guidance for exploring higher performance MoTe2 sensors.

During the COVID-19 epidemic in Wuhan, China, a series of measures were implemented by the government to prevent the spread of disease, including the lockdown policy and construction of emergency hospitals. To estimate the impact of these measures on aquatic environments, turbidity of lakes in Wuhan was dynamically monitored by integrating multi-sensor satellite observations. Calibrated against field measurements, empirical turbidity models were developed with high accuracy (R2 = 0.77, RMSE = 3.13 NTU). Time series of lake turbidity during COVID-19 were then retrieved, and possible factors for the turbidity change were discussed, including meteorological conditions and human activities. Results demonstrated that (1) the mean turbidity showed a 24.9% decline from 33.4 NTU to 25.1 NTU after the lockdown in Wuhan, which dropped 16.0% compared to that in the previous year. This decline might be related to the sharp reduction in human activities after the lockdown; (2) no obvious turbidity disturbance was observed in the lakes around emergency hospitals during their construction, and the lakes remained stable after the operation of hospitals. The method of integrating multi-sensor satellite observations used in this study shows great performance in term of temporal resolution for dynamic monitoring of inland water.

The detection of dissolved gases in oil is an important method for the analysis of transformer fault diagnosis. In this article, the potential-doped structure of the Ag3 cluster on the HfSe2 monolayer and adsorption behavior of CO and C2H4 upon Ag3–HfSe2 were studied theoretically. Herein, the binding energy, adsorption energy, band structure, density of state (DOS), partial density of state (PDOS), Mulliken charge analysis, and frontier molecular orbital were investigated. The results showed that the adsorption effect on C2H4 is stronger than that on CO. The electrical sensitivity and anti-interference were studied based on the bandgap and adsorption energy of gases. In particular, there is an increase of 55.49% in the electrical sensitivity of C2H4 after the adsorption. Compared to the adsorption energy of different gases, it was found that only the adsorption of the C2H4 system is chemisorption, while that of the others is physisorption. It illustrates the great anti-interference in the detection of C2H4. Therefore, the study explored the potential of HfSe2-modified materials for sensing and detecting CO and C2H4 to estimate the working state of power transformers.

In this study, the adsorption of noxious gas molecules (NO, Cl2, and O3) on GaN and Au-decorated GaN was systematically scrutinized, and the adsorption energy, bond length, charge, density of state (DOS), partial density of state (PDOS), electron deformation density (EDD), and orbitals were analyzed by the density functional theory (DFT) method. It is found that the interaction between NO and pristine GaN is physical adsorption, while GaN chemically reacts with Cl2 and O3. These observations suggest that pristine GaN may be a candidate for the detection of Cl2 and O3. The highly activated Au-decorated GaN can enhance the adsorption performance toward NO and convert the physical adsorption for NO into chemical adsorption, explaining the fact that precious metal doping is essential for regulating the electronic properties of the substrate material. This further confirms the well-established role of Au-decorated GaN in NO gas-sensing applications. In addition, the adsorption performance of Au-decorated GaN for Cl2 and O3 molecules is highly improved, which provides guidance to scavenge toxic gases such as Cl2 and O3 by the Au-decorated GaN material.

Hydrogen sulfide (H2S) and sulfur dioxide (SO2) are two typical decomposition byproducts of sulfur hexafluoride (SF6), commonly used as an insulating medium in electrical equipment; for instance, in gas circuit breakers and gas insulated switchgears. In our work, fiber-like p-CuO/n-ZnO heterojunction gas sensing materials were successfully prepared via the electrospinning method to detect the SF6 decomposition byproducts, H2S and SO2 gases. The sensing results demonstrated that p-CuO/n-ZnO nanofiber sensors have good sensing performance with respect to H2S and SO2. It is noteworthy that this fiber-like p-CuO/n-ZnO heterojunction sensor exhibits higher and faster response–recovery time to H2S and SO2. The enhanced sensor performances can probably be attributed to the sulfuration–desulfuration reaction between H2S and the sensing materials. Moreover, the gas sensor exhibited a high response to the low exposure of H2S and SO2 gas (below 5 ppm). Towards the end of the paper, the gas sensing mechanism of the prepared p-CuO/n-ZnO heterojunction sensors to SO2 and H2S is discussed carefully. Calculations based on first principles were carried out for Cu/ZnO to construct adsorption models for the adsorption of SO2 and H2S gas molecules. Information on adsorption energy, density of states, energy gap values and charge density were calculated and compared to explain the gas-sensitive mechanism of ZnO on SO2 and H2S gases.

Excessive ethanol gas is a huge safety hazard, and people will experience extreme discomfort after inhalation, so efficient ethanol sensors are of great importance. This article reports on ethanol gas sensors that use NiO hollow spheres assembled from nanoparticles, nanoneedles, and nanosheets prepared by the hydrothermal method. All of the samples were characterized for performance evaluation. The sensors based on the NiO hollow spheres showed a good response to ethanol, and the hollow spheres assembled from nanosheets (NiO-S) obtained the best ethanol gas-sensing performance. NiO-S provided a larger response value (38.4) at 350 °C to 200 ppm ethanol, and it had good stability and reproducibility. The nanosheet structure and the fluffy surface of NiO-S obtained the largest specific surface area (55.20 m2/g), and this structure was beneficial for the sensor to adsorb more gas molecules in an ethanol atmosphere. In addition, the excellent sensing performance could ascribe to the larger Ni3+/Ni2+ of NiO-S, which achieved better electronic properties. Furthermore, in terms of commercial production, the template-free preparation of NiO-S eliminated one step, saving time and cost. Therefore, the sensors based on NiO-S will serve as candidates for ethanol sensing.

Using the first-principles theory, this study explored the electronic behavior and adsorption effect of SO2 on an InP3 monolayer doped with transition metal atoms (Pd, Pt, Au, Fe, Co and Mo). Through calculation and analysis, the optimum doping sites of TM dopants on the InP3 monolayer were determined, and the adsorption processes of SO2 by TM-InP3 monolayers were simulated. In the adsorption process, all TM-InP3 monolayers and SO2 molecules were deformed to some extent. All adsorption was characterized as chemical adsorption, and SO2 acted as an electron acceptor. Comparing Ead and Qt, the order of the SO2 adsorption effect was Mo-InP3 > Fe-InP3 > Co-InP3 > Pt-InP3 > Pd-InP3 > Au-InP3. Except for the Au atom, the other five TM atoms as dopants all enhanced the adsorption effect of InP3 monolayers for SO2. Furthermore, the analysis of DCD and DOS further confirmed the above conclusions. Based on frontier orbital theory analysis, it is revealed that the adsorption of SO2 reduces the conductivity of TM-InP3 monolayers to different degrees, and it is concluded that Pd-InP3, Pt-InP3, Fe-InP3 and Mo-InP3 monolayers have great potential in the application of SO2 resistive gas sensors. This study provides a theoretical basis for further research on TM-InP3 as a SO2 sensor.

In this paper, novel hierarchical undoped NiO and W-doped NiO microflowers were successfully synthesized via a facile hydrothermal route, and their sensing performance for ethanol was explored. Strikingly, the doping of W intervened the growth and assembly of NiO nanosheets to form different flower-like microstructures. The introduction of W caused beneficial morphological improvements from loose to dense microflower. Further ethanol sensing tests showed that the fabricated dense microflower based sensor possessed much higher response (60.15) and remarkable selectivity than that of the loose microflower at the optimal temperature of 300 °C. A plausible enhanced mechanism was proposed which demonstrated the improved properties may be ascribed to the large specific surface area and well-defined microstructure for gas adsorption and reaction.

Transformer oil is an important insulating material in power transformers. The detection of transformer oil is an important means to ensure the normal operation of the power system, which is recognized by the public. Interfacial tension (IFT) is an important parameter to characterize the flow properties of liquids. Too low interfacial tension of transformer oil can cause major accidents in transformers. Therefore, it is of great practical significance to achieve effective detection of interfacial tension. This work proposes the measurement of the IFT of transformer oil using multi frequency ultrasonic and a support vector machine that was optimized by particle swarm optimization algorithm (PSO-SVM). 210 samples, which were detected by multi frequency ultrasonic and the Ring Method, were divided into training sets (200 samples) and test sets (10 samples). Then multi-frequency ultrasonic data is subjected to MDS dimensionality reduction to obtain 11 dimensional low-dimensional data which as the input of SVM, and the IFT, which was detected by the Ring Method, as the output of SVM. After that, a particle swarm optimization algorithm (PSO) was incorporated to optimize the parameters (C, g) for a support vector machine (SVM).Then, the SVM model with the optimized parameters (g=1.356 and C=2.831) was trained with the training sets, and the model was verified with the test sets. Results show that the model, which proposed in this article, that describes the nonlinear relationship between multi frequency ultrasonic data and the interfacial tension of transformer oil shows higher accuracy.

In this paper, the adsorption behaviors of three gases (H2, CO, and C2H2) decomposed by the transformer oil on Pd-GaSe and Pd3-GaSe monolayers were calculated by density functional theory. Compared with Pd single-atom doping, Pd3 cluster doping changed the original structure and charge distribution to a greater extent, and more obviously improved the conductivity. According to the analysis of adsorption energy, charge transfer and deformation charge density, the results show that the two doped structures have better adsorption performance for the three gas molecules (H2, CO, and C2H2) than the intrinsic GaSe monolayer. Compared with Pd-GaSe, Pd3-GaSe showed stronger adsorption property for the three gases. Analysis of frontier molecular orbitals and recovery characteristics shows that Pd3-GaSe can be used as an ideal gas sensitive material for H2 detection because of its good desorption properties and obvious conductivity changes. Pd-GaSe can be used as a disposable resistive sensor for CO. Pd3-GaSe is a kind of sensing material suitable for disposable resistance sensors for CO and C2H2. These two doped structures have great application potential in gas adsorption and detection, and provide indications for further study on gas sensor detection by means of metal-doped GaSe monolayer.

Detecting the decomposition components of SF6 insulating gas is recognized as an effective means to monitor the operating status of the SF6 insulating switch. In this paper, the adsorption characteristics of a new two-dimensional material GeSe for five SF6 decomposition gases (SO2, SOF2, SO2F2, H2S and HF) are reported by first-principles simulation. Through the analysis of the change of energy band structure, density of states distribution, and gas desorption time, it is found that GeSe has the potential as a gas-sensitive material for the selective detection of SO2F2, and the computational work in this paper provides theoretical guidance for the development of new gas-sensitive sensors applied in monitoring SF6 insulated switches.

A large amount of power equipment works in closed or semi-closed environments for a long time. Carbon monoxide (CO) is the most prevalent discharge gas following a fault in the components. Based on the density functional theory of first principles, the adsorption behavior of CO gas molecules on intrinsic, Ag-doped and Au-doped hafnium disulfide (HfS2) monolayers was systematically studied at the atomic scale. Firstly, the intrinsic HfS2 monolayer, Ag-doped HfS2 (Ag-HfS2) monolayer and Au-doped HfS2 (Au-HfS2) monolayer, with different doping sites, were created. The structural stability, dopant charge transfer, substrate conductivity and energy band structure of different doping sites of the Ag-HfS2 and Au-HfS2 monolayer structures were calculated. The most stable doping structure was selected with which to obtain the best performance on the subsequent gas adsorption test. Then, the CO adsorption models of intrinsic HfS2, Ag-HfS2 and Au-HfS2 were constructed and geometrically optimized. The results show that the adsorption energy of the Ag-HfS2 monolayer for CO gas is −0.815 eV, which has good detection sensitivity and adsorption performance. The adsorption energy of CO on the Au-HfS2 monolayer is 2.142 eV, the adsorption cannot react spontaneously, and the detection sensitivity is low. The research content of this paper provides a theoretical basis for the design and research of gas sensing materials based on HfS2, promoting the development and application of HfS2 in gas sensing and other fields.

Dissolved gas analysis (DGA) is recognized as one of the most reliable methods in transformer fault diagnosis technology. In this paper, three characteristic gases of transformer oil (CO, C2H4, and CH4) were used in conjunction with a Cr-decorated InN monolayer according to first principle calculations. The adsorption performance of Cr–InN for these three gases were studied from several perspectives such as adsorption structures, adsorption energy, electron density, density of state, and band gap structure. The results revealed that the Cr–InN monolayer had good adsorption performance with CO and C2H4, while the band gap of the monolayer slightly changed after the adsorption of CO and C2H4. Additionally, the adsorption property of the Cr–InN monolayer on CH4 was acceptable and a significant response was simultaneously generated. This paper provides the first insights regarding the possibility of Cr-doped InN monolayers for the detection of gases dissolved in oil.

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.

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.

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.

C2H6 and C2H4 gases are two typical decompositions produced by partial discharge of transformer oil. To fully evaluate the feasibility of MoS2-based materials for the detection of C2H6 and C2H4 gases, the adsorption of C2H6 and C2H4 molecules on intrinsic and Au-doped MoS2 monolayer have been studied in this paper by the First-principle of Density Functional Theory (DFT). The adsorption mechanism of MoS2-based monolayer were investigated carefully in terms of adsorption energy, adsorption distance, bandgap structure, charge transfer and density of states (DOS). The calculated results show that the adsorption structures of the C2H6 and C2H4 molecules on Au-doped MoS2 monolayer with larger adsorption energies were stable, and have shorter adsorption distance, higher charge transfer, and stronger orbital hybridization compared with the corresponding MoS2 monolayer adsorption structures. It is concluded that the doped-Au atom affects the electronic structure of MoS2 monolayer to enhance the adsorption capacity. From this aspect, the present research offers a theoretical guidance to the application of Au-doped MoS2 materials as the sensing material for C2H6 and C2H4 gases.

Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method.

As an insulating medium, sulfur hexafluoride (SF6) is extensively applied to electrical insulation equipment to ensure its normal operation. However, both partial discharge and overheating may cause SF6 to decompose, and then the insulation strength of electrical equipment will be reduced. The adsorption properties and sensing mechanisms of four SF6 decomposed components (HF, SO2, SOF2 and SO2F2) upon an Au-modified InN (Au-InN) monolayer were studied in this work based on first-principles theory. Meanwhile, the adsorption energy (Ead), charge transfer (QT), deformation charge density (DCD), density of states (DOS), frontier molecular orbital and recovery property were calculated. It can be observed that the structures of the SO2, SOF2 and SO2F2 molecules changed significantly after being adsorbed. Meanwhile, the Ead and QT of these three adsorption systems are relatively large, while that of the HF adsorption system is the opposite. These phenomena indicate that Au-InN monolayer has strong adsorption capacity for SO2, SOF2 and SO2F2, and the adsorption can be identified as chemisorption. In addition, through the analysis of frontier molecular orbital, it is found that the conductivity of Au-InN changed significantly after adsorbing SO2, SOF2 and SO2F2. Combined with the analysis of the recovery properties, since the recovery time of SO2 and SO2F2 removal from Au-InN monolayer is still very long at 418 K, Au-InN is more suitable as a scavenger for these two gases rather than as a gas sensor. Since the recovery time of the SOF2 adsorption system is short at 418 K, and the conductivity of the system before and after adsorption changes significantly, Au-InN is an ideal SOF2 gas-sensing material. These results show that Au-InN has broad application prospects as an SO2, SOF2 and SO2F2 scavenger and as a resistive SOF2 sensor, which is of extraordinary meaning to ensure the safe operation of power systems. Our calculations can offer a theoretical basis for further exploration of gas adsorbent and resistive sensors prepared by Au-InN.

The adsorption and sensing behavior of three typical industrial toxic gases NO, NO2 and SO2 by the Pd modified C3N monolayer were studied in this work on the basic first principles theory. Meanwhile, the feasibility of using the Pd doped C3N monolayer (Pd-C3N) as a sensor and adsorbent for industrial toxic gases was discussed. First, the binding energies of two doping systems were compared when Pd was doped in the N-vacancy and C-vacancy sites of C3N to choose the more stable doping structure. The result shows that the doping system is more stable when Pd is doped in the N-vacancy site. Then, on the basis of the more stable doping model, the adsorption process of NO, NO2 and SO2 by the Pd-C3N monolayer was simulated. Observing the three gases adsorption systems, it can be found that the gas molecules are all deformed, the adsorption energy (Ead) and charge transfer (QT) of three adsorption systems are relatively large, especially in the NO2 adsorption system. This result suggests that the adsorption of the three gases on Pd-C3N belongs to chemisorption. The above conclusions can be further confirmed by subsequent deformable charge density (DCD) and density of state (DOS) analysis. Besides, through analyzing the band structure, the change in electrical conductivity of Pd-C3N after gas adsorption was studied, and the sensing mechanism of the resistive Pd-C3N toxic gas sensor was obtained. The favorable adsorption properties and sensing mechanism indicate that the toxic gas sensor and adsorbent prepared by Pd-C3N have great application potential. Our work may provide some guidance for the application of a new resistive sensor and gas adsorbent Pd-C3N in the field of toxic gas monitoring and adsorption.

In this work, Cr2O3 nanoparticles, and SnO2 nanofibers were fabricated by a sol–gel process and an electrospinning method, respectively. Gas sensitive materials with high sensitivity to C2H2 gas were obtained by coating Cr2O3 nanoparticles on SnO2 nanofibers. The prepared Cr2O3 nanoparticle-coated SnO2 nanofibers (Cr2O3 NPs. coated SnO2 NFs.) were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), X-ray energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and the gas sensing behaviors to C2H2 were studied. The Cr2O3 NPs. coated SnO2 NFs. exhibited low optimal operating temperature, high sensing response, excellent response-recovery time, and long-term stability to C2H2. The optimal operating temperature of the measured material to 20 ppm C2H2 was about 220°C and the C2H2 concentration had a good linear relationship with the response value when the concentration was 60 ppm. In addition, a reasonable gas sensing mechanism was proposed which may enhance the gas sensing performances for the Cr2O3 NPs. coated SnO2 NFs. to C2H2.

Hollow structured nanofibers have attracted much attention in diverse domains owing to their unique physicochemical properties and characteristics. Gas sensing is one of the most promising applications. In electrical engineering, the detection of SF6 decomposing gas products is significant to monitor the insulation status online of gas insulated switchgear (GIS). This mini-review presents the developments of hollow structured nanofibers in synthesis strategies and gas sensing application, especially in the detection of SF6 decomposing gas products, including hydrogen disulfide (H2S), sulfur dioxide (SO2), thionyl fluoride (SOF2), and sulfuryl fluoride (SO2F2). In addition, the gas sensing mechanism of metal oxide hollow nanofibers based gas sensor are discussed.

H2S and SOF2 gas are two typical decomposition products of SF6 gas under partial discharge condition. Based on the density functional theory (DFT), several doping structures of Si-MoS2 and adsorption structures of gas adsorbed Si-MoS2 were investigated. The electronic property, adsorption energy, charge transfer, and electron density difference were calculated to analyze the adsorption mechanism. Compared with the structure of pristine MoS2 monolayer, Si doping improves the surface activity of MoS2 monolayer. Moreover, the introduction of Si atom increases the effects of orbital hybridization between gas molecules and MoS2 monolayer, and promotes the charge transfer. Especially, SOF2 possesses a large adsorption energy with Si-MoS2 by crossing a small energy barrier. In addition, the good compatibility of Si-MoS2 with SF6 atmosphere, makes it a promising adsorbent for SF6 decomposition products removal. Keywords: H2S, SOF2, Si-MoS2 absorbent, DFT calculations

Hydrogen sulfide (H2S) is an important decomposition component of sulfur hexafluoride (SF6), which has been extensively used in gas-insulated switchgear (GIS) power equipment as insulating and arc-quenching medium. In this work, electrospun ZnO-SnO2 composite nanofibers as a promising sensing material for SF6 decomposition component H2S were proposed and prepared. The crystal structure and morphology of the electrospun ZnO-SnO2 samples were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM), respectively. The composition of the sensitive materials was analyzed by energy dispersive X-ray spectrometers (EDS) and X-ray photoelectron spectroscopy (XPS). Side heated sensors were fabricated with the electrospun ZnO-SnO2 nanofibers and the gas sensing behaviors to H2S gas were systematically investigated. The proposed ZnO–SnO2 composite nanofibers sensor showed lower optimal operating temperature, enhanced sensing response, quick response/recovery time and good long-term stability against H2S. The measured optimal operating temperature of the ZnO–SnO2 nanofibers sensor to 50 ppm H2S gas was about 250°C with a response of 66.23, which was 6 times larger than pure SnO2 nanofibers sensor. The detection limit of the fabricated ZnO–SnO2 nanofibers sensor toward H2S gas can be as low as 0.5 ppm. Finally, a plausible sensing mechanism for the proposed ZnO–SnO2 composite nanofibers sensor to H2S was also discussed.

In order to find an excellent sensing material for dissolved gases in transformer oil, the adsorption structures of intrinsic graphene (IG), Ge-doped graphene (GeG), and Cr-doped graphene (CrG) to H2 and C2H2 gas molecules were built. It was found that the doping site right above C atom (T) was the most stable structure by studying three potential doping positions of the Ge and Cr atom on the graphene surface. Then, the structural parameters, density of states, and difference state density of these adsorption systems were calculated and analyzed based on the density functional calculations. The results show that the adsorption properties of GeG and CrG systems for H2 and C2H2 are obviously better than the IG system. Furthermore, by comparing the two doping systems, CrG system exhibits more outstanding adsorption performances to H2 and C2H2, especially for C2H2 gas. Finally, the highest adsorption energy (−1.436 eV) and the shortest adsorption distance (1.981 Å) indicate that Cr-doped graphene is promising in the field of C2H2 gas-sensing detection.

First-principle calculations were carried out to simulate the three decomposition gases (SO2, SOF2, and SO2F2) of sulfur hexafluoride (SF6) on Ga-doped MoS2 (Ga-MoS2) monolayer. Based on density functional theory (DFT), pure MoS2 and multiple gas molecules (SF6, SO2, SOF2, and SO2F2) were built and optimized to the most stable structure. Four types of Ga-doped positions were considered and it was found that Ga dopant preferred to be adsorbed by the top of Mo atom (TMo). For the best adsorption effect, two ways of SO2, SOF2, and SO2F2 to approach the doping model were compared and the most favorable mode was selected. The adsorption parameters of Ga-MoS2 and intrinsic MoS2 were calculated to analyze adsorption properties of Ga-MoS2 towards three gases. These analyses suggested that Ga-MoS2 could be a good gas-sensing material for SO2 and SO2F2, while it was not suitable for SOF2 sensing due to its weak adsorption. This work provides a theoretical basis for the development of Ga-MoS2 materials with the hope that it can be used as a good gas-sensing material for electrical equipment.

In this study, the adsorption performances of graphene before and after modification to H2S and CH4 molecules were studied using first principles with the density functional theory (DFT) method. The most stable adsorption configuration, the adsorption energy, the density of states, and the charge transfer are discussed to research the adsorption properties of intrinsic graphene (IG), Ni-doped graphene (Ni−G), vacancy defect graphene (DG), and graphene oxide (G−OH) for H2S and CH4. The weak adsorption and charge transfer of IG achieved different degrees of promotion by doping the Ni atom, setting a single vacancy defect, and adding oxygen-containing functional groups. It can be found that a single vacancy defect significantly enhances the strength of interaction between graphene and adsorbed molecules. DG peculiarly shows excellent adsorption performance for H2S, which is of great significance for the study of a promising sensor for H2S gas.

Accurate monitoring of plant phenology is vital to effective understanding and prediction of the response of vegetation ecosystems to climate change. Satellite remote sensing is extensively employed to monitor vegetation phenology. However, fall phenology, such as peak foliage coloration, is less well understood compared with spring phenological events, and is mainly determined using the vegetation index (VI) time-series. Each VI only emphasizes a single vegetation property. Thus, selecting suitable VIs and taking advantage of multiple spectral signatures to detect phenological events is challenging. In this study, a novel grouping-based time-series approach for satellite remote sensing was proposed, and a wide range of spectral wavelengths was considered to monitor the complex fall foliage coloration process with simultaneous changes in multiple vegetation properties. The spatial and temporal scale effects of satellite data were reduced to form a reliable remote sensing time-series, which was then divided into groups, namely pre-transition, transition and post-transition groups, to represent vegetation dynamics. The transition period of leaf coloration was correspondingly determined to divisions with the smallest intra-group and largest inter-group distances. Preliminary results using a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2002 to 2013 at the Harvard Forest (spatial scale: ~3500 m; temporal scale: ~8 days) demonstrated that the method can accurately determine the coloration period (correlation coefficient: 0.88; mean absolute difference: 3.38 days), and that the peak coloration periods displayed a shifting trend to earlier dates. The grouping-based approach shows considerable potential in phenological monitoring using satellite time-series.

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.

The effect of silica nanoparticle (Nano-SiO2) dopants on insulation paper cellulose, and the interaction between them, was investigated using molecular dynamics simulations. The mechanical properties, interactions, and cellulose-Nano-SiO2 compatibility of composite models of cellulose doped with Nano-SiO2 were studied. An increase in Nano-SiO2 size leads to a decrease in the mechanical properties, and a decrease in the anti-deformation ability of the composite model. The binding energies and bond energies per surface area of the composite models indicate that the bonding interaction between spherical Nano-SiO2 and cellulose is the strongest among the four different Nano-SiO2 shapes that are investigated. The solubilities of the four composite models decrease with increasing Nano-SiO2 size, and the difference between the solubility of pure cellulose and those of the composite models increases with increasing Nano-SiO2 size. Good doping effects with the highest cellulose-Nano-SiO2 compatibility are achieved for the cellulose model doped with spherical Nano-SiO2 of 10 Å in diameter. These findings provide a method for modifying the mechanical properties of cellulose by doping, perhaps for improving insulation dielectrics.

In this paper, the porous NiO/SnO2 nanofibers were synthesized via the electrospinning method along with the carbonization process. The characterization results show that the pristine SnO2-based nanofibers can form porous structure with different grain size by carbonization. The hydrogen gas-sensing investigations indicate that the NiO/SnO2 sensor exhibits more prominent sensing properties than those of pure SnO2 sensor devices. Such enhanced performance is mainly attributed to the porous nanostructure, which can provide large active adsorption sites for surface reaction. Moreover, the existence of p-n heterojunctions between NiO and SnO2 also plays a key role in enhancing gas-sensing performances. Finally, the H2 sensing mechanism based on the NiO/SnO2 nanocomposite was proposed for developing high-performance gas sensor devices.

In this study, we reported a successful synthesis of a nanocomposite based on SnO2 nanoneedles anchored to NiO microsphere by a simple two-step hydrothermal route. The results show that the SnO2/NiO nanocomposite-based sensor exhibits more prominent performances than the pristine NiO microsphere to NO2 such as larger responses and more outstanding repeatability. The improved properties are mainly attributed to the p−n heterojunctions formed at the SnO2−NiO interface, leading to the change of potential barrier height and the enlargement of the depletion layer. Besides, the novel and unique nanostructure provides large and effective areas for the surface reaction. In addition, a plausible growth mechanism and the enhanced sensing mechanism were proposed to further discuss the special nanostructure which will benefit the exploration of high-performance sensors.

The water content in oil is closely related to the deterioration performance of an insulation system, and accurate prediction of water content in oil is important for the stability and security level of power systems. A novel method of measuring water content in transformer oil using multi frequency ultrasonic with a back propagation neural network that was optimized by principal component analysis and genetic algorithm (PCA-GA-BPNN), is reported in this paper. 160 oil samples of different water content were investigated using the multi frequency ultrasonic detection technology. Then the multi frequency ultrasonic data were preprocessed using principal component analysis (PCA), which was implemented to obtain main principal components containing 95% of original information. After that, a genetic algorithm (GA) was incorporated to optimize the parameters for a back propagation neural network (BPNN), including the weight and threshold. Finally, the BPNN model with the optimized parameters was trained with a random 150 sets of pretreatment data, and the generalization ability of the model was tested with the remaining 10 sets. The mean squared error of the test sets was 8.65 × 10−5, with a correlation coefficient of 0.98. Results show that the developed PCA-GA-BPNN model is robust and enables accurate prediction of a water content in transformer oil using multi frequency ultrasonic technology.

The influence of the thermal field of a transformer during operation on the thermal stability of meta-aramid insulation paper was studied through molecular dynamics simulations. Models of the crystalline and amorphous regions of meta-aramid fibers were constructed using known parameters. The model of the crystalline area was verified by comparing X-ray diffraction results with experimental data. The reasonableness of the simulation results was judged by the variation of energy, temperature, density, and cell size in relation to the dynamic time. The molecular dynamics simulations revealed that the modulus values in the crystalline regions were two to three times higher than those in the amorphous regions at various temperatures. In addition, the incompressibility, rigidity, deformation resistance, plasticity, and toughness of the crystalline regions were obviously higher than those of amorphous regions, whereas the toughness of the amorphous regions was better than that of the crystalline regions. The mechanical parameters of both the crystalline and amorphous regions of meta-aramid fibers were affected by temperature, although the amorphous regions were more sensitive to temperature than the crystalline regions. The molecular chain motion in the crystalline regions of meta-aramid fibers increased slightly with temperature, whereas that of the amorphous regions was more sensitive to temperature. Analyzing hydrogen bonding revealed that long-term operation at high temperature may destroy the structure of the crystalline regions of meta-aramid fibers, degrading the performance of meta-aramid insulation paper. Therefore, increasing the crystallinity and lowering the transformer operating temperature may improve the thermal stability of meta-aramid insulation paper. However, it should be noted that increasing the crystallinity of insulation paper may lower its toughness. These study results lay a good foundation for further exploration of the ways to improve the performance of meta-aramid insulation paper.

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.

SF6 decomposition components detection is a key technology to evaluate and diagnose the insulation status of SF6-insulated equipment online, especially when insulation defects-induced discharge occurs in equipment. In order to detect the type and concentration of SF6 decomposition components, a Ni-modified carbon nanotube (Ni-CNT) gas sensor has been prepared to analyze its gas sensitivity and selectivity to SF6 decomposition components based on an experimental and density functional theory (DFT) theoretical study. Experimental results show that a Ni-CNT gas sensor presents an outstanding gas sensing property according to the significant change of conductivity during the gas molecule adsorption. The conductivity increases in the following order: H2S > SOF2 > SO2 > SO2F2. The limit of detection of the Ni-CNT gas sensor reaches 1 ppm. In addition, the excellent recovery property of the Ni-CNT gas sensor makes it easy to be widely used. A DFT theoretical study was applied to analyze the influence mechanism of Ni modification on SF6 decomposition components detection. In summary, the Ni-CNT gas sensor prepared in this study can be an effective way to evaluate and diagnose the insulation status of SF6-insulated equipment online.

Morphology Control plays an important role in gas sensing properties of metal oxide semiconductor based gas sensors. In this study, various morphologies of SnO2 nanostructures including nanobulks, nanospheres, nanorods, and nanowires were successfully synthesized via a simple hydrothermal method assisted with different surfactants. X-ray powder diffraction and scanning electron microscopy were employed to characterize the prepared products. Gas sensors were fabricated by screen-printing the as-prepared SnO2 nanostructures onto planar ceramic substrates. Moreover, their gas sensing properties were systematically investigated towards acetylene gas (C2H2), an important fault hydrocarbon dissolved in power transformer oil. Experiments indicate that the SnO2 nanowires based sensor exhibits excellent gas sensing properties, such as lower operating temperature, higher gas response, quicker response-recovery time and good stability than those of SnO2 nanobulks, nanospheres and nanorods. These results imply SnO2 nanowires a promising sensing morphology for C2H2 detection and provide us a feasible way to develop high-performance gas sensor by tailoring the microstructures and morphologies of the materials in further.

Hierarchical flower-like ZnO nanorods, net-like ZnO nanofibers and ZnO nanobulks have been successfully synthesized via a surfactant assisted hydrothemal method. The synthesized products were characterized by X-ray powder diffraction and field emission scanning electron microscopy, respectively. A possible growth mechanism of the various hierarchical ZnO nanostructures is discussed in detail. Gas sensors based on the as-prepared ZnO nanostructures were fabricated by screen-printing on a flat ceramic substrate. Furthermore, their gas sensing characteristics towards methane were systematically investigated. Methane is an important characteristic hydrocarbon contaminant found dissolved in power transformer oil as a result of faults. We find that the hierarchical flower-like ZnO nanorods and net-like ZnO nanofibers samples show higher gas response and lower operating temperature with rapid response-recovery time compared to those of sensors based on ZnO nanobulks. These results present a feasible way of exploring high performance sensing materials for on-site detection of characteristic fault gases dissolved in transformer oil.

Sulfur dioxide, SO2, is one of the most important decomposition byproducts of sulfur hexafluoride, SF6, under partial discharge in GIS apparatus. The sensing performances of semiconductor gas sensors can be improved by morphology tailoring. This paper reported the synthesis method, structural characterization, and SO2 responsive characteristics of hierarchical flower-shaped ZnO nanostructures. Hierarchical ZnO nanoflowers were successfully prepared via a facile and simple hydrothermal method and characterized by X-ray powder diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy, respectively. Planar chemical gas sensor was fabricated and its responsive characteristics towards SO2 were systematically performed. The optimum operating temperature of the fabricated sensor was measured to be about 260°C, and the corresponding maximum responses were 16.72 and 26.14 to 30 and 60 ppm of SO2. Its saturated gas concentration was 2000 ppm with a response value of 67.41. Moreover, a quick response and recovery feature (7 s and 8 s versus 80 ppm of SO2) and good stability were also observed. All results indicate that the proposed sensor is a promising candidate for detecting SF6 decomposition byproduct SO2.

Suspended sediment (SS) is an important water quality indicator of coastal and estuarine ecosystems. Field measurement and satellite remote sensing are the most common approaches for water quality monitoring. However, the efficiency and precision of both methods are typically affected by their sampling strategy (time and interval), especially in highly dynamic coastal and estuarine waters, because only limited measurements are available to analyze the short-term variations or the long-term trends of SS. Dramatic variations of SS were observed, with standard deviation coefficients of 48.9% and 54.1%, at two fixed stations in Deep Bay, China. Therefore, it is crucial to resolve the temporal variations of SS and its main influencing factors, and thus to develop an improved sampling strategy for estuarine ecosystems. Based on two years of continuous high-frequency measurements of SS and concurrent tidal and meteorological data, we demonstrated that the tide is the dominant factor influencing the SS variation among tide, wind (speed and direction), and rainfall in Deep Bay, China. For the monitoring of maximum suspended sediment concentration (SSC), the recommended optimum sampling time coincides with the occurrence of the ebb tides, whereas multiple sampling times are recommended for monitoring of minimum SSC. Although variations of SS are also affected by other factors, the recommended sampling strategy could capture the maximum and minimum SSC variations exactly more than 85% days in a year on average in Deep Bay. This study provides a baseline of SS variation and direct sampling strategy guidance for future SS monitoring and could be extended to other coastal or estuarine waters with similar climatological/tidal exposures.

In this paper, pure and Ag-doped SnO2 nanospheres were synthesized by hydrothermal method and characterized via X-ray powder diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectra (XPS), respectively. The gas sensing performance of the pure, 1 at.%, 3 at.%, and 5 at.% Ag-doped SnO2 sensing devices toward hydrogen (H2) were systematically evaluated. The results indicated that compared with pure SnO2 nanospheres, Ag-doped SnO2 nanospheres could not only decrease the optimum working temperature but also significantly improve H2 sensing such as higher gas response and faster response-recovery. Among all the samples, the 3 at.% Ag-doped SnO2 showed the highest response 39 to 100 μL/L H2 at 300 °C. Moreover, its gas sensing mechanism was discussed, and the results will provide reference and theoretical guidance for the development of high-performance SnO2-based H2 sensing devices.

Coastal water regions represent some of the most fragile ecosystems, exposed to both climate change and human activities. While remote sensing provides unprecedented amounts of data for water quality monitoring on regional to global scales, the performance of satellite observations is frequently impeded by revisiting intervals and unfavorable conditions, such as cloud coverage and sun glint. Therefore, it is crucial to evaluate the impacts of varied sampling strategies (time and frequency) and insufficient observations on the monitoring of short-term and long-term tendencies of water quality parameters, such as suspended solids (SS), in highly dynamic coastal waters. Taking advantage of the first high-frequency in situ SS dataset (at 30 min sampling intervals from 2007 to 2008), collected in Deep Bay, China, this paper presents a quantitative analysis of the influences of sampling strategies on the monitoring of SS, in terms of sampling frequency and time of day. Dramatic variations of SS were observed, with standard deviation coefficients of 48.9% and 54.1%, at two fixed stations; in addition, significant uncertainties were revealed, with the average absolute percent difference of approximately 13%, related to sampling frequency and time, using nonlinear optimization and random simulation methods. For a sampling frequency of less than two observations per day, the relative error of SS was higher than 50%, and stabilized at approximately 10%, when at least four or five samplings were conducted per day. The optimal recommended sampling times for SS were at around 9:00, 12:00, 14:00, and 16:00 in Deep Bay. The “pseudo” MODIS SS dataset was obtained from high-frequency in situ SS measurements at 10:30 and 14:00, masked by the temporal gap distribution of MODIS coverage to avoid uncertainties propagated from atmospheric correction and SS models. Noteworthy uncertainties of daily observations from the Terra/Aqua MODIS were found, with mean relative errors of 19.2% and 17.8%, respectively, whereas at the monthly level, the mean relative error of Terra/Aqua MODIS observations was approximately 10.7% (standard deviation of 8.4%). Sensitivity analysis between MODIS coverage and SS relative errors indicated that temporal coverage (the percentage of valid MODIS observations for a month) of more than 70% is required to obtain high-precision SS measurements at a 5% error level. Furthermore, approximately 20% of relative errors were found with the coverage of 30%, which was the average coverage of satellite observations over global coastal waters. These results highlight the need for high-frequency measurements of geostationary satellites like GOCI and multi-source ocean color sensors to capture the dynamic process of coastal waters in both the short and long term.

A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.

Carbon monoxide (CO) is one of the most important fault characteristic gases dissolved in power transformer oil. With the advantages of high sensitivity and accuracy, long-term stability, and short detection time, photoacoustic spectroscopy (PAS) has been proven to be one promising sensing technology for trace gas recognition. In this investigation, a tunable PAS experimental system based on a distributed-feedback (DFB) diode laser was proposed for recognizing dissolved CO in transformer oil. The molecular spectral line of CO gas detection was selected at 1.567 μm in the whole experiment. Relationships between the photoacoustic (PA) signal and gas pressure, temperature, laser power, and CO gas concentration were measured and discussed in detail, respectively. Finally, based on the least square regression theory, a novel quantitative identification method for CO gas detection with the PAS experimental system was proposed. And a comparative research about the gas detection performances performed by the PAS system and gas chromatography (GC) measurement was presented. All results lay a solid foundation for exploring a portable and tunable CO gas PAS detection device for practical application in future.

Acetylene C2H2 gas is one of the most important fault characteristic hydrocarbon gases dissolved in oil immersed power transformer oil. This paper reports the successful preparation and characterization of samarium oxide Sm2O3 decorated tin oxide SnO2 based sensors with hierarchical rod structure for C2H2 gas detection. Pure and Sm2O3 decorated SnO2 sensing structures were synthesized by a facile hydrothermal method and characterized by XRD, FESEM, TEM, EDS, and XPS measurements, respectively. Planar chemical gas sensors with the synthesis samples were fabricated, and their sensing performances to C2H2 gas were systematically performed and automatically recorded by a CGS-1 TP intelligent gas sensing analysis system. The optimum operating temperature of the Sm2O3 decorated SnO2 based sensor towards 50 μL/L of C2H2 is 260°C, and its corresponding response value is 38.12, which is 6 times larger than the pure one. Its response time is about 8–10 s and 10–13 s for recovery time. Meanwhile good stability and reproducibility of the decorated sensor to C2H2 gas are also obtained. Furthermore, the proposed sensor exhibits excellent C2H2 selectivity among some potential interface gases, like H2 and CO gas. All sensing results indicate the sensor fabricated with oxide Sm2O3 decorated SnO2 nanorods might be a promising candidate for C2H2 detection in practice.