Search Results (1,273)

Online monitoring technology for transformers is a crucial safeguard for power supply, and diagnosing dissolved gases in 10 kV distribution transformer oil is considered an effective criterion for transformer fault detection. Using density functional theory, this paper simulated the adsorption process of five dissolved gases in a 10 kV distribution transformer on Os-modified C₃N nanosheets, and by calculating the band structure, differential charge density, density of states, and work function, the related sensing and adsorption mechanisms were revealed. The results indicate that Os modification significantly enhances the gas-sensing response of C₃N nanosheets, particularly for capturing C₂H₂ and CO, which is primarily attributed to the d-orbital electrons of the doped metal. The adsorption capability of Os-modified C₃N nanosheets of dissolved gases follows the order C₂H₂ > CO > H₂ > CO₂ > CH₄, with the adsorption type being physico-chemical adsorption, and these findings provide a theoretical foundation for developing high-sensitivity gas sensors for detecting dissolved gases in a 10 kV distribution transformer. Full article

Gas station canopy grid structures develop local damage during service life, necessitating regular inspection and maintenance to prevent structural collapse. However, conventional field inspection remains inefficient and highly dependent on manual operation. This paper proposes a time domain response sensitivity methodology for damage assessment of structural members in gas station canopy grid structures. The proposed methodology advances time-domain sensitivity analysis to handle spatially complex grid structures with dense spectral characteristics, while proposing a calculation method for implementing intelligent sensing technology in field inspections that enables automated damage localization in practical canopy structures. Through analyzing time domain response sensitivity matrix, an optimal sensor placement method for spatial grid structures is presented. A double-layer spatial grid structure model is constructed to validate the time domain response sensitivity damage identification method and the optimal sensor placement method based on sensitivity analysis. The results show that the time domain response sensitivity damage identification method identifies the member damage in gas station canopy grid structural numerical model with satisfactory accuracy and efficiency, the optimal sensor placement methodology is suitable for damage identification of structural members. Full article

Acute kidney injury (AKI) is a leading cause of distant organ dysfunction among critically ill patients. Mitochondrial dysfunction is considered a key factor driving the damage after renal ischemia–reperfusion (IR) injury. Damaged mitochondria release mitochondrial damage-associated molecular patterns (mtDAMPs) into the cytosol, which initiate a systemic inflammatory response. To better understand the underlying mechanism, mice were challenged with 30 min of bilateral renal ischemia followed by 24 h of reperfusion. The cytokine profiling in mouse lung tissues revealed that TREM-1 was significantly increased. Western Blot (WB) analysis demonstrated that the cGAS and STING pathway was increased in AKI mice. Transmission electron microscopy (TEM) images indicated that the mtDAMPs were released from damaged kidney mitochondria. Injection of mtDAMPs into mice induced an inflammatory response in the lungs similar to that induced by AKI. Mouse macrophages and lung epithelial cells were utilized to verify if inhibition of the TREM-1 and cGAS-STING pathways reduces mtDAMP-induced lung injury. Electric Cell-substrate Impedance Sensing (ECIS) results demonstrated that inhibiting the TREM-1 and cGAS-STING pathways significantly increased cell proliferation and migration while reducing mtDAMP-induced cytotoxicity. In conclusion, our findings suggest that targeting TREM-1 and cGAS-STING has the potential to attenuate acute lung injury in IR-AKI. Full article

This study presents a comprehensive first-principles investigation into the gas adsorption and sensing characteristics of Pd-doped MoSe₂, WSe₂, and MoSe₂-WSe₂ systems for dissolved gas analysis applications in oil-filled transformers. Through theoretical simulations, we first establish and characterize three distinct Pd-doped systems, examining their structural stability, electronic properties, and gas interaction mechanisms with key typical gases (H₂, C₂H₂, and C₂H₄). Our analysis reveals that the Pd@MoSe₂-WSe₂ heterojunction exhibits exceptional sensing performance, with calculated response values of −77.67% (H₂), −95.98% (C₂H₂), and −96.88% (C₂H₄)—significantly surpassing the capabilities of both Pd-MoSe₂ and Pd-WSe₂ monolayers. The observed response hierarchy (C₂H₄ > C₂H₂ > H₂) correlates directly with the degree of adsorption energy, charge transfer, and bandgap modification induced by gas adsorption. Finally, the reason for such enhancements are systemically analyzed. The findings not only position Pd@MoSe₂-WSe₂ as an outstanding candidate for condition evaluation in oil-filled transformers but also establish a structure–property relationship that uncovers the feasibility of a strategic heterojunction design to enhance the adsorption and sensing performances for typical gas species. Full article

This work comparably investigates the gas sensing potential of noble metal (Pd and Ru)-doped GeS₂ monolayers upon three C₄F₇N decomposed species (FCN, CF₃CN, and C₂F₄) using the first-principles theory, for operation status evaluation in C₄F₇N-insulated devices. The Pd- and Ru-doping effects on the pristine GeS₂ monolayer are analyzed, followed by the adsorption mechanism and sensing performance of two doped monolayers. Our results demonstrate that while Ru doping induces stronger surface interactions with the GeS₂ substrate and consequently exhibits superior adsorption strengths upon the three gases, the Pd-doped monolayer shows remarkable advantages in charge transfer capability that leads to exceptional room-temperature sensitivity responses of −99.6% (FCN), −95.0% (CF₃CN), and −88.0% (C₂F₄), thus significantly outperforming the Ru-doped system. Combined with the instantaneous recovery for gas desorption, the Pd-GeS₂ monolayer holds significance as an ideal room-temperature sensor to monitor the operation status of C₄F₇N-insulated devices in power systems. This research provides promising insights into the application of GeS₂-based materials for gas sensing in power systems and emphasizes the importance of dopant selection in designing high-performance gas sensing materials, especially for developing advanced electrical equipment monitoring technologies. Full article

In this paper, we propose and experimentally demonstrate a dual-parameter fiber optic sensor, which combines a Fabry–Perot interferometer (FPI) and a Mach–Zehnder interferometer (MZI) for simultaneous pressure and temperature sensing. The Fabry–Perot (FP) cavity is formed by sandwiching a capillary fiber between a single-mode fiber and a dual-core fiber (DCF). A fluid channel is very close to the central core of the DCF. By precisely drilling micro-air chambers in the annular cladding of a capillary fiber (CF) using a femtosecond laser, external air pressure can directly affect the capillary fiber and induce changes in the refractive index of the air in the CF. The F-P cavity achieves a pressure sensitivity of 3.67 nm/MPa with a temperature cross-sensitivity of 2.82 pm/°C. The MZI is constructed using a dual-core fiber filled with silicone oil in the fluidic channel, which enhances temperature sensitivity through the thermo-optic effect. The MZI sensor exhibits a nonlinear temperature response with an average sensitivity of 103.43 pm/°C. The corresponding pressure cross-sensitivity is about –0.11 nm/MPa. Due to very low cross-sensitivity, simultaneous measurement of temperature and gas pressure is feasible. In addition, we implement a variant by replacing silicone oil with a UV-curable adhesive, which delivers a comparable FP-based pressure sensitivity of ~3.93 nm/MPa while yielding an MZI-based temperature sensitivity of 71.7 pm/°C and potentially improved long-term stability. Full article

Volatile organic compound (VOC) monitoring is crucial for environmental safety and health, but conventional gas sensors often suffer from poor selectivity or lack spatial information. Here, we report a localized surface plasmon resonance (LSPR) gas sensor based on Au nano-urchins coated with a zeolitic imidazolate framework (ZIF-8) for both the quantitative detection and visualization of VOCs. Substrates were fabricated by immobilizing Au nano-urchins (~90 nm) on 3-aminopropyltriethoxysilane-modified glass and subsequently growing ZIF-8 crystals (~250 nm) for different durations. Scanning electron microscopy and optical analysis revealed that 90 min of ZIF-8 growth provided the optimal coverage and strongest plasmonic response. Using a spectrometer-based LSPR system, the optimized substrate exhibited clear, concentration-dependent responses to three representative VOCs, 2-pentanone, acetic acid, and ethyl acetate, over nine concentrations, with detection limits of 12.7, 14.5, and 36.3 ppm, respectively. Furthermore, a camera-based LSPR visualization platform enabled real-time imaging of gas plumes and evaporation-driven diffusion, with differential pseudo-color mapping providing intuitive spatial distributions and concentration dependence. These results demonstrate that ZIF-8-modified Au nano-urchin substrates enable sensitive and reproducible VOC detection and, importantly, transform plasmonic sensing into a visual modality, offering new opportunities for integrated LSPR–surface-enhanced Raman scattering dual-mode gas sensing in the future. Full article

Laboratories are complex and dynamic environments where diverse hazards—including toxic gas leakage, volatile solvent combustion, and unexpected fire ignition—pose serious threats to personnel safety and property. Traditional monitoring systems relying on single-type sensors or manual inspections often fail to provide timely warnings or comprehensive hazard perception, resulting in delayed response and potential escalation of incidents. To address these limitations, this study proposes a multi-node laboratory safety monitoring and early warning system integrating multi-source sensing, heterogeneous communication, and cloud–edge collaboration. The system employs a LoRa-based star-topology network to connect distributed sensing and actuation nodes, ensuring long-range, low-power communication. A Raspberry Pi-based module performs real-time facial recognition for intelligent access control, while an OpenMV module conducts lightweight flame detection using color-space blob analysis for early fire identification. These edge-intelligent components are optimized for embedded operation under resource constraints. The cloud–edge–app collaborative architecture supports real-time data visualization, remote control, and adaptive threshold configuration, forming a closed-loop safety management cycle from perception to decision and execution. Experimental results show that the facial recognition module achieves 95.2% accuracy at the optimal threshold, and the flame detection algorithm attains the best balance of precision, recall, and F1-score at an area threshold of around 60. The LoRa network maintains stable communication up to 0.8 km, and the system’s emergency actuation latency ranges from 0.3 s to 5.5 s, meeting real-time safety requirements. Overall, the proposed system significantly enhances early fire warning, multi-source environmental monitoring, and rapid hazard response, demonstrating strong applicability and scalability in modern laboratory safety management. Full article

Zinc oxide (ZnO) nanomaterials have emerged as promising candidates for gas sensing applications due to their high sensitivity, fast response–recovery cycles, thermal and chemical stability, and low fabrication cost. However, the performance of pristine ZnO remains limited by high operating temperatures, poor selectivity, and suboptimal detection at low gas concentrations. To address these limitations, significant research efforts have focused on dopant incorporation and polymer hybridization. This review summarizes recent advances in dopant engineering using elements such as Al, Ga, Mg, In, Sn, and transition metals (Co, Ni, Cu), which modulate ZnO’s crystal structure, defect density, carrier concentration, and surface activity—resulting in enhanced gas adsorption and electron transport. Furthermore, ZnO–polymer nanocomposites (e.g., with polyaniline, polypyrrole, PEG, and chitosan) exhibit improved flexibility, surface functionality, and room-temperature responsiveness due to the presence of active functional groups and tunable porosity. The synergistic combination of dopants and polymers facilitates enhanced charge transfer, increased surface area, and stronger gas–molecule interactions. Where applicable, sol–gel-based studies are explicitly highlighted and contrasted with non-sol–gel routes to show how synthesis controls defect chemistry, morphology, and sensing metrics. This review provides a comprehensive understanding of the structure–function relationships in doped ZnO and ZnO–polymer hybrids and offers guidelines for the rational design of next-generation, low-power, and selective gas sensors for environmental and industrial applications. Full article

In this study, two types of gas sensors—silicone-based interdigital electrode and silicon micropillar sensors based on rGO and rGO/SnO₂—were fabricated. Their gas-sensing performance was investigated at room temperature. First, interdigital electrodes of different channel widths were fabricated to investigate the impact of the channel width parameter. Subsequently, the rGO/SnO₂ doping ratio in the composite material was varied to identify the optimal composition for gas sensitivity. Additionally, triangular and square-arrayed silicon micropillar substrates were fabricated via photolithography and inductively coupled plasma etching. The rGO/SnO₂-based gas sensor on a silicon micropillar substrate exhibited an ultra-high specific surface area. The triangular micropillar arrangement of rGO/SnO₂-160 demonstrates the best performance, showing approximately 14% higher response and a 106 s reduction in response time compared with interdigital electrode sensors spray-coated with the same concentration of rGO/SnO₂ when tested at room temperature under 250 ppm NO₂. The optimized sensor achieves a detection limit as low as 5 ppm and maintains high responsiveness, even in conditions of 60% relative humidity (RH). Additionally, the repeatability, selectivity, and stability of the sensor were evaluated. Finally, structural and morphological characterization was conducted using XRD, SEM, TEM, and Raman spectroscopy, which confirmed the successful modification of rGO with SnO₂. Full article

This paper presents a thermal gas flow sensing system, from surface acoustic wave (SAW) temperature sensor to oscillation circuit and multi-module miniaturization integration. A single-port GaN/Si SAW resonator with single resonant mode and excellent characteristics was fabricated. Combined with an in-house-developed SiGe HBT, a temperature-sensitive high-frequency oscillator was constructed. Under constant temperature control, system-level flow measurement was achieved through dual-oscillation configuration and modular integration. The fabricated SAW device shows a temperature coefficient of frequency (TCF) −28.29 ppm/K and temperature linearity 0.998. The oscillator operates at 1.91 GHz with phase noise of −97.72/−118.62 dBc/Hz at 10/100 kHz offsets. The system demonstrates excellent dynamic response and repeatability, directly measuring 0–50 sccm flows. For higher flows (>50 sccm), a shunt technique extends the test range based on the 0–10 sccm linear region, where response time is <1 s with error <0.9%. Non-contact operation ensures high stability and long lifespan. The sensor shows outstanding performance and broad application prospects in flow measurement. Full article

As industrial waste gas, nitrogen dioxide (NO₂) is a serious hazard to air pollution and human health, and there is a pressing demand for developing high-performance NO₂ gas sensors. Tin disulfide (SnS₂), a representative two-dimensional metal sulfide characterized by a significant specific surface area, a suitable electron band gap, and an easily tunable layered structure, shows a broad application prospect in gas sensing applications. Nevertheless, SnS₂-based gas sensors suffer from poor sensitivity, which seriously hinders their application in room temperature gas sensing. In this study, Ag/SnS₂ heterojunction nanomaterials were synthesized by an in situ reduction approach. The findings reveals that the gas-sensitive response of the Ag/SnS₂ nanocomposites at room temperature under visible light irradiation can achieve 10.5 to 1 ppm NO₂, with a detection limit as low as 200 ppb, which realizes the room-temperature detection of Sub-ppm NO₂. Meanwhile, the sensor exhibits good selectivity, reproducibility (cyclic stability > 95%). The improved gas sensitivity of the Ag/SnS₂ sensor can be due to the synergistic effect of the carrier separation at the Ag/SnS₂ Schottky junction and the localized surface plasmon resonance (LSPR) of Ag nanoparticles. The LSPR effect significantly enhances light absorption and surface-active site density, facilitating trace NO₂ detection at room temperature. This study provides the foundation for the subsequent development of room temperature layered metal sulfide gas sensors. Full article

Fiber-optic sensing systems based on a forward transmission interferometric structure can achieve high sensitivity and a wide frequency response over long distances. However, there are still shortcomings in its ability to position multi-point vibrations and detect low-frequency vibrations, which limits its usefulness. To address these challenges, we study the viability of merging long-range forward-transmission distributed vibration sensing (FTDVS) with high spatial resolution optical frequency-domain reflectometry (OFDR), forming the first reported hybrid distributed sensing method between these two methods. The probe light source is shared between the two sub-systems, which utilizes stable linear optical frequency sweeping facilitated by high-order sideband injection locking. As a result, this is a new approach for the FTDVS method, which conventionally uses fixed-frequency continuous light. The method of nearest neighbor signal replacement (NSR) is proposed to address the issue of discontinuity in phase demodulation under periodic external modulation. The experimental results demonstrate that the hybrid system can determine the position of vibration signals between 0 and 900 Hz within a sensing distance of 21 km. When the sensing distance is extended to 71 km, the FTDVS module can still function adequately for high-frequency vibration signals. This hybrid architecture offers a fresh approach to simultaneously achieving long-distance sensing and wide frequency response, making it suitable for the combined measurement of dynamic (e.g., gas leakage, pipeline excavation warning) and quasi-static (e.g., pipeline displacement) events in long-distance applications. Full article

The increasing demand for reliable, sensitive, and cost-effective gas sensors drives ongoing research in this field. Ideal gas sensors must demonstrate high sensitivity and selectivity, stability, rapid response and recovery times, energy efficiency, and affordability. One-dimensional (1D) metal oxide semiconductors (MOSs) are prominent candidates due to their excellent sensing properties and straightforward fabrication processes. The sensing efficacy of 1D MOSs is heavily dependent on their surface area and porosity, which influence gas interaction and detection efficiency. Polymeric templates serve as effective tools for enhancing these properties by enabling the creation of uniform, porous nanostructures with high surface area, thereby improving gas adsorption, sensitivity, and dynamic response characteristics. This review systematically examines the role of polymeric templates in the construction of 1D MOSs for gas sensing applications. It discusses critical factors influencing polymer template selection and how this choice affects key microstructural parameters, such as grain size, pore distribution, and defect density, essential to sensor performance. The recent literature highlights the mechanisms through which polymer templates facilitate the fine-tuning of nanostructures. Future research directions include exploring novel polymer architectures, developing scalable synthesis methods, and integrating these sensors with emerging technologies. Full article

The prompt and reliable detection of NH₃ leakage at room temperature (RT) is considered important for safety assurance and sustainable production. Although chemiresistive NH₃ sensors feature low cost and structural simplicity, their practical application is hindered by high operating temperatures and inadequate selectivity. Metal–organic frameworks (MOFs) and their derivatives offer a promising approach to address these limitations. In this work, Ce-BDC precursors with tunable particle sizes and crystallinity were synthesized by adjusting the raw material concentration. Controlled pyrolysis yielded a series of CeO₂-C-X (X = 0.5, 1, 1.5, 2) materials with nanosized particles. Among them, the CeO₂-C-1 sensor delivered a high response of 82% toward NH₃ under 40% relative humidity at RT. Moreover, it possessed excellent selectivity, repeatability, and rapid response-recovery behavior compared with the other samples. CeO₂-C-1 also remained stable under varying oxygen and humidity conditions, demonstrating high applicability. The superior sensing properties may be attributed to its high specific surface area and optimized mesoporous structure, which facilitated efficient gas adsorption and reaction. These findings demonstrated that precise control of MOF precursors and the structure in CeO₂ nanomaterials was critical for achieving high-performance gas sensing and established Ce-MOF-derived CeO₂ as a promising sensing material for NH₃ detection at RT. Full article