Theoretical study of SF6 decomposition products adsorption on metal oxide cluster-modified single-layer graphene

Advances in 2D Materials Based Gas Sensors for Industrial Machine Olfactory Applications

The escalating development and improvement of gas sensing ability in industrial equipment, or "machine olfactory", propels the evolution of gas sensors toward enhanced sensitivity, selectivity, stability, power efficiency, cost-effectiveness, and longevity. Two-dimensional (2D) materials, distinguished by their atomic-thin profile, expansive specific surface area, remarkable mechanical strength, and surface tunability, hold significant potential for addressing the intricate challenges in gas sensing. However, a comprehensive review of 2D materials-based gas sensors for specific industrial applications is absent. This review delves into the recent advances in this field and highlights the potential applications in industrial machine olfaction. The main content encompasses industrial scenario characteristics, fundamental classification, enhancement methods, underlying mechanisms, and diverse gas sensing applications. Additionally, the challenges associated with transitioning 2D material gas sensors from laboratory development to industrialization and commercialization are addressed, and future-looking viewpoints on the evolution of next-generation intelligent gas sensory systems in the industrial sector are prospected.

Real-Time Monitoring of Air Discharge in a Switchgear by an Intelligent NO2 Sensor Module

An air-insulated power equipment adopts air as the insulating medium and is widely implemented in power systems. When discharge faults occur, the air produces decomposition products represented by NO2. The efficient NO2 sensor enables the identification of electrical equipment faults. However, single-sensor-dependent NO2 detection is vulnerable to interfering gases. Implementing the sensor array could reduce the interference and improve detection efficiency. In the field of NO2 detection, In2O3 sensors have exhibited tremendous advantages. In our work, four composites based on In2O3 are integrated into sensor arrays, which could detect 250 ppb of NO2 and exhibit excellent selectivity when simultaneously exposed to CO. To further reduce the impact of humidity on gas-sensing performance, a convolutional neural network and a long short-term memory model equipped with an attention mechanism are proposed to evaluate NO2 concentration within 1 ppm, and the detection error is 63.69 ppb. In addition, the NO2 concentration estimation platform based on a microgas sensor is established to detect air discharge faults. The average concentration of NO2 generated by 10 consecutive discharge faults at 15 kV is 726.58 ppb, which indicates severe discharge in the switchgear. Our NO2 estimation method has great potential for large-scale deployment in low- and medium-voltage switchgears.

Ag-Doped MoSe2/ZnO Heterojunctions: A Highly Responsive Gas-Sensitive Material for Selective Detection of NO Based on DFT Study

In this work, the adsorption and sensing behavior of Ag-doped MoSe2/ZnO heterojunctions for H2, CH4, CO2, NO, CO, and C2H4 have been studied based on density functional theory (DFT). In gas adsorption analysis, the adsorption energy, adsorption distance, transfer charge, total electron density, density of states (DOS), energy band structure, frontier molecular orbital, and work function (WF) of each gas has been calculated. Furthermore, the reusability and stability of the Ag-doped MoSe2/ZnO heterojunctions have also been studied. The results showed that Ag-doped MoSe2/ZnO heterojunctions have great potential to be a candidate of highly selective and responsive gas sensors for NO detection with excellent reusability and stability.

Adsorption Properties of Ptn (n = 1-3) Cluster-Doped SnS2 and MoTe2 toward Vehicle Emissions: CO, CO2, and NO

The interaction mechanism between CO, CO2, and NO gas molecules and Ptn-SnS2 (n = 1-3) and Ptn-MoTe2 (n = 1-3) is analyzed based on density functional theory calculations. For Pt2-SnS2, the structure of Pt2-SnS2 is deformed during CO2 adsorption. For Pt3-SnS2, its structure is also significantly deformed when the gas is adsorbed. Pt2-SnS2 is not suitable for the detection and adsorption of CO2 gas, while Pt3-SnS2 is not suitable for the detection and adsorption of these three gases. According to the density of states and molecular orbital analysis, the conductivity of the adsorption system of Pt-SnS2 remains almost unchanged after the adsorption of CO, so Pt-SnS2 is not suitable for the detection of CO gases. The adsorption of gases on intrinsic MoTe2 is a weakly interacting physical adsorption. Doping with one to three Pt atoms all resulted in different degrees of enhancement of the adsorption capacity of the substrates for these three target gases. However, for Pt2-MoTe2 and Pt3-MoTe2, the structure of these two materials undergoes significant deformation upon NO adsorption. In addition, the interaction between Pt3-MoTe2 and CO2 is weak, and the conductivity of this system is almost unaffected by CO2 adsorption. In addition, all other constructions are suitable for the detection of the corresponding gases. This paper provides a theoretical basis for the development of gas sensors for the detection of automotive and industrial emission gases.

Theoretical Study on Adsorption Behavior of SF6 Decomposition Components on Mg-MOF-74

SF₆ gas is an arc extinguishing medium that is widely used in gas insulated switchgear (GIS). When insulation failure occurs in GIS, it leads to the decomposition of SF₆ in partial discharge (PD) and other environments. The detection of the main decomposition components of SF₆ is an effective method to diagnose the type and degree of discharge fault. In this paper, Mg-MOF-74 is proposed as a gas sensing nanomaterial for detecting the main decomposition components of SF₆. The adsorption of SF₆, CF₄, CS₂, H₂S, SO₂, SO₂F₂ and SOF₂ on Mg-MOF-74 was calculated by Gaussian16 simulation software based on density functional theory. The analysis includes parameters of the adsorption process such as binding energy, charge transfer, and adsorption distance, as well as the change in bond length, bond angle, density of states, and frontier orbital of the gas molecules. The results show that Mg-MOF-74 has different degrees of adsorption for seven gases, and chemical adsorption will lead to changes in the conductivity of the system; therefore, it can be used as a gas sensing material for the preparation of SF6 decomposition component gas sensors.

TiO2 Gas Sensors Combining Experimental and DFT Calculations: A Review

Gas sensors play an irreplaceable role in industry and life. Different types of gas sensors, including metal-oxide sensors, are developed for different scenarios. Titanium dioxide is widely used in dyes, photocatalysis, and other fields by virtue of its nontoxic and nonhazardous properties, and excellent performance. Additionally, researchers are continuously exploring applications in other fields, such as gas sensors and batteries. The preparation methods include deposition, magnetron sputtering, and electrostatic spinning. As researchers continue to study sensors with the help of modern computers, microcosm simulations have been implemented, opening up new possibilities for research. The combination of simulation and calculation will help us to better grasp the reaction mechanisms, improve the design of gas sensor materials, and better respond to different gas environments. In this paper, the experimental and computational aspects of TiO2 are reviewed, and the future research directions are described.