Because of the interesting and multifunctional properties,recently,ZnO nanostructures are considered as excellent material for fabrication of highly sensitive and selective gas sensors.Thus,ZnO nanomaterials are widel...Because of the interesting and multifunctional properties,recently,ZnO nanostructures are considered as excellent material for fabrication of highly sensitive and selective gas sensors.Thus,ZnO nanomaterials are widely used to fabricate efficient gas sensors for the detection of various hazardous and toxic gases.The presented review article is focusing on the recent developments of NO2gas sensors based on ZnO nanomaterials.The review presents the general introduction of some metal oxide nanomaterials for gas sensing application and finally focusing on the structure of ZnO and its gas sensing mechanisms.Basic gas sensing characteristics such as gas response,response time,recovery time,selectivity,detection limit,stability and recyclability,etc are also discussed in this article.Further,the utilization of various ZnO nanomaterials such as nanorods,nanowires,nano-micro flowers,quantum dots,thin films and nanosheets,etc for the fabrication of NO2gas sensors are also presented.Moreover,various factors such as NO2concentrations,annealing temperature,ZnO morphologies and particle sizes,relative humidity,operating temperatures which are affecting the NO2gas sensing properties are discussed in this review.Finally,the review article is concluded and future directions are presented.展开更多
A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure.Specifically,a digital finite impulse response(FIR)filter is designed to denoise and f...A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure.Specifically,a digital finite impulse response(FIR)filter is designed to denoise and filter the signal,and the time-frequency domain evolution of induced charge signals is analyzed during coal failure experiments.The quantitative relationships between the induced electric charge and stress-strain energy,and ultimately,between induced electric charge and coal deformation/failure,are revealed.Ultimately,the electric charge sensor exhibits high signal collection frequency and high sensitivity,and the FIR low-pass filter constructed in MATLAB effectively denoises and filters induced charge signals.The main frequency range of the white noise is 50-500 Hz,and the main frequency of the charge signal induced by coal deformation and failure is concentrated in the range of 0-50 Hz.The optimal distances for monitoring cubic and cylindrical raw coal samples using this sensor are 9 mm and 11 mm,respectively.Notably,strain energy is released faster when it can dissipate more readily,and induced charge pulses become denser when more intense signals produce large fluctuations.A method is proposed to identify coal deformation and failure based on changes in the induced electric charge.This study provides a new means of monitoring the early warning signs of dynamic coal mine disasters.Based on our experimental results and conclusions,a new method is proposed to identify coal deformation and failure based on changes in the induced electric charge.The precursor to the moment of coal failure can be identified by monitoring the amplitude of the induced charge,the dynamic trend of fluctuation,and the cumulative number of induced electric charge pulses during the process of coal deformation.展开更多
A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensor...A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.展开更多
基金supported by NSTIP strategic technologies programs,number(12-NAN2551-02)in the Kingdom of Saudi Arabia
文摘Because of the interesting and multifunctional properties,recently,ZnO nanostructures are considered as excellent material for fabrication of highly sensitive and selective gas sensors.Thus,ZnO nanomaterials are widely used to fabricate efficient gas sensors for the detection of various hazardous and toxic gases.The presented review article is focusing on the recent developments of NO2gas sensors based on ZnO nanomaterials.The review presents the general introduction of some metal oxide nanomaterials for gas sensing application and finally focusing on the structure of ZnO and its gas sensing mechanisms.Basic gas sensing characteristics such as gas response,response time,recovery time,selectivity,detection limit,stability and recyclability,etc are also discussed in this article.Further,the utilization of various ZnO nanomaterials such as nanorods,nanowires,nano-micro flowers,quantum dots,thin films and nanosheets,etc for the fabrication of NO2gas sensors are also presented.Moreover,various factors such as NO2concentrations,annealing temperature,ZnO morphologies and particle sizes,relative humidity,operating temperatures which are affecting the NO2gas sensing properties are discussed in this review.Finally,the review article is concluded and future directions are presented.
基金supported by the National Key Research and Development Project of the National Natural Science Foundation(Grant No.2022YFC3004605)the National Natural Science Foundation of China Youth Science Fund(Grant No.52104087).
文摘A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure.Specifically,a digital finite impulse response(FIR)filter is designed to denoise and filter the signal,and the time-frequency domain evolution of induced charge signals is analyzed during coal failure experiments.The quantitative relationships between the induced electric charge and stress-strain energy,and ultimately,between induced electric charge and coal deformation/failure,are revealed.Ultimately,the electric charge sensor exhibits high signal collection frequency and high sensitivity,and the FIR low-pass filter constructed in MATLAB effectively denoises and filters induced charge signals.The main frequency range of the white noise is 50-500 Hz,and the main frequency of the charge signal induced by coal deformation and failure is concentrated in the range of 0-50 Hz.The optimal distances for monitoring cubic and cylindrical raw coal samples using this sensor are 9 mm and 11 mm,respectively.Notably,strain energy is released faster when it can dissipate more readily,and induced charge pulses become denser when more intense signals produce large fluctuations.A method is proposed to identify coal deformation and failure based on changes in the induced electric charge.This study provides a new means of monitoring the early warning signs of dynamic coal mine disasters.Based on our experimental results and conclusions,a new method is proposed to identify coal deformation and failure based on changes in the induced electric charge.The precursor to the moment of coal failure can be identified by monitoring the amplitude of the induced charge,the dynamic trend of fluctuation,and the cumulative number of induced electric charge pulses during the process of coal deformation.
文摘A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.
