The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant envi...The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant environmental impacts,electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission(NZE)target by 2050.This study aims to utilize historical electricity load data for the period 2013–2024,as well as data on external factors affecting electricity consumption,to forecast electricity load in Timor-Leste in the next 10 years(2025–2035).The forecasting results are expected to support efforts in energy distribution efficiency,reduce operational costs,and inform decisions related to the sustainable energy transition.The method used in this study consists of two main approaches:the causality method,represented by the econometric Principal Component Analysis(PCA)model,which involves external factors in the data processing process,and the time series method,utilizing the LSTM,XGBoost,and hybrid(LSTM+XGBoost)models.In the time series method,data processing is combined with two approaches:the sliding window and the rolling recursive forecast.The performance of each model is evaluated using the Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).The model with the lowest MAPE(<10%)is considered the best-performing model,indicating the highest accuracy.Additionally,a Monte Carlo simulation with 50,000 iterations was used to process the data and measure the prediction uncertainty,as well as test the calibration of the electricity load projection data.The results showed that the hybrid model(LSTM+XGBoost)with a rolling forecast recursive approach is the best-performing model in predicting electricity load in Timor-Leste.This model yields an RMSE of 75.76 MW,an MAE of 55.76 MW,and an MAPE of 5.27%,indicating a high level of accuracy.In addition,the model is also indicated as one that fits the characteristics of electricity load in Timor-Leste,as it produces the lowest percentage of forecasting error in predicting electricity load.The integration of the best model with Monte Carlo Simulation,which yields a p-value of 0.565,suggests that the results of electricity load projections for the period 2025–2035 are well-calibrated,reliable,accurate,and unbiased.展开更多
To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)...To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.展开更多
As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance,the classification and identification of infrared temperature measurement images have become crucial ...As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance,the classification and identification of infrared temperature measurement images have become crucial in effective intelligent fault diagnosis of various electrical equipment.In response to the increasing demand for sufficient feature fusion in current real-time detection and low detection accuracy in existing networks for Substation fault diagnosis,we introduce an innovative method known as Gather and Distribution Mechanism-You Only Look Once(GD-YOLO).Firstly,a partial convolution group is designed based on different convolution kernels.We combine the partial convolution group with deep convolution to propose a new Grouped Channel-wise Spatial Convolution(GCSConv)that compensates for the information loss caused by spatial channel convolution.Secondly,the Gather and Distribute Mechanism,which addresses the fusion problem of different dimensional features,has been implemented by aligning and sharing information through aggregation and distribution mechanisms.Thirdly,considering the limitations in current bounding box regression and the imbalance between complex and simple samples,Maximum Possible Distance Intersection over Union(MPDIoU)and Adaptive SlideLoss is incorporated into the loss function,allowing samples near the Intersection over Union(IoU)to receive more attention through the dynamic variation of the mean Intersection over Union.The GD-YOLO algorithm can surpass YOLOv5,YOLOv7,and YOLOv8 in infrared image detection for electrical equipment,achieving a mean Average Precision(mAP)of 88.9%,with accuracy improvements of 3.7%,4.3%,and 3.1%,respectively.Additionally,the model delivers a frame rate of 48 FPS,which aligns with the precision and velocity criteria necessary for the detection of infrared images in power equipment.展开更多
In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results i...In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.展开更多
Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic effici...Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.展开更多
Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a c...Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.展开更多
Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energ...Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.展开更多
Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-syn...Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-synchrosqueezing transform(TMssT)was proposed to capture these transient impulses for fault diagnosis.However,the TMSST,which is based on the short-time Fourier transform(STFT),suffers from unclear high-frequency re-presentations owing to the fixed sliding window used in the STFT.To address this limitation,the current study combined TMSST with the S-transform and a local maximum method to enhance the time-frequency representation for improved signal analysis.Furthermore,an extractive reconstruction algorithm that binds the maximum value of the spectral envelope is proposed for spectral decomposition.To validate the proposed technique,a simulated noise-added signal and four experimental bearing defect datasets were used.The results demonstrate that the proposed technique can effectively and accurately extract fault features from bearing signals regardless of whether the bearings operate under constant or varying speed conditions.This study offers a novel and efficient approach for fault diagnosis in mechanical systems with complex dynamic behaviors.展开更多
To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon...To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon capture and storage(CCS),hydrogen fuel cell(HFC),and combined heat and power(CHP).The P2G process is refined into a two-stage structure,and HFC is introduced to enhance hydrogen utilization.Together with CCS and CHP,these devices form a multi-energy conversion system coupling electricity,heat,cooling,and gas.A laddertype carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.To evaluate the resilience of the proposed low-carbon scheduling strategy involving multiple energy units under the variability of renewable energy,a two-level robust optimization framework is developed.This model captures the most adverse scenarios of wind and solar generation.The dispatch strategy is validated against these extreme conditions to demonstrate its flexibility and effectiveness.The problem is solved using the GUROBI optimization tool.Results from simulations indicate that themodel increases renewable energy integration by 39.1%,and achieves reductions of 15.96%in carbon emissions and 16.29%in operational expenditures.The results demonstrate that the strategy ensures both economic efficiency and environmental performance under uncertain conditions.Compared with existing studies that separately model two-stage P2G or CCS devices,this paper integrates HFC,CHP,and CCS into a unified dispatchable system,enabling refined hydrogen utilization and flexible carbon circulation.Furthermore,the introduction of a laddertype carbon pricing mechanism,combined with multi-energy storage participation in implicit demand response,creates a dynamic and cost-sensitive dispatch framework.These modeling strategies go beyond conventional linear IES formulations and provide more realistic system representations.The proposed approach not only deepens the coupling among electric,thermal,and gas systems,but also offers a feasible pathway for high-penetration renewable integration in low-carbon energy systems.展开更多
Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and earl...Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.展开更多
Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason...Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason,a SOH estimation method is proposed based on charging data reconstruction combined with image processing.The charging voltage data is used to train the least squares generative adversarial network(LSGAN),which is validated under different levels of missing data.From a visual perspective,the Gram angle field method is applied to convert one-dimensional time series data into image data.This method fully preserves the time series characteristics and nonlinear evolution patterns,which avoids the difficulties and limited expressive power associated with manual feature extraction.At the same time,the Swin Transformer model is introduced to extract global structures and local details from images,enabling better capture of sequence change trends.Combined with the long short-term memory network(LSTM),this enables accurate estimation of battery SOH.Two different types of batteries are used to validate the test.The experimental results show that the proposed method has good estimation accuracy under different training proportions.展开更多
There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior sep...There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior separately.In this paper,a unified tribology-kinematic model is established considering the coupling effect between friction and the ball velocity vector.The friction in ball-groove contact and ball speed are simultaneously measured by a newly developed disc-ball-disc device for studying friction and movement in ball screws.A comprehensive analysis of rubbing interface behavior and ball motion is conducted.The results show that the coupling effect between friction in ball-groove contact and ball motion is quite obvious.The sliding velocity of the ball is much higher with coupling effect than that when ignoring coupling influence,especially at high-speed conditions.The friction in ball-groove contact decreases at first and then shows a dramatic increase with the gradual rise of rotation speed,which is caused by the coupling variation of sliding speed.The studies show that the disc-ball-disc approach is an innovative and valuable method to investigate friction and ball motion in ball screws.展开更多
Effects of alloying elements Ni,Co,Mn,Cr,and H on the stacking fault energy(SFE)ofγ-Fe and its microscopic mechanisms were systematically investigated.Generalized SFE calculations show that individual alloying elemen...Effects of alloying elements Ni,Co,Mn,Cr,and H on the stacking fault energy(SFE)ofγ-Fe and its microscopic mechanisms were systematically investigated.Generalized SFE calculations show that individual alloying elements Ni,Co,and H increase SFE ofγ-Fe,whereas Mn and Cr decrease SFE.The influence of alloying elements on SFE exhibits short-range characteristics.The effect of synergistic interaction of alloying elements and H on SFE was further investigated.Results show that the co-alloying of Ni/Co with H exacerbates the effect of H on the increase in SFE.In contrast,the synergistic effect of Mn/Cr with H tends to inhibit H from the increasing SFE.Finally,the electronic structure analysis elucidated the microscopic mechanism of the change in SFE.Alloying elements modulate SFE by changing the interatomic charge density at the stacking fault plane and the density of states of the stacking fault structure at the Fermi level.The present results add to the knowledge of alloying related influence on the mechanical property and hydrogen embrittlement ofγ-Fe.展开更多
Current experimental techniques still face challenges in clarifying the structural and dynamic properties of helium(He)in liquid lithium(Li).A critical example of this technical hurdle is the formation of He bubbles,w...Current experimental techniques still face challenges in clarifying the structural and dynamic properties of helium(He)in liquid lithium(Li).A critical example of this technical hurdle is the formation of He bubbles,which significantly affects the transport of He within liquid Li—a vital aspect when considering liquid Li as a plasma-facing material in nuclear fusion reactors.We develop a machine-learning-based deep potential(DP)with ab initio accuracy for the Li-He system and perform molecular dynamics simulations at temperatures ranging from 470 K to 1270 K with a wide range of He concentrations.We observe that He atoms exhibit a tendency to aggregate and form clusters and bubbles in liquid Li.Notably,He clusters exhibit a significant increase in size at elevated temperatures and high concentrations of He,accompanied by the phase separation of Li and He atoms.We also observe an anomalous non-linear relationship between the diffusion coefficient of He and temperature,which is attributed to the larger cluster size at higher temperatures.Our study provides a deeper understanding of the behavior of He in liquid Li and further supports the potential application of liquid Li under extreme conditions.展开更多
As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.Ho...As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.展开更多
Metal hydrides with high hydrogen density provide promising hydrogen storage paths for hydrogen transportation.However,the requirement of highly pure H_(2)for re-hydrogenation limits its wide application.Here,amorphou...Metal hydrides with high hydrogen density provide promising hydrogen storage paths for hydrogen transportation.However,the requirement of highly pure H_(2)for re-hydrogenation limits its wide application.Here,amorphous Al_(2)O_(3)shells(10 nm)were deposited on the surface of highly active hydrogen storage material particles(MgH_(2)-ZrTi)by atomic layer deposition to obtain MgH_(2)-ZrTi@Al_(2)O_(3),which have been demonstrated to be air stable with selective adsorption of H_(2)under a hydrogen atmosphere with different impurities(CH_(4),O_(2),N_(2),and CO_(2)).About 4.79 wt% H_(2)was adsorbed by MgH_(2)-ZrTi@10nmAl_(2)O_(3)at 75℃under 10%CH_(4)+90%H_(2)atmosphere within 3 h with no kinetic or density decay after 5 cycles(~100%capacity retention).Furthermore,about 4 wt%of H_(2)was absorbed by MgH_(2)-ZrTi@10nmAl_(2)O_(3)under 0.1%O_(2)+0.4%N_(2)+99.5%H_(2)and 0.1%CO_(2)+0.4%N_(2)+99.5%H_(2)atmospheres at 100℃within 0.5 h,respectively,demonstrating the selective hydrogen absorption of MgH_(2)-ZrTi@10nmAl_(2)O_(3)in both oxygen-containing and carbon dioxide-containing atmospheres hydrogen atmosphere.The absorption and desorption curves of MgH_(2)-ZrTi@10nmAl_(2)O_(3)with and without absorption in pure hydrogen and then in 21%O_(2)+79%N_(2)for 1 h were found to overlap,further confirming the successful shielding effect of Al_(2)O_(3)shells against O_(2)and N_(2).The MgH_(2)-ZrTi@10nmAl_(2)O_(3)has been demonstrated to be air stable and have excellent selective hydrogen absorption performance under the atmosphere with CH_(4),O_(2),N_(2),and CO_(2).展开更多
The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary sate...The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m^(−2) in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.展开更多
Halide perovskites have emerged as promising materials for X-ray detection with exceptional properties and reasonable costs.Among them,heterostructures between 3D perovskites and low-dimensional perovskites attract in...Halide perovskites have emerged as promising materials for X-ray detection with exceptional properties and reasonable costs.Among them,heterostructures between 3D perovskites and low-dimensional perovskites attract intensive studies of their advantages due to low-level ion migration and decent stability.However,there is still a lack of methods to precisely construct heterostructures and a fundamental understanding of their structure-dependent optoelectronic properties.Herein,a gas-phase method was developed to grow 2D perovskites directly on 3D perovskites with nanoscale accuracy.In addition,the larger steric hindrance of organic layers of 2D perovskites was proved to enable slower ion migration,which resulted in reduced trap states and better stability.Based on MAPbBr_(3)single crystals with the(PA)_(2)PbBr_(4)capping layer,the X-ray detector achieved a sensitivity of 22,245μC Gy_(air)^(−1)cm^(−2),a response speed of 240μs,and a dark current drift of 1.17.10^(–4)nA cm^(−1)s^(−1)V^(−1),which were among the highest reported for state-of-the-art perovskite-based X-ray detectors.This study presents a precise synthesis method to construct perovskite-based heterostructures.It also brings an in-depth understanding of the relationship between lattice structures and properties,which are beneficial for advancing high-performance and cost-effective X-ray detectors.展开更多
AgSnO_ 2 electrical contact materials doped with Bi_2O_3,La_2O_3,and TiO_2 were successfully fabricated by the powder metallurgy method under different initial sintering temperatures.The electrical conductivity,densit...AgSnO_ 2 electrical contact materials doped with Bi_2O_3,La_2O_3,and TiO_2 were successfully fabricated by the powder metallurgy method under different initial sintering temperatures.The electrical conductivity,density,hardness,and contact resistance of the Ag Sn O_2/Bi_2O_3,AgSnO_2/La_2O_3,and AgSnO_2/Ti O_2 contact materials were measured and analyzed.The arc-eroded surface morphologies of the doped AgSnO_2 contact materials were investigated by scanning electron microscopy(SEM).The effects of the initial sintering temperature on the physical properties and electrical contact properties of the doped AgSnO_2 contact materials were discussed.The results indicate that the physical properties can be improved and the contact resistance of the AgSnO_2 contact materials can be substantially reduced when the materials are sintered under their optimal initial sintering temperatures.展开更多
A good contact between the pantograph and catenary is critically important for the working reliability of electric trains, while the basic understanding on the electrical contact evolution during the pantograph--caten...A good contact between the pantograph and catenary is critically important for the working reliability of electric trains, while the basic understanding on the electrical contact evolution during the pantograph--catenary system working is still ambiguous so far. In this paper, the evolution of electric contact was studied in respects of the contact resistance, temperature rise, and microstructure variation, based on a home-made pantograph-catenary simulation system. Pure carbon strips and copper alloy contact wires were used, and the experimental electrical current, sliding speed, and normal force were set as 80 A, 30 km/h, and 80 N, respectively. The contact resistance presented a fluctuation without obvious regularity, concentrating in the region of 25 and 50 mf~. Temperature rise of the contact point experienced a fast increase at the first several minutes and finally reached a steady state. The surface damage of carbon trips in microstructure analysis revealed a complicated interaction of the sliding friction, joule heating, and arc erosion.展开更多
文摘The rapid development of technology has led to an ever-increasing demand for electrical energy.In the context of Timor-Leste,which still relies on fossil energy sources with high operational costs and significant environmental impacts,electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission(NZE)target by 2050.This study aims to utilize historical electricity load data for the period 2013–2024,as well as data on external factors affecting electricity consumption,to forecast electricity load in Timor-Leste in the next 10 years(2025–2035).The forecasting results are expected to support efforts in energy distribution efficiency,reduce operational costs,and inform decisions related to the sustainable energy transition.The method used in this study consists of two main approaches:the causality method,represented by the econometric Principal Component Analysis(PCA)model,which involves external factors in the data processing process,and the time series method,utilizing the LSTM,XGBoost,and hybrid(LSTM+XGBoost)models.In the time series method,data processing is combined with two approaches:the sliding window and the rolling recursive forecast.The performance of each model is evaluated using the Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).The model with the lowest MAPE(<10%)is considered the best-performing model,indicating the highest accuracy.Additionally,a Monte Carlo simulation with 50,000 iterations was used to process the data and measure the prediction uncertainty,as well as test the calibration of the electricity load projection data.The results showed that the hybrid model(LSTM+XGBoost)with a rolling forecast recursive approach is the best-performing model in predicting electricity load in Timor-Leste.This model yields an RMSE of 75.76 MW,an MAE of 55.76 MW,and an MAPE of 5.27%,indicating a high level of accuracy.In addition,the model is also indicated as one that fits the characteristics of electricity load in Timor-Leste,as it produces the lowest percentage of forecasting error in predicting electricity load.The integration of the best model with Monte Carlo Simulation,which yields a p-value of 0.565,suggests that the results of electricity load projections for the period 2025–2035 are well-calibrated,reliable,accurate,and unbiased.
基金supported by the National Natural Science Foundation of China(Nos.62063009,52262050)the National Key Research and Development Program during the 14th 5-Year Plan(No.2023YFB4302100)the Major Science and Technology Research and Development Special Project in Jiangxi Province(No.20232ACE01011).
文摘To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.
基金Science and Technology Department of Jilin Province(No.20200403075SF)Education Department of Jilin Province(No.JJKH20240148KJ).
文摘As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance,the classification and identification of infrared temperature measurement images have become crucial in effective intelligent fault diagnosis of various electrical equipment.In response to the increasing demand for sufficient feature fusion in current real-time detection and low detection accuracy in existing networks for Substation fault diagnosis,we introduce an innovative method known as Gather and Distribution Mechanism-You Only Look Once(GD-YOLO).Firstly,a partial convolution group is designed based on different convolution kernels.We combine the partial convolution group with deep convolution to propose a new Grouped Channel-wise Spatial Convolution(GCSConv)that compensates for the information loss caused by spatial channel convolution.Secondly,the Gather and Distribute Mechanism,which addresses the fusion problem of different dimensional features,has been implemented by aligning and sharing information through aggregation and distribution mechanisms.Thirdly,considering the limitations in current bounding box regression and the imbalance between complex and simple samples,Maximum Possible Distance Intersection over Union(MPDIoU)and Adaptive SlideLoss is incorporated into the loss function,allowing samples near the Intersection over Union(IoU)to receive more attention through the dynamic variation of the mean Intersection over Union.The GD-YOLO algorithm can surpass YOLOv5,YOLOv7,and YOLOv8 in infrared image detection for electrical equipment,achieving a mean Average Precision(mAP)of 88.9%,with accuracy improvements of 3.7%,4.3%,and 3.1%,respectively.Additionally,the model delivers a frame rate of 48 FPS,which aligns with the precision and velocity criteria necessary for the detection of infrared images in power equipment.
文摘In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.
基金funded by the Department of Education of Liaoning Province and was supported by the Basic Scientific Research Project of the Department of Education of Liaoning Province(Grant No.LJ222411632051)and(Grant No.LJKQZ2021085)Natural Science Foundation Project of Liaoning Province(Grant No.2022-BS-222).
文摘Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.
基金supported by the Royal Academy of Engineering,UK,in the scheme of Distinguished International Associate(DIA-2424-5-134).
文摘Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.
基金supported by Integrated Distribution Network Planning and Operational Enhancement Using Flexibility Domains Under Deep Human-Vehicle-Charger-Road-Grid Coupling(U22B20105).
文摘Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.
基金Supported by National Natural Science Foundation of China(Grant No.62271230)Shandong Provincial Central Guidance on Local Science and Technology Development Fund(Grant No.YDZX2022178).
文摘Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-synchrosqueezing transform(TMssT)was proposed to capture these transient impulses for fault diagnosis.However,the TMSST,which is based on the short-time Fourier transform(STFT),suffers from unclear high-frequency re-presentations owing to the fixed sliding window used in the STFT.To address this limitation,the current study combined TMSST with the S-transform and a local maximum method to enhance the time-frequency representation for improved signal analysis.Furthermore,an extractive reconstruction algorithm that binds the maximum value of the spectral envelope is proposed for spectral decomposition.To validate the proposed technique,a simulated noise-added signal and four experimental bearing defect datasets were used.The results demonstrate that the proposed technique can effectively and accurately extract fault features from bearing signals regardless of whether the bearings operate under constant or varying speed conditions.This study offers a novel and efficient approach for fault diagnosis in mechanical systems with complex dynamic behaviors.
基金supported by the Key Project of Shanghai(Project Number A1-0224-25-002-02-040,Municipal Key Course—Heat Transfer)funded by the National Natural Science Foundation of China(Grant No.52077137).
文摘To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon capture and storage(CCS),hydrogen fuel cell(HFC),and combined heat and power(CHP).The P2G process is refined into a two-stage structure,and HFC is introduced to enhance hydrogen utilization.Together with CCS and CHP,these devices form a multi-energy conversion system coupling electricity,heat,cooling,and gas.A laddertype carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.To evaluate the resilience of the proposed low-carbon scheduling strategy involving multiple energy units under the variability of renewable energy,a two-level robust optimization framework is developed.This model captures the most adverse scenarios of wind and solar generation.The dispatch strategy is validated against these extreme conditions to demonstrate its flexibility and effectiveness.The problem is solved using the GUROBI optimization tool.Results from simulations indicate that themodel increases renewable energy integration by 39.1%,and achieves reductions of 15.96%in carbon emissions and 16.29%in operational expenditures.The results demonstrate that the strategy ensures both economic efficiency and environmental performance under uncertain conditions.Compared with existing studies that separately model two-stage P2G or CCS devices,this paper integrates HFC,CHP,and CCS into a unified dispatchable system,enabling refined hydrogen utilization and flexible carbon circulation.Furthermore,the introduction of a laddertype carbon pricing mechanism,combined with multi-energy storage participation in implicit demand response,creates a dynamic and cost-sensitive dispatch framework.These modeling strategies go beyond conventional linear IES formulations and provide more realistic system representations.The proposed approach not only deepens the coupling among electric,thermal,and gas systems,but also offers a feasible pathway for high-penetration renewable integration in low-carbon energy systems.
文摘Distribution transformers play a vital role in power distribution systems,and their reliable operation is crucial for grid stability.This study presents a simulation-based framework for active fault diagnosis and early warning of distribution transformers,integrating Sample Ensemble Learning(SEL)with a Self-Optimizing Support Vector Machine(SO-SVM).The SEL technique enhances data diversity and mitigates class imbalance,while SO-SVM adaptively tunes its hyperparameters to improve classification accuracy.A comprehensive transformer model was developed in MATLAB/Simulink to simulate diverse fault scenarios,including inter-turn winding faults,core saturation,and thermal aging.Feature vectors were extracted from voltage,current,and temperature measurements to train and validate the proposed hybrid model.Quantitative analysis shows that the SEL–SO-SVM framework achieves a classification accuracy of 97.8%,a precision of 96.5%,and an F1-score of 97.2%.Beyond classification,the model effectively identified incipient faults,providing an early warning lead time of up to 2.5 s before significant deviations in operational parameters.This predictive capability underscores its potential for preventing catastrophic transformer failures and enabling timely maintenance actions.The proposed approach demonstrates strong applicability for enhancing the reliability and operational safety of distribution transformers in simulated environments,offering a promising foundation for future real-time and field-level implementations.
基金supported in part by the National Natural Science Foundation of China(under Grant 62473309,62203352)the Shaanxi Outstanding Youth Science Fund Project(under Grant 2024JC-JCQN-68)+1 种基金the Xi’an Science and Technology Plan Project(under Grant 24GXFW0050)the Xi’an Key Laboratory(under Grant 24ZDSY0015).
文摘Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason,a SOH estimation method is proposed based on charging data reconstruction combined with image processing.The charging voltage data is used to train the least squares generative adversarial network(LSGAN),which is validated under different levels of missing data.From a visual perspective,the Gram angle field method is applied to convert one-dimensional time series data into image data.This method fully preserves the time series characteristics and nonlinear evolution patterns,which avoids the difficulties and limited expressive power associated with manual feature extraction.At the same time,the Swin Transformer model is introduced to extract global structures and local details from images,enabling better capture of sequence change trends.Combined with the long short-term memory network(LSTM),this enables accurate estimation of battery SOH.Two different types of batteries are used to validate the test.The experimental results show that the proposed method has good estimation accuracy under different training proportions.
基金Supported by National Natural Science Foundation of China(Grant No.52275206).
文摘There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior separately.In this paper,a unified tribology-kinematic model is established considering the coupling effect between friction and the ball velocity vector.The friction in ball-groove contact and ball speed are simultaneously measured by a newly developed disc-ball-disc device for studying friction and movement in ball screws.A comprehensive analysis of rubbing interface behavior and ball motion is conducted.The results show that the coupling effect between friction in ball-groove contact and ball motion is quite obvious.The sliding velocity of the ball is much higher with coupling effect than that when ignoring coupling influence,especially at high-speed conditions.The friction in ball-groove contact decreases at first and then shows a dramatic increase with the gradual rise of rotation speed,which is caused by the coupling variation of sliding speed.The studies show that the disc-ball-disc approach is an innovative and valuable method to investigate friction and ball motion in ball screws.
基金supported by National Science and Technology Major Project(2025ZD0618901)National Natural Science Foundation of China(U2241245 and 52321001)+2 种基金Aeronautical Science Foundation of China(2022Z053092001)Natural Science Foundation of Shenyang(23-503-6-05)Science and Technology Major Project of Liaoning Province(2024JH1/11700028).
文摘Effects of alloying elements Ni,Co,Mn,Cr,and H on the stacking fault energy(SFE)ofγ-Fe and its microscopic mechanisms were systematically investigated.Generalized SFE calculations show that individual alloying elements Ni,Co,and H increase SFE ofγ-Fe,whereas Mn and Cr decrease SFE.The influence of alloying elements on SFE exhibits short-range characteristics.The effect of synergistic interaction of alloying elements and H on SFE was further investigated.Results show that the co-alloying of Ni/Co with H exacerbates the effect of H on the increase in SFE.In contrast,the synergistic effect of Mn/Cr with H tends to inhibit H from the increasing SFE.Finally,the electronic structure analysis elucidated the microscopic mechanism of the change in SFE.Alloying elements modulate SFE by changing the interatomic charge density at the stacking fault plane and the density of states of the stacking fault structure at the Fermi level.The present results add to the knowledge of alloying related influence on the mechanical property and hydrogen embrittlement ofγ-Fe.
基金Project supported by the Excellence Research Group Program for Multiscale Problems in Nonlinear Mechanics of the National Natural Science Foundation of China(Grant No.12588201)the National Key R&D Program of China(Grant No.2025YFB3003603)+1 种基金the National Natural Science Foundation of China(Grant No.12135002)the Fundamental Research Funds for the Central Universities,Peking University,the Beijing Natural Science Foundation(Grant No.QY23030)。
文摘Current experimental techniques still face challenges in clarifying the structural and dynamic properties of helium(He)in liquid lithium(Li).A critical example of this technical hurdle is the formation of He bubbles,which significantly affects the transport of He within liquid Li—a vital aspect when considering liquid Li as a plasma-facing material in nuclear fusion reactors.We develop a machine-learning-based deep potential(DP)with ab initio accuracy for the Li-He system and perform molecular dynamics simulations at temperatures ranging from 470 K to 1270 K with a wide range of He concentrations.We observe that He atoms exhibit a tendency to aggregate and form clusters and bubbles in liquid Li.Notably,He clusters exhibit a significant increase in size at elevated temperatures and high concentrations of He,accompanied by the phase separation of Li and He atoms.We also observe an anomalous non-linear relationship between the diffusion coefficient of He and temperature,which is attributed to the larger cluster size at higher temperatures.Our study provides a deeper understanding of the behavior of He in liquid Li and further supports the potential application of liquid Li under extreme conditions.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(MSIT),South Korea(RS-2024-00421181)financially supported in part by National R&D Program(2021M3H4A3A02086430)through NRF(National Research Foundation of Korea)funded by Ministry of Science and ICT+2 种基金the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL25021-210)The Inter-University Semiconductor Research Center,Institute of Engineering Research,and Soft Foundry Institute at Seoul National University provided research facilities for this workhe grant by the National Research Foundation of Korea(NSF)supported by the Korea government(MIST)(RS-2025-16903034)。
文摘As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.
基金supported by the National Natural Science Foundation of China(22175136)the State Key Laboratory of Electrical Insulation and Power Equipment(EIPE23127)the Fundamental Research Funds for the Central Universities(xtr052024009).
文摘Metal hydrides with high hydrogen density provide promising hydrogen storage paths for hydrogen transportation.However,the requirement of highly pure H_(2)for re-hydrogenation limits its wide application.Here,amorphous Al_(2)O_(3)shells(10 nm)were deposited on the surface of highly active hydrogen storage material particles(MgH_(2)-ZrTi)by atomic layer deposition to obtain MgH_(2)-ZrTi@Al_(2)O_(3),which have been demonstrated to be air stable with selective adsorption of H_(2)under a hydrogen atmosphere with different impurities(CH_(4),O_(2),N_(2),and CO_(2)).About 4.79 wt% H_(2)was adsorbed by MgH_(2)-ZrTi@10nmAl_(2)O_(3)at 75℃under 10%CH_(4)+90%H_(2)atmosphere within 3 h with no kinetic or density decay after 5 cycles(~100%capacity retention).Furthermore,about 4 wt%of H_(2)was absorbed by MgH_(2)-ZrTi@10nmAl_(2)O_(3)under 0.1%O_(2)+0.4%N_(2)+99.5%H_(2)and 0.1%CO_(2)+0.4%N_(2)+99.5%H_(2)atmospheres at 100℃within 0.5 h,respectively,demonstrating the selective hydrogen absorption of MgH_(2)-ZrTi@10nmAl_(2)O_(3)in both oxygen-containing and carbon dioxide-containing atmospheres hydrogen atmosphere.The absorption and desorption curves of MgH_(2)-ZrTi@10nmAl_(2)O_(3)with and without absorption in pure hydrogen and then in 21%O_(2)+79%N_(2)for 1 h were found to overlap,further confirming the successful shielding effect of Al_(2)O_(3)shells against O_(2)and N_(2).The MgH_(2)-ZrTi@10nmAl_(2)O_(3)has been demonstrated to be air stable and have excellent selective hydrogen absorption performance under the atmosphere with CH_(4),O_(2),N_(2),and CO_(2).
基金supported by the National Natural Science Foundation of China(Grant No.42375192).
文摘The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m^(−2) in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.
基金support from National Key Research and Development Program of China(2024YFE0217100)the National Natural Science Foundation of China(21905006,22261160370,and 62105075)+7 种基金the Guangdong Provincial Science and Technology Plan(2021A0505110003)the Natural Science Foundation of Hunan Province,China(2023JJ50132)Guangxi Department of Science and Technology(2020GXNSFBA159049 and AD19110030)the Shenzhen Science and Technology Program(SGDX20230116093205009,JCYJ20220818100211025 and 2022378670)the Natural Science Foundation of Top Talent of SZTU(GDRC202343)financial support of Innovation and Technology Fund(#GHP/245/22SZ)The University Grant Council of the University of Hong Kong(grant No.2302101786)General Research Fund(grant Nos.17200823 and 17310624)from the Research Grants Council.
文摘Halide perovskites have emerged as promising materials for X-ray detection with exceptional properties and reasonable costs.Among them,heterostructures between 3D perovskites and low-dimensional perovskites attract intensive studies of their advantages due to low-level ion migration and decent stability.However,there is still a lack of methods to precisely construct heterostructures and a fundamental understanding of their structure-dependent optoelectronic properties.Herein,a gas-phase method was developed to grow 2D perovskites directly on 3D perovskites with nanoscale accuracy.In addition,the larger steric hindrance of organic layers of 2D perovskites was proved to enable slower ion migration,which resulted in reduced trap states and better stability.Based on MAPbBr_(3)single crystals with the(PA)_(2)PbBr_(4)capping layer,the X-ray detector achieved a sensitivity of 22,245μC Gy_(air)^(−1)cm^(−2),a response speed of 240μs,and a dark current drift of 1.17.10^(–4)nA cm^(−1)s^(−1)V^(−1),which were among the highest reported for state-of-the-art perovskite-based X-ray detectors.This study presents a precise synthesis method to construct perovskite-based heterostructures.It also brings an in-depth understanding of the relationship between lattice structures and properties,which are beneficial for advancing high-performance and cost-effective X-ray detectors.
基金financially supported by the National Natural Science Foundation of China (No.51777057)the Natural Science Foundation of Hebei Province, China (No.E2016202106)the Science and Technology Research Project of Colleges and Universities in Hebei Province, China (No.ZD2016078)
文摘AgSnO_ 2 electrical contact materials doped with Bi_2O_3,La_2O_3,and TiO_2 were successfully fabricated by the powder metallurgy method under different initial sintering temperatures.The electrical conductivity,density,hardness,and contact resistance of the Ag Sn O_2/Bi_2O_3,AgSnO_2/La_2O_3,and AgSnO_2/Ti O_2 contact materials were measured and analyzed.The arc-eroded surface morphologies of the doped AgSnO_2 contact materials were investigated by scanning electron microscopy(SEM).The effects of the initial sintering temperature on the physical properties and electrical contact properties of the doped AgSnO_2 contact materials were discussed.The results indicate that the physical properties can be improved and the contact resistance of the AgSnO_2 contact materials can be substantially reduced when the materials are sintered under their optimal initial sintering temperatures.
基金supported by the National Natural Science Foundation of China (Nos. U1234202 and 51577158)the National Science Foundation for Distinguished Young Scholars of China (No. 51325704)the Fundamental Research Funds for the Central Universities (No. A0920502051505-19)
文摘A good contact between the pantograph and catenary is critically important for the working reliability of electric trains, while the basic understanding on the electrical contact evolution during the pantograph--catenary system working is still ambiguous so far. In this paper, the evolution of electric contact was studied in respects of the contact resistance, temperature rise, and microstructure variation, based on a home-made pantograph-catenary simulation system. Pure carbon strips and copper alloy contact wires were used, and the experimental electrical current, sliding speed, and normal force were set as 80 A, 30 km/h, and 80 N, respectively. The contact resistance presented a fluctuation without obvious regularity, concentrating in the region of 25 and 50 mf~. Temperature rise of the contact point experienced a fast increase at the first several minutes and finally reached a steady state. The surface damage of carbon trips in microstructure analysis revealed a complicated interaction of the sliding friction, joule heating, and arc erosion.
