Severe injuries due to electricity are rare,but when they occur,they may cause life-threatening conditions.In order to define the severity of electrical injuries,the most widely used classification is voltage power.In...Severe injuries due to electricity are rare,but when they occur,they may cause life-threatening conditions.In order to define the severity of electrical injuries,the most widely used classification is voltage power.Injuries are mainly classified into two categories as low voltage electrical injuries(LVEI)(<1000 V)and high voltage electrical injuries(>1000 V).Fatal injuries have been reported mostly after high-voltage electric shock.Low-voltage electricity current rarely causes severe trauma and complications.展开更多
Recent advances in van der Waals(vdW) ferroelectrics have sparked the development of related heterostructures with non-volatile and field-tunable functionalities. In vdW ferroelectric heterojunctions, the interfacial ...Recent advances in van der Waals(vdW) ferroelectrics have sparked the development of related heterostructures with non-volatile and field-tunable functionalities. In vdW ferroelectric heterojunctions, the interfacial electrical characteristics play a crucial role in determining their performance and functionality. In this study,we explore the interfacial polarization coupling in two-dimensional(2D) ferroelectric heterojunctions by fabricating a graphene/h-BN/CuInP_(2)S_(6)/α-In_(2)Se_(3)/Au ferroelectric field-effect transistor. By varying the gate electric field, the CuInP_(2)S_(6)/α-In_(2)Se_(3) heterojunction displays distinct interfacial polarization coupling states, resulting in significantly different electrical transport behaviors. Under strong gate electric fields, the migration of Cu ions further enhances the interfacial polarization effect, enabling continuous tuning of both the polarization state and carrier concentration in α-In_(2)Se_(3). Our findings offer valuable insights for the development of novel multifunctional devices based on 2D ferroelectric materials.展开更多
To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge gen...To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.展开更多
Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secur...According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secured China's position as the world's largest auto market for the 17th year in a row.展开更多
Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer e...Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.展开更多
To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobje...To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.展开更多
To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy s...To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy storage(ES)devices),and the increased grid load fluctuations and safety risks due to uncoordinated electric vehicles(EVs)charging,this paper proposes a novel dual-scale hierarchical collaborative optimization strategy.This strategy decouples system-level economic dispatch from distributed EV agent control,effectively solving the resource coordination conflicts arising from the high computational complexity,poor scalability of existing centralized optimization,or the reliance on local information decision-making in fully decentralized frameworks.At the lower level,an EV charging and discharging model with a hybrid discrete-continuous action space is established,and optimized using an improved Parameterized Deep Q-Network(PDQN)algorithm,which directly handles mode selection and power regulation while embedding physical constraints to ensure safety.At the upper level,microgrid(MG)operators adopt a dynamic pricing strategy optimized through Deep Reinforcement Learning(DRL)to maximize economic benefits and achieve peak-valley shaving.Simulation results show that the proposed strategy outperforms traditional methods,reducing the total operating cost of the MG by 21.6%,decreasing the peak-to-valley load difference by 33.7%,reducing the number of voltage limit violations by 88.9%,and lowering the average electricity cost for EV users by 15.2%.This method brings a win-win result for operators and users,providing a reliable and efficient scheduling solution for distribution networks with high renewable energy penetration rates.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is p...Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.展开更多
Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombinati...Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.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
The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter per...The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.展开更多
China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This s...China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This study presents a compar ative analysis of the national electric bicycle standards in China and Malaysia,offering technical insights from a standardization perspective.These insights aim to support Chinese enterprises in strategically positioning their technologies in the Malaysian market.The findings reveal significant differences in technical parameters,safety requirements,and testing methods,highlighting the need for tailored product adapt ation.展开更多
As a core functional refractory in the continuous casting process,the service reliability of the submerged entry nozzle(SEN)is directly related to the stability of continuous casting production,the quality of casting ...As a core functional refractory in the continuous casting process,the service reliability of the submerged entry nozzle(SEN)is directly related to the stability of continuous casting production,the quality of casting billets,and production efficiency.Al_(2)O_(3) inclusions clogging constitutes the predominant failure mode of SEN,particularly during continuous casting of high-grade steels.Although several studies in the literature have demonstrated that electric field application can mitigate SEN clogging to some extent,the underlying mechanism remains poorly understood,which hinders its widespread acceptance and practical implementation.The mechanism of preventing SEN clogging by applying a positive electric field was studied,and experimental verification was conducted on it in a certain steel plant.The results indicate that Al_(2)O_(3) inclusions exhibit a positive charge in molten steel under high-temperature(~1600℃)and low-oxygen-partial-pressure(≤20×10-6)conditions.In the continuous casting process at a Chinese steel plant,applying a positive electric field to the SEN effectively suppressed the migration of Al_(2)O_(3) inclusions toward the SEN wall,significantly enhancing its clogging resistance.展开更多
With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyz...With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.展开更多
The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rap...The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rapid and accurate prediction crucial for high-throughput screening and development of high-performance alloys.This study introduces a physics-informed symbolic regression approach that addresses the limitations of traditional methods,including the high computational cost of first-principles calculations and the poor interpretability of machine learning models.Comprehensive datasets comprising 1512 data points from 60 literature sources were analyzed,including thermal conductivity measurements from 52 alloy systems and electrical conductivity measurements from 36 systems.The derived symbolic regression model achieved Mean Absolute Percentage Errors(MAPEs)of 11.2%and 11.4%for thermal conductivity in low and high-component systems,respectively.When integrated with the Smith-Palmer equation,electrical conductivity predictions reached MAPEs of 15.6%and 16.4%.Independent validation on an entirely separate dataset of 554 data points from 53 additional literature sources,including 37 previously unseen alloy systems,confirmed model generalizability with MAPEs of 10.7%-15.2%.Shapley Additive Explanations(SHAP)analysis was employed to evaluate the relative importance of different features affecting conductivity,while equation decomposition quantified the contribution of individual functional terms.This methodology bridges data-driven prediction with mechanistic understanding,establishing a foundation for knowledge-based design of magnesium alloys with tailored transport properties.展开更多
Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning ...Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning methods,accurate and reliable price forecasts can be achieved.This study forecasts day-ahead prices in Türkiye’s electricity market using eXtreme Gradient Boosting(XGBoost).We benchmark XGBoost against four alternatives—Support Vector Machines(SVM),Long Short-Term Memory(LSTM),Random Forest(RF),and Gradient Boosting(GBM)—using 8760 hourly observations from 2023 provided by Energy Exchange Istanbul(EXIST).All models were trained on an identical chronological 80/20 train–test split,with hyperparameters tuned via 5-fold cross-validation on the training set.XGBoost achieved the best performance(Mean Absolute Error(MAE)=144.8 TRY/MWh,Root Mean Square Error(RMSE)=201.8 TRY/MWh,coefficient of determination(R^(2))=0.923)while training in 94 s.To enhance interpretability and identify key drivers,we employed Shapley Additive Explanations(SHAP),which highlighted a strong association between higher prices and increased natural-gas-based generation.The results provide a clear performance benchmark and practical guidance for selecting forecasting approaches in day-ahead electricity markets.展开更多
Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short...Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short time remains a major challenge.In this study,a multifunctional mussel-inspired hydrogel was synthesized in only 5 min,with polydopamine(PDA)-polypyrrole(Ppy)-polyaniline(PANi)and poly(vinyl alcohol)(PVA)nanoparticles incorporated into the polyacrylamide(PAM)network.The resulting hydrogel exhibited high transparency(about 90% light transmission in the range of 400-800 nm),high conductivity((95.4±0.4)×10^(-4)S/cm),tensile strength(32.60±1.03 k Pa),strain at break(904.46%±11.50%),and adhesive strength(30-60 k Pa).It also demonstrated rapid self-healing properties(about 48% strength recovery within 1h at 50℃)and water-dependent shape memory behavior.As a wearable strain sensor,the hydrogel successfully detected finger flexion,wrist movements,facial expression changes,and breathing with high sensitivity and stability.The calculated gauge factor(GF)was 7.44±0.31,which is higher than that of many previously reported hydrogels.Compared with previous oyster-inspired or Ppy-based hydrogels,our system showed a much shorter synthesis time,higher transparency,and enhanced multifunctionality.These findings highlight the potential of the proposed hydrogel for next-generation flexible electronics,e-skin,and biomedical monitoring devices.展开更多
The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack...The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack a unified data structure,and depend heavily on manual intervention to process high-frequency and retroactive transactions.To address these limitations,a graph-based unified settlement framework is proposed to enhance automation,flexibility,and adaptability in electricity market settlements.A flexible attribute-graph model is employed to represent heterogeneousmulti-market data,enabling standardized integration,rapid querying,and seamless adaptation to evolving business requirements.An extensible operator library is designed to support configurable settlement rules,and a suite of modular tools—including dataset generation,formula configuration,billing templates,and task scheduling—facilitates end-to-end automated settlement processing.A robust refund-clearing mechanism is further incorporated,utilizing sandbox execution,data-version snapshots,dynamic lineage tracing,and real-time changecapture technologies to enable rapid and accurate recalculations under dynamic policy and data revisions.Case studies based on real-world data from regional Chinese markets validate the effectiveness of the proposed approach,demonstrating marked improvements in computational efficiency,system robustness,and automation.Moreover,enhanced settlement accuracy and high temporal granularity improve price-signal fidelity,promote cost-reflective tariffs,and incentivize energy-efficient and demand-responsive behavior among market participants.The method not only supports equitable and transparent market operations but also provides a generalizable,scalable foundation for modern electricity settlement platforms in increasingly complex and dynamic market environments.展开更多
文摘Severe injuries due to electricity are rare,but when they occur,they may cause life-threatening conditions.In order to define the severity of electrical injuries,the most widely used classification is voltage power.Injuries are mainly classified into two categories as low voltage electrical injuries(LVEI)(<1000 V)and high voltage electrical injuries(>1000 V).Fatal injuries have been reported mostly after high-voltage electric shock.Low-voltage electricity current rarely causes severe trauma and complications.
基金supported by the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-049)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302800)the Fundamental Research Funds for the Central Universities(Grant No.WK3510000013)。
文摘Recent advances in van der Waals(vdW) ferroelectrics have sparked the development of related heterostructures with non-volatile and field-tunable functionalities. In vdW ferroelectric heterojunctions, the interfacial electrical characteristics play a crucial role in determining their performance and functionality. In this study,we explore the interfacial polarization coupling in two-dimensional(2D) ferroelectric heterojunctions by fabricating a graphene/h-BN/CuInP_(2)S_(6)/α-In_(2)Se_(3)/Au ferroelectric field-effect transistor. By varying the gate electric field, the CuInP_(2)S_(6)/α-In_(2)Se_(3) heterojunction displays distinct interfacial polarization coupling states, resulting in significantly different electrical transport behaviors. Under strong gate electric fields, the migration of Cu ions further enhances the interfacial polarization effect, enabling continuous tuning of both the polarization state and carrier concentration in α-In_(2)Se_(3). Our findings offer valuable insights for the development of novel multifunctional devices based on 2D ferroelectric materials.
基金supported by the National Key Research and Development Project of the National Natural Science Foundation of China(Grant No.2022YFC3004605)the National Natural Science Foundation of China Youth Science Fund(Grant No.52104087).
文摘To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.
文摘Each morning at Yangluo Port in Wuhan,Hubei Province,the all-electric cargo vessel Huahang Xinneng No.1 completes a battery swap in under 10 minutes before returning to service with nearly 8,000 kWh of power onboard。
文摘According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secured China's position as the world's largest auto market for the 17th year in a row.
基金supported by the National Natural Science Foundation of China(No.22278156)the Guangdong Special Support Program Project(No.2021JC060580)+1 种基金the Young Elite Scientists Sponsorship Program by CAST-Doctoral Student Special Plan,the China Scholarship Council Program(No.202406150148)the Natural Science Foundation of Guangdong Province(No.2023A1515011186).
文摘Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.
基金Supported by State Grid Corporation of China Science and Technology Project:Research on Key Technologies for Intelligent Carbon Metrology in Vehicle-to-Grid Interaction(Project Number:B3018524000Q).
文摘To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.
基金supported in part by the Research on Key Technologies for the Development of an Active Balancing Cooperative Control Systemfor Distribution Networks and the National Natural Science Foundation of China under Grant 521532240029,Grant 62303006.
文摘To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy storage(ES)devices),and the increased grid load fluctuations and safety risks due to uncoordinated electric vehicles(EVs)charging,this paper proposes a novel dual-scale hierarchical collaborative optimization strategy.This strategy decouples system-level economic dispatch from distributed EV agent control,effectively solving the resource coordination conflicts arising from the high computational complexity,poor scalability of existing centralized optimization,or the reliance on local information decision-making in fully decentralized frameworks.At the lower level,an EV charging and discharging model with a hybrid discrete-continuous action space is established,and optimized using an improved Parameterized Deep Q-Network(PDQN)algorithm,which directly handles mode selection and power regulation while embedding physical constraints to ensure safety.At the upper level,microgrid(MG)operators adopt a dynamic pricing strategy optimized through Deep Reinforcement Learning(DRL)to maximize economic benefits and achieve peak-valley shaving.Simulation results show that the proposed strategy outperforms traditional methods,reducing the total operating cost of the MG by 21.6%,decreasing the peak-to-valley load difference by 33.7%,reducing the number of voltage limit violations by 88.9%,and lowering the average electricity cost for EV users by 15.2%.This method brings a win-win result for operators and users,providing a reliable and efficient scheduling solution for distribution networks with high renewable energy penetration rates.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金supported by National Natural Science Foundation of China(No.52025055 and 52275571)Basic Research Operation Fund of China(No.xzy012024024).
文摘Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.
基金Supported by National Natural Science Foundation of China(Grant Nos.52005039,51575043,51975048,U1764257).
文摘Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.
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 the National Natural Science Foundation of China(52471240)the Natural Science Foundation of Zhejiang Province(LZ23B030003)+2 种基金the Fundamental Research Funds for the Central Universities(226-2024-00075)support from the Engineering and Physical Sciences Research Council(EPSRC,UK)RiR grant-RIR18221018-1EU COST CA23155。
文摘The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.
文摘China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This study presents a compar ative analysis of the national electric bicycle standards in China and Malaysia,offering technical insights from a standardization perspective.These insights aim to support Chinese enterprises in strategically positioning their technologies in the Malaysian market.The findings reveal significant differences in technical parameters,safety requirements,and testing methods,highlighting the need for tailored product adapt ation.
基金supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China(No.52302031)National Natural Science Foundation of China(No.51932008).
文摘As a core functional refractory in the continuous casting process,the service reliability of the submerged entry nozzle(SEN)is directly related to the stability of continuous casting production,the quality of casting billets,and production efficiency.Al_(2)O_(3) inclusions clogging constitutes the predominant failure mode of SEN,particularly during continuous casting of high-grade steels.Although several studies in the literature have demonstrated that electric field application can mitigate SEN clogging to some extent,the underlying mechanism remains poorly understood,which hinders its widespread acceptance and practical implementation.The mechanism of preventing SEN clogging by applying a positive electric field was studied,and experimental verification was conducted on it in a certain steel plant.The results indicate that Al_(2)O_(3) inclusions exhibit a positive charge in molten steel under high-temperature(~1600℃)and low-oxygen-partial-pressure(≤20×10-6)conditions.In the continuous casting process at a Chinese steel plant,applying a positive electric field to the SEN effectively suppressed the migration of Al_(2)O_(3) inclusions toward the SEN wall,significantly enhancing its clogging resistance.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China,grant number 21YJA790009National Natural Science Foundation of China,grant number 72140001.
文摘With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.
基金supported by the National Key Research and Development Program of China(No.2023YFB3712401)the National Natural Science Foundation of China(No.52274301)+2 种基金the Aeronautical Science Foundation of China(No.2023Z0530S6005)Academician Workstation of Kunming University of Science and Technology(2024),Ningbo Yongjiang Talent-Introduction Program(No.2022A-023C)Zhejiang Phenomenological Materials Technology Co.,Ltd.,China.
文摘The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rapid and accurate prediction crucial for high-throughput screening and development of high-performance alloys.This study introduces a physics-informed symbolic regression approach that addresses the limitations of traditional methods,including the high computational cost of first-principles calculations and the poor interpretability of machine learning models.Comprehensive datasets comprising 1512 data points from 60 literature sources were analyzed,including thermal conductivity measurements from 52 alloy systems and electrical conductivity measurements from 36 systems.The derived symbolic regression model achieved Mean Absolute Percentage Errors(MAPEs)of 11.2%and 11.4%for thermal conductivity in low and high-component systems,respectively.When integrated with the Smith-Palmer equation,electrical conductivity predictions reached MAPEs of 15.6%and 16.4%.Independent validation on an entirely separate dataset of 554 data points from 53 additional literature sources,including 37 previously unseen alloy systems,confirmed model generalizability with MAPEs of 10.7%-15.2%.Shapley Additive Explanations(SHAP)analysis was employed to evaluate the relative importance of different features affecting conductivity,while equation decomposition quantified the contribution of individual functional terms.This methodology bridges data-driven prediction with mechanistic understanding,establishing a foundation for knowledge-based design of magnesium alloys with tailored transport properties.
文摘Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning methods,accurate and reliable price forecasts can be achieved.This study forecasts day-ahead prices in Türkiye’s electricity market using eXtreme Gradient Boosting(XGBoost).We benchmark XGBoost against four alternatives—Support Vector Machines(SVM),Long Short-Term Memory(LSTM),Random Forest(RF),and Gradient Boosting(GBM)—using 8760 hourly observations from 2023 provided by Energy Exchange Istanbul(EXIST).All models were trained on an identical chronological 80/20 train–test split,with hyperparameters tuned via 5-fold cross-validation on the training set.XGBoost achieved the best performance(Mean Absolute Error(MAE)=144.8 TRY/MWh,Root Mean Square Error(RMSE)=201.8 TRY/MWh,coefficient of determination(R^(2))=0.923)while training in 94 s.To enhance interpretability and identify key drivers,we employed Shapley Additive Explanations(SHAP),which highlighted a strong association between higher prices and increased natural-gas-based generation.The results provide a clear performance benchmark and practical guidance for selecting forecasting approaches in day-ahead electricity markets.
文摘Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short time remains a major challenge.In this study,a multifunctional mussel-inspired hydrogel was synthesized in only 5 min,with polydopamine(PDA)-polypyrrole(Ppy)-polyaniline(PANi)and poly(vinyl alcohol)(PVA)nanoparticles incorporated into the polyacrylamide(PAM)network.The resulting hydrogel exhibited high transparency(about 90% light transmission in the range of 400-800 nm),high conductivity((95.4±0.4)×10^(-4)S/cm),tensile strength(32.60±1.03 k Pa),strain at break(904.46%±11.50%),and adhesive strength(30-60 k Pa).It also demonstrated rapid self-healing properties(about 48% strength recovery within 1h at 50℃)and water-dependent shape memory behavior.As a wearable strain sensor,the hydrogel successfully detected finger flexion,wrist movements,facial expression changes,and breathing with high sensitivity and stability.The calculated gauge factor(GF)was 7.44±0.31,which is higher than that of many previously reported hydrogels.Compared with previous oyster-inspired or Ppy-based hydrogels,our system showed a much shorter synthesis time,higher transparency,and enhanced multifunctionality.These findings highlight the potential of the proposed hydrogel for next-generation flexible electronics,e-skin,and biomedical monitoring devices.
基金funded by the Science and Technology Project of State Grid Corporation of China(5108-202355437A-3-2-ZN).
文摘The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack a unified data structure,and depend heavily on manual intervention to process high-frequency and retroactive transactions.To address these limitations,a graph-based unified settlement framework is proposed to enhance automation,flexibility,and adaptability in electricity market settlements.A flexible attribute-graph model is employed to represent heterogeneousmulti-market data,enabling standardized integration,rapid querying,and seamless adaptation to evolving business requirements.An extensible operator library is designed to support configurable settlement rules,and a suite of modular tools—including dataset generation,formula configuration,billing templates,and task scheduling—facilitates end-to-end automated settlement processing.A robust refund-clearing mechanism is further incorporated,utilizing sandbox execution,data-version snapshots,dynamic lineage tracing,and real-time changecapture technologies to enable rapid and accurate recalculations under dynamic policy and data revisions.Case studies based on real-world data from regional Chinese markets validate the effectiveness of the proposed approach,demonstrating marked improvements in computational efficiency,system robustness,and automation.Moreover,enhanced settlement accuracy and high temporal granularity improve price-signal fidelity,promote cost-reflective tariffs,and incentivize energy-efficient and demand-responsive behavior among market participants.The method not only supports equitable and transparent market operations but also provides a generalizable,scalable foundation for modern electricity settlement platforms in increasingly complex and dynamic market environments.
