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
The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being promi...The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being prominent examples.Consequently,promoting bone regeneration is a crucial medical challenge that demands immediate attention.As early as the mid-20th century,researchers revealed that electrical stimulation could effectively promote the healing and regeneration of bone tissue.This is achieved by mimicking the endogenous electric field within bone tissue,which influences cellular behavior and molecular mechanisms.In recent years,electroactive hydrogels responsive to electric field stimulation have been developed and applied to regulate cell functions at different stages of bone regeneration.This paper elaborates on the regulatory effects of electrical stimulation on MSCs,macrophages,and vascular endothelial cells during the process of bone regeneration.It also involves the activation of relevant ion channels and signaling pathways.Subsequently,it comprehensively reviews various electric-field-responsive hydrogels developed in recent years,covering aspects such as material selection,preparation methods,characteristics,and their applications in bone regeneration.Ultimately,it provides an objective summary of the existing deficiencies in hydrogel materials and research,and looks ahead to future development directions.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
Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating c...Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating current(AC)(direct current(DC))voltage control.In fact,faster and more stable active and reactive power in the presence of frequency and voltage sags and swells is needed.Power electronics-controlled variable speed generators do not have enough energy storage(inertia)for the scope(static synchronous compensators(STATCOMs)included).This is because power electronics tends to decouple the generator from the power system.While virtual inertia control in doubly fed induction generators(DFIGs)offers a partial solution to these problems,a more robust and comprehensive framework is required for advanced grid support.This is how,by extending the dual-excitation principles,the dualaxis excited electric synchronous generators(DE-SG)provide superior flexibility in two variants summarized here:as a multifunctional DFIG and dual-axis vs.single-axis excited synchronous generator(SG),and as a synchronous condenser(SC),with dual DC and AC excitation(as a no-load DFIG with inertia wheel),where variable speed is used to accelerate/decelerate the SC and thus provide additional assistance in frequency stabilization.These solutions,good for short-time transients,are not meant,however,to replace the large bidirectional energy storage systems(pump-hydro,hydrogen,batteries,etc.)which are crucial for the daily inherent variations of output energy in modern power systems with multiple power sources.The present paper offers a summary of techniques used in the dual-axis excited vs.single-axis excited SGs(SE-SGs),and SCs topologies,modeling,and control for better stability in modern multiple-source energy systems.This survey includes multiple case studies to shed light on prominent methods.展开更多
The interdependence of electrical parameters has long inhibited the progress of bismuth telluride(Bi_(2)Te3),limiting its widespread application in thermoelectric cooling and power generation.This work investigates th...The interdependence of electrical parameters has long inhibited the progress of bismuth telluride(Bi_(2)Te3),limiting its widespread application in thermoelectric cooling and power generation.This work investigates the n-type Bi_(2)Te_(2.79)Se_(0.21)I_(0.004)(Bi_(2)(Te,Se)_(3),BTS)system with light Zn doping,revealing that Zn addition simultaneously enhances the Seebeck coefficient(S)and electrical conductivity(σ)through the modulation of defect composition and multi-level band regulation.The substitution of Zn atoms at Bi sites enhances S via bandgap(E_(g))widening,band flattening,and band splitting effects,contributing to a competitive power factor(PF)of∼60μW⋅cm^(−1)⋅K^(−2).Additionally,thermal conductivity is maintained at a low level,leading to an extraordinary figure-of-merit(ZT)value of∼1.3 at room temperature.Furthermore,the Bi_(2)Zn_(0.01)Te_(2.79)Se_(0.21)I_(0.004) system demonstrates impressive thermoelectric device performance,with a maximum cooling temperature difference(ΔT_(max))of∼70.0 K at 300 K,rising to∼78.0 K at 323 K and∼85.7 K at 343 K,as well as a maximum conversion efficiency(η_(max))of∼6.2%under aΔT of 200 K.This study clarifies the mechanism of Zn doping and presents a cost-effective strategy for enhancing the performance of n-type BTS thermoelectrics and their devices.展开更多
Advanced adiabatic compressed air energy storage(AA-CAES),with its dual capability for electricity-heat cogeneration and energy storage,offers significant potential as an energy hub for integrated electricity and heat...Advanced adiabatic compressed air energy storage(AA-CAES),with its dual capability for electricity-heat cogeneration and energy storage,offers significant potential as an energy hub for integrated electricity and heat systems(IEHS).While synergies in the electricity-heat market are known to enhance economic efficiency,it is hard to achieve cooperative operation due to the inherent differences among participants of IEHS and the absence of an incentive-compatible mechanism.To address this challenge,this paper proposes a Nash bargaining-based cooperative operation strategy for IEHS with AA-CAES.First,a cooperative alliance framework based on the Nash bargaining is proposed to optimize energy trading.Second,to overcome computational complexity,the non-convex,nonlinear Nash bargaining problem is decomposed into a two-stage optimization approach.In the first stage,a joint planning model maximizes the total profit of the alliance,determining the optimal energy interaction for each participant.In the second stage,a subsequent model ensures fair profit distribution by optimizing pricing and benefit-sharing mechanisms.Subsequently,a distributed solution strategy based on the self-adaptive alternating direction method of multipliers is utilized to preserve operator privacy and improve computational efficiency.Finally,case studies demonstrate that within the electricity-heat co-supply mode,the daily profit of AA-CAES can improve by approximately 4137.45 CNY.Meanwhile,through the proposed cooperative strategy,participants in the IEHS can obtain greater profits,which validates the effectiveness of this strategy.展开更多
Neuromuscular electrical stimulation(NMES)is a well-established therapeutic approach for chronic wounds.Conventionally,NMES involves direct electrode contact with wounds or adjacent healthy skin;however,it is limited ...Neuromuscular electrical stimulation(NMES)is a well-established therapeutic approach for chronic wounds.Conventionally,NMES involves direct electrode contact with wounds or adjacent healthy skin;however,it is limited by the need for wound exposure and by increased pain.Our preliminary study demonstrated the innovative application of remote NMES(rNMES)to the skeletal muscle of the distal calf,which showed the potential to accelerate wound healing in remote areas.rNMES was effective in human clinical trials in our previous work,although the underlying mechanisms remain unclear.As rNMES is often used to stimulate muscle contraction in long-term bedridden patients,we analyzed data from the Gene Expression Omnibus(GEO)database and found that exercise promotes midkine(MDK)expression in muscle.MDK is a small secreted heparin-binding protein that interacts with multiple cell surface receptors to promote growth.In the present study,we found that MDK significantly enhanced macrophage efferocytosis in a low-density lipoprotein receptor-related protein 1(LRP1)-dependent manner.Our findings demonstrate that rNMES upregulates MDK expression in skeletal muscles through the AMPK-ERK axis,facilitating its delivery to wounds through the circulatory system and promoting LRP1-mediated efferocytosis of apoptotic cells,thereby expediting wound healing.展开更多
Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,const...Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,constructing a plasmonic ZnIn_(2)S_(4-x)MoO_(3-x)(ZIS/MO)S-scheme heterojunction where oxygen and sulfur vacancies synergistically reconfigure charge transfer dynamics via dual-path modulation.Uniquely,sulfur vacancies amplify the built-in electric field(IEF)intensity by enlarging the Fermi level gap,while oxygen and sulfur dual-vacancies induce localized surface plasmon resonance(LSPR)via free-carrier concentration enhancement.Simultaneously,sulfur vacancies lower the H^(*)adsorption barrier,and dual vacancies amplify photothermal conversion by promoting nonradiative decay,accelerating temperature elevation and kinetics.Electron dynamics confirm that this dual-vacancy synergy prolongs charge carrier lifetime by a factor of 5.23.Consequently,the optimized sulfur vacancy-rich ZnIn_(2)S_(4-x)/MoO_(3-x)(R-ZIS/MO)exhibits remarkable photocatalytic hydrogen production rates of 3.60 mmol g^(-1) h^(-1)under visible light and 22.74 mmol g^(-1) h^(-1) under full-spectrum irradiation,representing 7.8-fold and17.2-fold enhancements,respectively.This study establishes a new paradigm.Targeted dual-vacancy coordination in plasmonic heterostructures enables unprecedented IEF-LSPR co-modulation,opening avenues for high-efficiency solar energy conversion.展开更多
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
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。
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
Ride-hailing electric vehicles are mobile resources with dispatch potential to improve resilience.However,they have not been well investigated because their charging and order-serving are affected or managed by the po...Ride-hailing electric vehicles are mobile resources with dispatch potential to improve resilience.However,they have not been well investigated because their charging and order-serving are affected or managed by the power grid dispatching center and the ride-hailing platform.Effective pre-strategies can improve the prevention ability for high-impact and low-probability(HILP)events and provide the foundation for measures in the response and restoration stages.First,this paper proposes a resilience reserve to expand the existing research on power system resilience.Secondly,this paper puts forward an interactive method of deep reinforcement learning,which considers the interests of both the power grid dispatching center and the ride-hailing platform.It improves the resilience reserve by achieving the order dispatch,orderly charging management of ride-hailing electric vehicles,and the pricing strategy of charging stations.Finally,this paper uses a practical example covering about 107.32 km2 in the center of Chengdu to verify that the proposed method improves the resilience reserve of the power system without obviously damaging the interests of the ride-hailing platform.展开更多
The demand for extended electric vehicle(EV)range necessitates advanced lightweighting strategies.This study introduces a materials genome approach,augmented by machine learning(ML),for optimizing lightweight composit...The demand for extended electric vehicle(EV)range necessitates advanced lightweighting strategies.This study introduces a materials genome approach,augmented by machine learning(ML),for optimizing lightweight composite designs for EVs.A comprehensive materials genome database was developed,encompassing composites based on carbon,glass,and natural fibers.This database systematically records critical parameters such as mechanical properties,density,cost,and environmental impact.Machine learning models,including Random Forest,Support Vector Machines,and Artificial Neural Networks,were employed to construct a predictive system for material performance.Subsequent material composition optimization was performed using amulti-objective genetic algorithm.Experimental validation demonstrated that an optimized carbon fiber/bio-based resin composite achieved a 45%weight reduction compared to conventional steel,while maintaining equivalent structural strength.The predictive accuracy of the models reached 94.2%.A cost-benefit analysis indicated that despite a 15%increase in material cost,the overall vehicle energy consumption decreased by 12%,leading to an 18%total cost saving over a five-year operational lifecycle,under a representative mid-size battery electric vehicle(BEV)operational scenario.展开更多
The J55 tubing thread fastener in an electric pump well experienced corrosion failure.The causes of the failure were investigated through physical and chemical property tests,corrosion product analysis,and microbial a...The J55 tubing thread fastener in an electric pump well experienced corrosion failure.The causes of the failure were investigated through physical and chemical property tests,corrosion product analysis,and microbial analysis.The results show that the metallographic structure and composition of the J55 tubing were normal.CO 2 corrosion was not the main cause of the thread fastener failure.The actual cause of the corrosion failure was microbiological corrosion,such as sulfate-reducing bacteria,thiosulfate-reducing bacteria,and iron-oxidizing bacteria.展开更多
Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strate...Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.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
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 Science Foundation of China(No.82272491)。
文摘The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being prominent examples.Consequently,promoting bone regeneration is a crucial medical challenge that demands immediate attention.As early as the mid-20th century,researchers revealed that electrical stimulation could effectively promote the healing and regeneration of bone tissue.This is achieved by mimicking the endogenous electric field within bone tissue,which influences cellular behavior and molecular mechanisms.In recent years,electroactive hydrogels responsive to electric field stimulation have been developed and applied to regulate cell functions at different stages of bone regeneration.This paper elaborates on the regulatory effects of electrical stimulation on MSCs,macrophages,and vascular endothelial cells during the process of bone regeneration.It also involves the activation of relevant ion channels and signaling pathways.Subsequently,it comprehensively reviews various electric-field-responsive hydrogels developed in recent years,covering aspects such as material selection,preparation methods,characteristics,and their applications in bone regeneration.Ultimately,it provides an objective summary of the existing deficiencies in hydrogel materials and research,and looks ahead to future development directions.
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Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating current(AC)(direct current(DC))voltage control.In fact,faster and more stable active and reactive power in the presence of frequency and voltage sags and swells is needed.Power electronics-controlled variable speed generators do not have enough energy storage(inertia)for the scope(static synchronous compensators(STATCOMs)included).This is because power electronics tends to decouple the generator from the power system.While virtual inertia control in doubly fed induction generators(DFIGs)offers a partial solution to these problems,a more robust and comprehensive framework is required for advanced grid support.This is how,by extending the dual-excitation principles,the dualaxis excited electric synchronous generators(DE-SG)provide superior flexibility in two variants summarized here:as a multifunctional DFIG and dual-axis vs.single-axis excited synchronous generator(SG),and as a synchronous condenser(SC),with dual DC and AC excitation(as a no-load DFIG with inertia wheel),where variable speed is used to accelerate/decelerate the SC and thus provide additional assistance in frequency stabilization.These solutions,good for short-time transients,are not meant,however,to replace the large bidirectional energy storage systems(pump-hydro,hydrogen,batteries,etc.)which are crucial for the daily inherent variations of output energy in modern power systems with multiple power sources.The present paper offers a summary of techniques used in the dual-axis excited vs.single-axis excited SGs(SE-SGs),and SCs topologies,modeling,and control for better stability in modern multiple-source energy systems.This survey includes multiple case studies to shed light on prominent methods.
基金supported by the National Key Research and Development Program of China (Grant No.2024YFA1210400)the National Science Fund for Distinguished Young Scholars (Grant No.52525101)+3 种基金the National Natural Science Foundation of China (Grant Nos.52450001 and 22409014)the International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No.52411540237)the Tencent Xplorer Prizethe support of the National High-Level Talent Special Support Programs—Young Talents。
文摘The interdependence of electrical parameters has long inhibited the progress of bismuth telluride(Bi_(2)Te3),limiting its widespread application in thermoelectric cooling and power generation.This work investigates the n-type Bi_(2)Te_(2.79)Se_(0.21)I_(0.004)(Bi_(2)(Te,Se)_(3),BTS)system with light Zn doping,revealing that Zn addition simultaneously enhances the Seebeck coefficient(S)and electrical conductivity(σ)through the modulation of defect composition and multi-level band regulation.The substitution of Zn atoms at Bi sites enhances S via bandgap(E_(g))widening,band flattening,and band splitting effects,contributing to a competitive power factor(PF)of∼60μW⋅cm^(−1)⋅K^(−2).Additionally,thermal conductivity is maintained at a low level,leading to an extraordinary figure-of-merit(ZT)value of∼1.3 at room temperature.Furthermore,the Bi_(2)Zn_(0.01)Te_(2.79)Se_(0.21)I_(0.004) system demonstrates impressive thermoelectric device performance,with a maximum cooling temperature difference(ΔT_(max))of∼70.0 K at 300 K,rising to∼78.0 K at 323 K and∼85.7 K at 343 K,as well as a maximum conversion efficiency(η_(max))of∼6.2%under aΔT of 200 K.This study clarifies the mechanism of Zn doping and presents a cost-effective strategy for enhancing the performance of n-type BTS thermoelectrics and their devices.
基金supported in part by the National Natural Science Foundation of China(No.52407115)State Key Laboratory of Power System Operation and Control(61011000223).
文摘Advanced adiabatic compressed air energy storage(AA-CAES),with its dual capability for electricity-heat cogeneration and energy storage,offers significant potential as an energy hub for integrated electricity and heat systems(IEHS).While synergies in the electricity-heat market are known to enhance economic efficiency,it is hard to achieve cooperative operation due to the inherent differences among participants of IEHS and the absence of an incentive-compatible mechanism.To address this challenge,this paper proposes a Nash bargaining-based cooperative operation strategy for IEHS with AA-CAES.First,a cooperative alliance framework based on the Nash bargaining is proposed to optimize energy trading.Second,to overcome computational complexity,the non-convex,nonlinear Nash bargaining problem is decomposed into a two-stage optimization approach.In the first stage,a joint planning model maximizes the total profit of the alliance,determining the optimal energy interaction for each participant.In the second stage,a subsequent model ensures fair profit distribution by optimizing pricing and benefit-sharing mechanisms.Subsequently,a distributed solution strategy based on the self-adaptive alternating direction method of multipliers is utilized to preserve operator privacy and improve computational efficiency.Finally,case studies demonstrate that within the electricity-heat co-supply mode,the daily profit of AA-CAES can improve by approximately 4137.45 CNY.Meanwhile,through the proposed cooperative strategy,participants in the IEHS can obtain greater profits,which validates the effectiveness of this strategy.
基金supported by the National Natural Science Foundation of China(Grant No.82271252 to W.L.,No.8217091029 to T.W.and No.82204542 to L.H.)the Key Medical Research Projects of Jiangsu Health and Health Commission(Grant No.K2023066 to L.Z.)the Taishan Industrial Talent Project(Grant No.2020-371722-73-03-097290 to W.L.).
文摘Neuromuscular electrical stimulation(NMES)is a well-established therapeutic approach for chronic wounds.Conventionally,NMES involves direct electrode contact with wounds or adjacent healthy skin;however,it is limited by the need for wound exposure and by increased pain.Our preliminary study demonstrated the innovative application of remote NMES(rNMES)to the skeletal muscle of the distal calf,which showed the potential to accelerate wound healing in remote areas.rNMES was effective in human clinical trials in our previous work,although the underlying mechanisms remain unclear.As rNMES is often used to stimulate muscle contraction in long-term bedridden patients,we analyzed data from the Gene Expression Omnibus(GEO)database and found that exercise promotes midkine(MDK)expression in muscle.MDK is a small secreted heparin-binding protein that interacts with multiple cell surface receptors to promote growth.In the present study,we found that MDK significantly enhanced macrophage efferocytosis in a low-density lipoprotein receptor-related protein 1(LRP1)-dependent manner.Our findings demonstrate that rNMES upregulates MDK expression in skeletal muscles through the AMPK-ERK axis,facilitating its delivery to wounds through the circulatory system and promoting LRP1-mediated efferocytosis of apoptotic cells,thereby expediting wound healing.
基金supported by the NSF of China(Nos.22579102 and 22405160)the Natural Science Foundation of Hubei Province(2024AFB288)+2 种基金the Natural Science Research Project of Yichang City(Grant A25-3-007)the 111 Project(D20015)the Key Project Foundation of Hubei Three Gorges Laboratory(SC250009)。
文摘Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,constructing a plasmonic ZnIn_(2)S_(4-x)MoO_(3-x)(ZIS/MO)S-scheme heterojunction where oxygen and sulfur vacancies synergistically reconfigure charge transfer dynamics via dual-path modulation.Uniquely,sulfur vacancies amplify the built-in electric field(IEF)intensity by enlarging the Fermi level gap,while oxygen and sulfur dual-vacancies induce localized surface plasmon resonance(LSPR)via free-carrier concentration enhancement.Simultaneously,sulfur vacancies lower the H^(*)adsorption barrier,and dual vacancies amplify photothermal conversion by promoting nonradiative decay,accelerating temperature elevation and kinetics.Electron dynamics confirm that this dual-vacancy synergy prolongs charge carrier lifetime by a factor of 5.23.Consequently,the optimized sulfur vacancy-rich ZnIn_(2)S_(4-x)/MoO_(3-x)(R-ZIS/MO)exhibits remarkable photocatalytic hydrogen production rates of 3.60 mmol g^(-1) h^(-1)under visible light and 22.74 mmol g^(-1) h^(-1) under full-spectrum irradiation,representing 7.8-fold and17.2-fold enhancements,respectively.This study establishes a new paradigm.Targeted dual-vacancy coordination in plasmonic heterostructures enables unprecedented IEF-LSPR co-modulation,opening avenues for high-efficiency solar energy conversion.
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.
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。
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.
文摘Ride-hailing electric vehicles are mobile resources with dispatch potential to improve resilience.However,they have not been well investigated because their charging and order-serving are affected or managed by the power grid dispatching center and the ride-hailing platform.Effective pre-strategies can improve the prevention ability for high-impact and low-probability(HILP)events and provide the foundation for measures in the response and restoration stages.First,this paper proposes a resilience reserve to expand the existing research on power system resilience.Secondly,this paper puts forward an interactive method of deep reinforcement learning,which considers the interests of both the power grid dispatching center and the ride-hailing platform.It improves the resilience reserve by achieving the order dispatch,orderly charging management of ride-hailing electric vehicles,and the pricing strategy of charging stations.Finally,this paper uses a practical example covering about 107.32 km2 in the center of Chengdu to verify that the proposed method improves the resilience reserve of the power system without obviously damaging the interests of the ride-hailing platform.
文摘The demand for extended electric vehicle(EV)range necessitates advanced lightweighting strategies.This study introduces a materials genome approach,augmented by machine learning(ML),for optimizing lightweight composite designs for EVs.A comprehensive materials genome database was developed,encompassing composites based on carbon,glass,and natural fibers.This database systematically records critical parameters such as mechanical properties,density,cost,and environmental impact.Machine learning models,including Random Forest,Support Vector Machines,and Artificial Neural Networks,were employed to construct a predictive system for material performance.Subsequent material composition optimization was performed using amulti-objective genetic algorithm.Experimental validation demonstrated that an optimized carbon fiber/bio-based resin composite achieved a 45%weight reduction compared to conventional steel,while maintaining equivalent structural strength.The predictive accuracy of the models reached 94.2%.A cost-benefit analysis indicated that despite a 15%increase in material cost,the overall vehicle energy consumption decreased by 12%,leading to an 18%total cost saving over a five-year operational lifecycle,under a representative mid-size battery electric vehicle(BEV)operational scenario.
文摘The J55 tubing thread fastener in an electric pump well experienced corrosion failure.The causes of the failure were investigated through physical and chemical property tests,corrosion product analysis,and microbial analysis.The results show that the metallographic structure and composition of the J55 tubing were normal.CO 2 corrosion was not the main cause of the thread fastener failure.The actual cause of the corrosion failure was microbiological corrosion,such as sulfate-reducing bacteria,thiosulfate-reducing bacteria,and iron-oxidizing bacteria.
基金sponsored in part by the National Natural Science Foundation of China(52167014)in part by the Science and Technology Commission of Shanghai Municipality(23XD1422000,23QB1400500).
文摘Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.
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.
