Freak wave simulation based on nonlinear model and the research on the time-frequency energy spectrum of simulation results

VOF （volume of fluid） method has been used to make the numerical simulation of freak wave come true. The comparisons between the numerical results and linear theoretical results corresponding to Eq.（5） have been carried out to show that the numerical results have a better exhibition of nonlinear characteristics. Wavelet analysis method has been adopted to investigate the time-frequency energy spectrum of simulation freak waves and the results reveal strong nonlinear interaction enables energy to be transferred to high harmonics during the progress of its formation. Varying water depth can enhance the nonlinear interaction, making much more energy be transferred to high harmonics and freak waves with higher asymmetry be generated.

The Time-Frequency Energy Attenuation Factor and Its Application on the Basis of Gauss Linear Frequency-Modulated Continuous Wavelet Transform

Based on the Gauss linear frequency modulated wavelet transform, a new characteristic index is presented, namely time frequency energy attenuation factor which can reflect the difference features of waveform in earthquake focus mechanism, wave traveling path and its attenuation characteristics in focal area or near field. In order to test its validity, we select the natural earthquakes and explosion or collapse events whose focus mechanisms vary obviously,and some natural earthquakes located at the same site or in a very small area. The study indicates that the time frequency energy attenuation factors of the natural earthquakes are obviously different with that of explosion or collapse events, and the change of the time frequency energy attenuation factors is relatively stable for the earthquakes under the normal seismicity background. Using the above mentioned method, it is expected to offer a useful criterion for strong earthquake prediction by continuous earthquake observation.

The W transform and its improved methods for time-frequency analysis of seismic data

The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

Investigating and predicting the role of photovoltaic, wind, and hydrogen energies in sustainable global energy evolution

The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil fuels.This review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and hydrogen.This transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic development.The transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community impact.The environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological footprint.This study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero emissions.By 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and India.These developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy solutions.This review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.

Heavy ion energy influence on multiple-cell upsets in small sensitive volumes:from standard to high energies

The 28 nm process has a high cost-performance ratio and has gradually become the standard for the field of radiation-hardened devices.However,owing to the minimum physical gate length of only 35 nm,the physical area of a standard 6T SRAM unit is approximately 0.16μm^(2),resulting in a significant enhancement of multi-cell charge-sharing effects.Multiple-cell upsets(MCUs)have become the primary physical mechanism behind single-event upsets(SEUs)in advanced nanometer node devices.The range of ionization track effects increases with higher ion energies,and spacecraft in orbit primarily experience SEUs caused by high-energy ions.However,ground accelerator experiments have mainly obtained low-energy ion irradiation data.Therefore,the impact of ion energy on the SEU cross section,charge collection mechanisms,and MCU patterns and quantities in advanced nanometer devices remains unclear.In this study,based on the experimental platform of the Heavy Ion Research Facility in Lanzhou,low-and high-energy heavy-ion beams were used to study the SEUs of 28 nm SRAM devices.The influence of ion energy on the charge collection processes of small-sensitive-volume devices,MCU patterns,and upset cross sections was obtained,and the applicable range of the inverse cosine law was clarified.The findings of this study are an important guide for the accurate evaluation of SEUs in advanced nanometer devices and for the development of radiation-hardening techniques.

2024 Adult Compendium of Physical Activities:A third update of the energy costs of human activities

Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Older Adult Compendium of Physical Activities:Energy costs of human activities in adults aged 60 and older

Purpose:To describe the development of a Compendium for estimating the energy costs of activities in adults>60 years(OA Compendium).Methods:Physical activities(PAs)and their metabolic equivalent of task(MET)values were obtained from a systematic search of studies published in 4 sport and exercise databases(PubMed,Embase,SPORTDiscus(EBSCOhost),and Scopus)and a review of articles included in the 2011 Adult Compendium that measured PA in older adults.MET values were computed as the oxygen cost(VO_(2),mL/kg/min)during PA divided by 2.7 m L/kg/min(MET_(60+))to account for the lower resting metabolic rate in older adults.Results:We identified 68 articles and extracted energy expenditure data on 427 PAs.From these,we derived 99 unique Specific Activity codes with corresponding MET_(60+)values for older adults.We developed a website to present the OA Compendium MET_(60+)values:https://pacompendium.com.Conclusion:The OA Compendium uses data collected from adults>60 years for more accurate estimation of the energy cost of PAs in older adults.It is an accessible resource that will allow researchers,educators,and practitioners to find MET_(60+)values for older adults for use in PA research and practice.

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

A reliability-oriented genetic algorithm-levenberg marquardt model for leak risk assessment based on time-frequency features

Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses,a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents.The fast and accurate leak detection methods are essential for maintaining pipeline safety in pipeline reliability engineering.Current oil pipeline leakage signals are insufficient for feature extraction,while the training time for traditional leakage prediction models is too long.A new leak detection method is proposed based on time-frequency features and the Genetic Algorithm-Levenberg Marquardt(GA-LM)classification model for predicting the leakage status of oil pipelines.The signal that has been processed is transformed to the time and frequency domain,allowing full expression of the original signal.The traditional Back Propagation(BP)neural network is optimized by the Genetic Algorithm(GA)and Levenberg Marquardt(LM)algorithms.The results show that the recognition effect of a combined feature parameter is superior to that of a single feature parameter.The Accuracy,Precision,Recall,and F1score of the GA-LM model is 95%,93.5%,96.7%,and 95.1%,respectively,which proves that the GA-LM model has a good predictive effect and excellent stability for positive and negative samples.The proposed GA-LM model can obviously reduce training time and improve recognition efficiency.In addition,considering that a large number of samples are required for model training,a wavelet threshold method is proposed to generate sample data with higher reliability.The research results can provide an effective theoretical and technical reference for the leakage risk assessment of the actual oil pipelines.

Dynamics and vibration reduction performance of asymmetric tristable nonlinear energy sink

With its complex nonlinear dynamic behavior,the tristable system has shown excellent performance in areas such as energy harvesting and vibration suppression,and has attracted a lot of attention.In this paper,an asymmetric tristable design is proposed to improve the vibration suppression efficiency of nonlinear energy sinks(NESs)for the first time.The proposed asymmetric tristable NES(ATNES)is composed of a pair of oblique springs and a vertical spring.Then,the three stable states,symmetric and asymmetric,can be achieved by the adjustment of the distance and stiffness asymmetry of the oblique springs.The governing equations of a linear oscillator(LO)coupled with the ATNES are derived.The approximate analytical solution to the coupled system is obtained by the harmonic balance method(HBM)and verified numerically.The vibration suppression efficiency of three types of ATNES is compared.The results show that the asymmetric design can improve the efficiency of vibration reduction through comparing the chaotic motion of the NES oscillator between asymmetric steady states.In addition,compared with the symmetrical tristable NES(TNES),the ATNES can effectively control smaller structural vibrations.In other words,the ATNES can effectively solve the threshold problem of TNES failure to weak excitation.Therefore,this paper reveals the vibration reduction mechanism of the ATNES,and provides a pathway to expand the effective excitation amplitude range of the NES.

Moderate Fields, Maximum Potential: Achieving High Records with Temperature‑Stable Energy Storage in Lead‑Free BNT‑Based Ceramics

The increasing awareness of environmental concerns has prompted a surge in the exploration of leadfree,high-power ceramic capacitors.Ongoing efforts to develop leadfree dielectric ceramics with exceptional energystorage performance(ESP)have predominantly relied on multicomponent composite strategies,often accomplished under ultrahigh electric fields.However,this approach poses challenges in insulation and system downsizing due to the necessary working voltage under such conditions.Despite extensive study,bulk ceramics of(Bi_(0.5)Na_(0.5))TiO_(3)(BNT),a prominent lead-free dielectric ceramic family,have seldom achieved a recoverable energy-storage(ES)density(Wrec)exceeding 7 J cm^(−3).This study introduces a novel approach to attain ceramic capacitors with high ESP under moderate electric fields by regulating permittivity based on a linear dielectric model,enhancing insulation quality,and engineering domain structures through chemical formula optimization.The incorporation of SrTiO_(3)(ST)into the BNT matrix is revealed to reduce the dielectric constant,while the addition of Bi(Mg_(2/3)Nb_(1/3))O_(3)(BMN)aids in maintaining polarization.Additionally,the study elucidates the methodology to achieve high ESP at moderate electric fields ranging from 300 to 500 kV cm^(−1).In our optimized composition,0.5(Bi_(0.5)Na_(0.4)K_(0.1))TiO_(3)–0.5(2/3ST-1/3BMN)(B-0.5SB)ceramics,we achieved a Wrec of 7.19 J cm^(−3) with an efficiency of 93.8%at 460 kV cm^(−1).Impressively,the B-0.5SB ceramics exhibit remarkable thermal stability between 30 and 140℃ under 365 kV cm^(−1),maintaining a Wrec exceeding 5 J cm^(−3).This study not only establishes the B-0.5SB ceramics as promising candidates for ES materials but also demonstrates the feasibility of optimizing ESP by modifying the dielectric constant under specific electric field conditions.Simultaneously,it provides valuable insights for the future design of ceramic capacitors with high ESP under constraints of limited electric field.

Development status and prospect of underground thermal energy storage technology

Underground Thermal Energy Storage(UTES)store unstable and non-continuous energy underground,releasing stable heat energy on demand.This effectively improve energy utilization and optimize energy allocation.As UTES technology advances,accommodating greater depth,higher temperature and multi-energy complementarity,new research challenges emerge.This paper comprehensively provides a systematic summary of the current research status of UTES.It categorized different types of UTES systems,analyzes the applicability of key technologies of UTES,and evaluate their economic and environmental benefits.Moreover,this paper identifies existing issues with UTES,such as injection blockage,wellbore scaling and corrosion,seepage and heat transfer in cracks,etc.It suggests deepening the research on blockage formation mechanism and plugging prevention technology,improving the study of anticorrosive materials and water treatment technology,and enhancing the investigation of reservoir fracture network characterization technology and seepage heat transfer.These recommendations serve as valuable references for promoting the high-quality development of UTES.

Nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in aerospace community:a comparative analysis

The aerospace community widely uses difficult-to-cut materials,such as titanium alloys,high-temperature alloys,metal/ceramic/polymer matrix composites,hard and brittle materials,and geometrically complex components,such as thin-walled structures,microchannels,and complex surfaces.Mechanical machining is the main material removal process for the vast majority of aerospace components.However,many problems exist,including severe and rapid tool wear,low machining efficiency,and poor surface integrity.Nontraditional energy-assisted mechanical machining is a hybrid process that uses nontraditional energies(vibration,laser,electricity,etc)to improve the machinability of local materials and decrease the burden of mechanical machining.This provides a feasible and promising method to improve the material removal rate and surface quality,reduce process forces,and prolong tool life.However,systematic reviews of this technology are lacking with respect to the current research status and development direction.This paper reviews the recent progress in the nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in the aerospace community.In addition,this paper focuses on the processing principles,material responses under nontraditional energy,resultant forces and temperatures,material removal mechanisms,and applications of these processes,including vibration-,laser-,electric-,magnetic-,chemical-,advanced coolant-,and hybrid nontraditional energy-assisted mechanical machining.Finally,a comprehensive summary of the principles,advantages,and limitations of each hybrid process is provided,and future perspectives on forward design,device development,and sustainability of nontraditional energy-assisted mechanical machining processes are discussed.

An ionic liquid-assisted strategy for enhanced anticorrosion of low-energy PEO coatings on magnesium–lithium alloy

A low-energy plasma electrolytic oxidation(LePEO)technique is developed to simultaneously improve energy efficiency and anti-corrosion.Ionic liquids(1-butyl-3-methylimidazole tetrafluoroborate(BmimBF_(4)))as sustainable corrosion inhibitors are chosen to investigate the corrosion inhibition behavior of ionic liquid(ILs)during the LePEO process for LA91 magnesium-lithium(Mg-Li)alloy.Results show that the ionic liquid BmimBF_(4)participates in the LePEO coating formation process,causing an increment in coating thickness and surface roughness.The low conductivity of the ionic liquid is responsible for the voltage and breakdown voltage increases during the LePEO with IL process(LePEO-IL).After adding BmimBF_(4),corrosion current density decreases from 1.159×10^(−4)A·cm^(−2)to 8.143×10^(−6)A·cm^(−2).The impedance modulus increases to 1.048×10^(4)Ω·cm^(−2)and neutral salt spray remains intact for 24 h.The superior corrosion resistance of the LePEO coating assisted by ionic liquid could be mainly attributed to its compact and thick barrier layer and physical absorption of ionic liquid.The ionic liquid-assisted LePEO technique provides a promising approach to reducing energy consumption and improving film performance.

A game-theoretic approach for federated learning:A trade-off among privacy,accuracy and energy

Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become possible.Distributed devices not only provide adequate training data,but also cause privacy leakage and energy consumption.How to optimize the energy consumption in distributed communication systems,while ensuring the privacy of users and model accuracy,has become an urgent challenge.In this paper,we define the FL as a 3-layer architecture including users,agents and server.In order to find a balance among model training accuracy,privacy-preserving effect,and energy consumption,we design the training process of FL as game models.We use an extensive game tree to analyze the key elements that influence the players’decisions in the single game,and then find the incentive mechanism that meet the social norms through the repeated game.The experimental results show that the Nash equilibrium we obtained satisfies the laws of reality,and the proposed incentive mechanism can also promote users to submit high-quality data in FL.Following the multiple rounds of play,the incentive mechanism can help all players find the optimal strategies for energy,privacy,and accuracy of FL in distributed communication systems.

Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics

The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper.

Enhanced High-Temperature Energy Storage Performance of All-Organic Composite Dielectric via Constructing Fiber-Re in forced Structure

Optimizing the high-temperature energy storage characteristics of energy storage dielectrics is of great significance for the development of pulsed power devices and power control systems.Selecting a polymer with a higher glass transition temperature(T_(g))as the matrix is one of the effective ways to increase the upper limit of the polymer operating temperature.However,current high-T_(g)polymers have limitations,and it is difficult to meet the demand for high-temperature energy storage dielectrics with only one polymer.For example,polyetherimide has high-energy storage efficiency,but low breakdown strength at high temperatures.Polyimide has high corona resistance,but low high-temperature energy storage efficiency.In this work,combining the advantages of two polymer,a novel high-T_(g)polymer fiber-reinforced microstructure is designed.Polyimide is designed as extremely fine fibers distributed in the composite dielectric,which will facilitate the reduction of high-temperature conductivity loss for polyimide.At the same time,due to the high-temperature resistance and corona resistance of polyimide,the high-temperature breakdown strength of the composite dielectric is enhanced.After the polyimide content with the best high-temperature energy storage characteristics is determined,molecular semiconductors(ITIC)are blended into the polyimide fibers to further improve the high-temperature efficiency.Ultimately,excellent high-temperature energy storage properties are obtained.The 0.25 vol%ITIC-polyimide/polyetherimide composite exhibits high-energy density and high discharge efficiency at 150℃(2.9 J cm^(-3),90%)and 180℃(2.16 J cm^(-3),90%).This work provides a scalable design idea for high-performance all-organic high-temperature energy storage dielectrics.

Reinforcing effects of polypropylene on energy absorption and fracturing of cement-based tailings backfill under impact loading

Polypropylene(PP)fiber-reinforced cement-based tailings backfill(FRCTB)is a green compound material with superior crack resistance and has good prospects for application in underground mining.However,FRCTB exhibits susceptibility to dynamic events,such as impact ground pressure and blast vibrations.This paper investigates the energy and crack distribution behavior of FRCTB under dynamic impact,considering the height/diameter(H/D)effect.Split Hopkinson pressure bar,industrial computed tomography scan,and scanning electron microscopy(SEM)experiments were carried out on six types of FRCTB.Laboratory outcomes confirmed fiber aggregation at the bottom of specimens.When H/D was less than 0.8,the proportion of PP fibers distributed along theθangle direction of80°-90°increased.For the total energy,all samples presented similar energy absorption,reflectance,and transmittance.However,a rise in H/D may cause a rise in the energy absorption rate of FRCTB during the peak phase.A positive correlation existed between the average strain rate and absorbed energy per unit volume.The increase in H/D resulted in a decreased crack volume fraction of FRCTB.When the H/D was greater than or equal to 0.7,the maximum crack volume fraction of FRCTB was observed close to the incidence plane.Radial cracks were present only in the FRCTB with an H/D ratio of 0.5.Samples with H/D ratios of 0.5 and 0.6 showed similar distributions of weakly and heavily damaged areas.PP fibers can limit the emergence and expansion of cracks by influencing their path.SEM observations revealed considerable differences in the bonding strengths between fibers and the FRCTB.Fibers that adhered particularly well to the substrate were attracted together with the hydration products adhering to surfaces.These results show that FRCTB is promising as a sustainable and green backfill for determining the design properties of mining with backfill.

Significantly Improved High-Temperature Energy Storage Performance of BOPP Films by Coating Nanoscale Inorganic Layer

Biaxially oriented polypropylene(BOPP)is one of the most commonly used commercial capacitor films,but its upper operating temperature is below 105℃due to the sharply increased electrical conduction loss at high temperature.In this study,growing an inorganic nanoscale coating layer onto the BOPP film's surface is proposed to suppress electrical conduction loss at high temperature,as well as increase its upper operating temperature.Four kinds of inorganic coating layers that have different energy band structure and dielectric property are grown onto the both surface of BOPP films,respectively.The effect of inorganic coating layer on the high-temperature energy storage performance has been systematically investigated.The favorable coating layer materials and appropriate thickness enable the BOPP films to have a significant improvement in high-temperature energy storage performance.Specifically,when the aluminum nitride(AIN)acts as a coating layer,the AIN-BOPP-AIN sandwich-structured films possess a discharged energy density of 1.5 J cm^(-3)with an efficiency of 90%at 125℃,accompanying an outstandingly cyclic property.Both the discharged energy density and operation temperature are significantly enhanced,indicating that this efficient and facile method provides an important reference to improve the high-temperature energy storage performance of polymer-based dielectric films.