A test study on 50% lightning impulse breakdown voltage in two-phase mixture of gas and solid particles has been carried out in a specially designed discharge cabinet. A mechanical sieve is set up for sifting differen...A test study on 50% lightning impulse breakdown voltage in two-phase mixture of gas and solid particles has been carried out in a specially designed discharge cabinet. A mechanical sieve is set up for sifting different solid particles into the discharge space uniformly. The lightning impulse voltage according with international electro-technical commission （IEC） standard is applied to the electrodes inside the discharge cabinet by the rule of up-down method in a total of 40 times. The results showed that the 50% lightning impulse breakdown voltage in two-phase mixture of gas and solid particles has its own features and is much different from that in air.展开更多
Based on 0.13μm complementary metal-oxide-semiconductor（CMOS） technology,a phase and frequency detector（PFD） is designed with a low supply voltage of 0.5V for frequency synthesizers used in wireless sensor netwo...Based on 0.13μm complementary metal-oxide-semiconductor（CMOS） technology,a phase and frequency detector（PFD） is designed with a low supply voltage of 0.5V for frequency synthesizers used in wireless sensor networks（WSNs）.The PFD can compare the frequency and phase differences of input signals and deliver a signal voltage proportional to the difference.Low threshold transistors are used in the circuits since a power supply of 0.5V is adopted.A pulse latched structure is also used in the circuits in order to increase both the detection range of phase errors and the maximum operation frequency.In experiments,a phase error with a range from-358° to 358° is measured when the input signal frequency is 2MHz.The PFD has a faster acquisition speed compared with conventional digital PFDs.When the input signals are at a frequency of 2MHz with zero phase error,the circuits have a power consumption of 1.8[KG＊8]μW,and the maximum operation frequency is 1.25GHz.展开更多
The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the exis...The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution network.Firstly,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are established.Additionally,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the EVcharger.Amultiobjective optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy consumption.Then,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time scales.Themulti-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control optimization.Simulation results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution network.It effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.展开更多
The integration of renewable energy sources(RESs)with inverter interfaces has fundamentally reshaped power system dynamics,challenging traditional stability analysis frameworks designed for synchronous generator-domin...The integration of renewable energy sources(RESs)with inverter interfaces has fundamentally reshaped power system dynamics,challenging traditional stability analysis frameworks designed for synchronous generator-dominated grids.Conventional classifica-tions,which decouple voltage,frequency,and rotor angle stability,fail to address the emerging strong voltage‒angle coupling effects caused by RES dynamics.This coupling introduces complex oscillation modes and undermines system robustness,neces-sitating novel stability assessment tools.Recent studies focus on eigenvalue distributions and damping redistribution but lack quantitative criteria and interpretative clarity for coupled stability.This work proposes a transient energy-based framework to resolve these gaps.By decomposing transient energy into subsystem-dissipated components and coupling-induced energy exchange,the method establishes stability criteria compatible with a broad variety of inverter-interfaced devices while offering an intuitive energy-based interpretation for engineers.The coupling strength is also quantified by defining the relative coupling strength index,which is directly related to the transient energy interpretation of the coupled stability.Angle‒voltage coupling may induce instability by injecting transient energy into the system,even if the individual phase angle and voltage dynamics themselves are stable.The main contributions include a systematic stability evaluation framework and an energy decomposition approach that bridges theoretical analysis with practical applicability,addressing the urgent need for tools for managing modern power system evolving stability challenges.展开更多
Lithium-rich materials possess the ultra-high specific capacity,but the redox of oxygen is not completely reversible,resulting in voltage attenuation and structural instability.A stepwise co-precipitation method is us...Lithium-rich materials possess the ultra-high specific capacity,but the redox of oxygen is not completely reversible,resulting in voltage attenuation and structural instability.A stepwise co-precipitation method is used for the first time in this paper to achieve the control of the two-phase distribution through controlling the distribution of transition metal elements and realize the modification of particle surface structure without the aid of heterologous ions.The results of characterization tests show that the content of LiMO_(2) phase inside the particles and the content of Li_(2)MnO_(3) phase on the surface of the particles are successfully increased,and the surface induced formation of Li_(4)Mn_(5)O_(12) spinel phase or some disorderly ternary.The electrochemical performance of the modified sample is as follows:LR(pristine)shows specific discharge capacity of 72.7 mA·h·g^(−1)after 500 cycles at 1 C,while GR(modified sample)shows specific discharge capacity of 137.5 mA·h·g^(−1) at 1 C,and the discharge mid-voltage of GR still remains above 3 V when cycling to 220 cycles at 1 C(mid-voltage of LR remains above 3 V when cycling to 160 cycles at 1 C).Therefore,deliberately regulating the local state of the two phases is a successful way to reinforced the material structure and inhibition the voltage attenuation.展开更多
Low-voltage distribution systems in our country are mostly used in agricultural loads and household loads. The value and using time of these kinds of loads are uncontrollable, which lead to the three-phase imbalance i...Low-voltage distribution systems in our country are mostly used in agricultural loads and household loads. The value and using time of these kinds of loads are uncontrollable, which lead to the three-phase imbalance in low-voltage distribution system, and seriously affect the quality of power supply. A new type of the commutation system and an improved quantum genetic algorithm (IQGA) are proposed in the paper. At last, the rationality and the efficiency of the method are verified by a practical example.展开更多
Passive microseismic monitoring(PMM)serves as a fundamental technology for assessing hydraulic fracturing(HF)effectiveness,with a key focus on accurate and efficient phase detection/arrival picking and source location...Passive microseismic monitoring(PMM)serves as a fundamental technology for assessing hydraulic fracturing(HF)effectiveness,with a key focus on accurate and efficient phase detection/arrival picking and source location.In PMM data processing,the data-driven paradigm(deep learning based)outperforms the model-driven paradigm in characteristic extraction but lacks quality control and uncertainty quantification.Monte Carlo Dropout,a Bayesian uncertainty quantification technique,performs stochastic neuron deactivation through multiple forward propagation samplings.Therefore,this study proposes a deep learning neural network incorporating uncertainty quantification with manual quality control integration,establishing an optimized workflow spanning automated phase detection to robust source location.The methodology implementation comprises two principal components:(1)The MDNet employing Monte Carlo Dropout strategy enabling simultaneous phase detection/arrival picking and unce rtainty estimation;(2)an integrated hybrid-driven workflow with a traveltime-based inve rsion method for source location.Validation with field data demonstrates that MD-Net achieves superior performance under low signal-to-noise ratio conditions,maintaining detection accuracy exceeding 99%for both P-and S-waves.The phase arrival picking precision shows significant improvement,with a 40%reduction in standard deviation compared to the baseline model(P-S time difference decreasing from12.0 ms to 7.1 ms),while providing quantifiable uncertainty metrics for manual calibration.Source location results further reveal that our hybrid-driven workflow produces more physically plausible event distributions,with 100%of microseismic eve nts clustering along the primary fracture expanding direction.This performance surpasses traditional cross-correlation methods and single/multi-trace data-driven me thods in spatial rationality.This study establishes an inte rpretable,high-pre cision automated framework for HF-PMM applications,demonstrating potential for extension to diverse geological settings and monitoring configurations.展开更多
It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament ch...It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.展开更多
It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the ...It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.展开更多
Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scali...Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.展开更多
Modeling the dynamics of flapping wing aerial vehicle is challenging due to the complexity of aerodynamic effects and mechanical structures.The aim of this work is to develop an accurate dynamics model of flapping win...Modeling the dynamics of flapping wing aerial vehicle is challenging due to the complexity of aerodynamic effects and mechanical structures.The aim of this work is to develop an accurate dynamics model of flapping wing aerial vehicle based on real flight data.We propose a modeling framework that combines rigid body dynamics with a neural network to predict aerodynamic effects.By incorporating the concept of flapping phase,we significantly enhance the network’s ability to analyze transient aerodynamic behavior.We design and utilize a phase-functioned neural network structure for aerodynamic predictions and train the network using real flight data.Evaluation results show that the network can predict aerodynamic effects and demonstrate clear physical significance.We verify that the framework can be used for dynamic propagation and is expected to be utilized for building simulators for flapping wing aerial vehicles.展开更多
Photonic computing has emerged as a promising technology for the ever-increasing computational demands of machine learning and artificial intelligence.Due to the advantages in computing speed,integrated photonic chips...Photonic computing has emerged as a promising technology for the ever-increasing computational demands of machine learning and artificial intelligence.Due to the advantages in computing speed,integrated photonic chips have attracted wide research attention on performing convolutional neural network algorithm.Programmable photonic chips are vital for achieving practical applications of photonic computing.Herein,a programmable photonic chip based on ultrafast laser-induced phase change is fabricated for photonic computing.Through designing the ultrafast laser pulses,the Sb film integrated into photonic waveguides can be reversibly switched between crystalline and amorphous phase,resulting in a large contrast in refractive index and extinction coefficient.As a consequence,the light transmission of waveguides can be switched between write and erase states.To determine the phase change time,the transient laser-induced phase change dynamics of Sb film are revealed at atomic scale,and the time-resolved transient reflectivity is measured.Based on the integrated photonic chip,photonic convolutional neural networks are built to implement machine learning algorithm,and images recognition task is achieved.This work paves a route for fabricating programmable photonic chips by designed ultrafast laser,which will facilitate the application of photonic computing in artificial intelligence.展开更多
As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,par...As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,particularly when addressing high-dimensional and complex data in multicomponent systems.To overcome these challenges,this study proposes an innovative model,LSGWO-BP,which integrates an improved Grey Wolf Optimizer(GWO)with a backpropagation neural network(BP)to enhance the accuracy and efficiency of quasi-phase equilibrium predictions within the KKS phase-field framework.Three mapping enhancement strategies were investigated–Circle-Root,Tent-Cosine,and Logistic-Sine mappings-with the Logistic mapping further improved via Sine perturbation to boost global search capability and convergence speed in large-scale,complex data scenarios.Evaluation results demonstrate that the LSGWO-BP model significantly outperforms conventional machine learning approaches in predicting quasi-phase equilibrium,achieving a 14%–28%reduction in mean absolute error(MAE).Substantial improvements were also observed in mean squared error,root mean squared error,and mean absolute percentage error,alongside a 7%–33%increase in the coefficient of determination(R2).Furthermore,the model exhibits strong potential for microstructural simulation applications.Overall,the study confirms the effectiveness of the LSGWO-BP model in materials science,especially in enhancing phase-field modeling efficiency and enabling accurate,intelligent prediction for multicomponent alloy systems,thereby offering robust support for microstructure prediction and control.展开更多
The complex compositions of high-entropy alloys(HEAs)enable a variety of phase structures like FCC single phase,BCC single phase,or duplex FCC+BCC phase.Accurate and efficient prediction of phase structure is crucial ...The complex compositions of high-entropy alloys(HEAs)enable a variety of phase structures like FCC single phase,BCC single phase,or duplex FCC+BCC phase.Accurate and efficient prediction of phase structure is crucial for accelerating the discovery of new components and designing HEAs with desired phase structure.In this work,five machine learning strategies were utilized to predict the phase structures of HEAs with a dataset of 296.Specifically,a two-step feature selection strategy was proposed,enabling pronounced improvement in the computational efficiency from 2047 to 12 iterations for each model while ensuring fewer input features and higher prediction accuracy.Compared with traditional valence electron concentration criterion,the prediction accuracy of collected dataset was highly improved from 0.79 to 0.98 for random forest.Furthermore,HEAs with compositions of Al_(x)CoCu_(6)Ni_(6)Fe_(6)(x=1,3,6)were developed to validate the prediction results of machine learning models,and the mechanical properties as well as corrosion resistance were investigated.It is found that the higher Al content enhances the yield strength but deteriorates corrosion resistance.The present two-step feature selection strategy provides an alternative method that is feasible for predicting the phase structure of HEAs with high efficiency and accuracy.展开更多
The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-va...The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.展开更多
LiFePO_(4)has normal olivine-structured(a-LFP)and high pressure(b-LFP)phases,with the former being one of the cathode materials for commercial Li-ion batteries.Despite extensive focus on the respective electrochemical...LiFePO_(4)has normal olivine-structured(a-LFP)and high pressure(b-LFP)phases,with the former being one of the cathode materials for commercial Li-ion batteries.Despite extensive focus on the respective electrochemical properties of the two phases,there is a lack of comparative studies on their electronic and magnetic properties,and the origin of the structural phase transition remains unclear.By combining first-principles calculations with molecular dynamics simulations,we find that the anisotropic compression of Li-O bonds drives the structural phase transition from a-LFP to b-LFP at a critical pressure of 20 GPa,while b-LFP undergoes a transition from semiconductor to metal due to Fe^(3+)generated during delithiation.Their antiferromagnetic(AFM)ground states are predicted to arise from the negative magnetic exchange interactions between nearest and next-nearest neighbor sites,with the corresponding N'eel temperature showing significant enhancement under pressure.Furthermore,compared with a-LFP,b-LFP shows increases in bulk,shear,and Young’s moduli of 8%,13%,and 12%,respectively.These findings enrich the physical property data of LiFePO_(4)phase compounds,providing knowledge for expanding the application scenarios of the a-LFP phase under special operating conditions such as high pressure.展开更多
Flexible phase change materials(PCMs)have become increasingly critical to address the demand for thermal management in electronic technologies and energy conversion.However,their application remains challenging becaus...Flexible phase change materials(PCMs)have become increasingly critical to address the demand for thermal management in electronic technologies and energy conversion.However,their application remains challenging because of their rigidity,liquid leakage,and insufficient thermal conductivity.Herein,flexible glutamic acid@natural rubber/paraffin wax(PW)/carbon nanotubes-graphene nanoplatelets(GNR/PW/CGNP)phase change composites with high thermal conductivity,excellent shape stability,and recyclability were reported.Zn^(2+)-based dynamic crosslinking was constructed through the reaction of zinc acetate and carboxyl groups on glutamic acid@natural rubber(GNR),which was used as a flexible matrix to physically blend with paraffin wax/carbon nanotubes/graphene nanoplatelets(PW/CGNP)to achieve uniform dispersion of PW/CGNP,continuous thermal conductivity networks,and good encapsulation of PW.The GNR/PW/CGNP composites showed excellent mechanical strength,flexibility,and recycling ability,and effective encapsulation prevented the outflow of melted PW during the phase transition.Also,the phase change enthalpy could attain 111.1 J/g with a higher thermal conductivity of 1.055 W/m K,428%higher than that of pure PW owing to the formation of efficient thermal conductive pathways,which exhibited outstanding thermal management performance and superior temperature control behavior in electronic devices.The developed flexible composite PCMs may open new possibilities for next-generation flexible thermal management electronics.展开更多
Sodium-ion batteries are the prominent device for stationary energy storage system and low-speed electric vehicles.However,the practical application is still limited by the unsatisfied performance and high cost of the...Sodium-ion batteries are the prominent device for stationary energy storage system and low-speed electric vehicles.However,the practical application is still limited by the unsatisfied performance and high cost of the cathode side,which strictly requires the development of high voltage,high capacity,and earth-abundant cathode material.Ni-Fe-Mn ternary layered oxide has been recognized as one of the most promising standard type of cathodes.However,the composition and phase structure on high-voltage characteristics have not been well investigated.Herein,selecting the typically high-voltage cathode of P2-Na_(0.67)Ni_(0.33)Mn_(0.67)O_(2)as a parent material,we fabricate ten Ni-Fe-Mn ternary layered oxides through replacing the Ni,Mn,or both Ni and Mn by Fe.The thermodynamically stable phase diagram for those materials is presented.The electrochemical properties for all the samples are investigated in detail.Three potential Ni-Fe-Mn ternary layered oxides are picked up considering the energy density,cycle stability,kinetics,cost price,and working voltage,which demonstrate great potential for surpassing the performance of lithium iron phosphate.The related electrochemical reaction and fading mechanism are well revealed.This work provides some new foundational Ni-Fe-Mn ternary layered materials for high-voltage sodium-ion batteries.展开更多
We present a comprehensive investigation into the physical properties of intermetallic ErPd_(2)Si_(2),a compound renowned for its intriguing magnetic and electronic characteristics.We confirm the tetragonal crystal st...We present a comprehensive investigation into the physical properties of intermetallic ErPd_(2)Si_(2),a compound renowned for its intriguing magnetic and electronic characteristics.We confirm the tetragonal crystal structure of ErPd_(2)Si_(2)within the I4/mmm space group.Notably,we observed anisotropic thermal expansion,with the lattice constant a expanding and c contracting between 15 and300 K.This behaviour is attributed to lattice vibrations and electronic contributions.Heat capacity measurements revealed three distinct temperature regimes:T_(1)~3.0 K,T_(N)~4.20 K,and T_(2)~15.31 K.These correspond to thedisappearance of spin-density waves,the onset of an incommensurate antiferromagnetic(AFM)structure,and the crystal-field splitting and/or the presence of short-range spin fluctuations,respectively.Remarkably,the AFM phase transition anomaly was observed exclusively in lowfield magnetization data(120 Oe)at T_(N).A high magnetic field(B=3 T)effectively suppressed this anomaly,likely due to spin-flop and spin-flip transitions.Furthermore,the extracted effective paramagnetic(PM)moments closely matched the expected theoretical value,suggesting a dominant magnetic contribution from localized 4f spins of Er.Additionally,significant differences in resistance(R)values at low temperatures under applied B indicated a magnetoresistance(MR)effect with a minimum value of-4.36%.Notably,the measured MR effect exhibited anisotropic behavior,where changes in the strength or direction of the applied B induced variations in the MR effect.A twofold symmetry of R was discerned at 3 and9 T,originating from the orientation of spin moments relative to the applied B.Intriguingly,above T_(N),shortrange spin fluctuations also displayed a preferred orientation along the c-axis due to single-ion anisotropy.Moreover,the R demonstrated a clear B dependence below30 K.The magnetic-field point where R transitions from linear B dependence to a stable state increased with temperature:~3 T(at 2 K),~4.5 T(at 4 K),and~6 T(at 10 K).Our study sheds light on the magnetic and electronic properties of ErPd_(2)Si_(2),offering valuable insights for potential applications in spintronics and quantum technologies.展开更多
基金National Natural Science Foundation of China.(No.50237010)
文摘A test study on 50% lightning impulse breakdown voltage in two-phase mixture of gas and solid particles has been carried out in a specially designed discharge cabinet. A mechanical sieve is set up for sifting different solid particles into the discharge space uniformly. The lightning impulse voltage according with international electro-technical commission （IEC） standard is applied to the electrodes inside the discharge cabinet by the rule of up-down method in a total of 40 times. The results showed that the 50% lightning impulse breakdown voltage in two-phase mixture of gas and solid particles has its own features and is much different from that in air.
基金The National High Technology Research and Development Program of China (863 Program) (No. 2007AA01Z2A7)Program for Special Talents in Six Fields of Jiangsu Province
文摘Based on 0.13μm complementary metal-oxide-semiconductor（CMOS） technology,a phase and frequency detector（PFD） is designed with a low supply voltage of 0.5V for frequency synthesizers used in wireless sensor networks（WSNs）.The PFD can compare the frequency and phase differences of input signals and deliver a signal voltage proportional to the difference.Low threshold transistors are used in the circuits since a power supply of 0.5V is adopted.A pulse latched structure is also used in the circuits in order to increase both the detection range of phase errors and the maximum operation frequency.In experiments,a phase error with a range from-358° to 358° is measured when the input signal frequency is 2MHz.The PFD has a faster acquisition speed compared with conventional digital PFDs.When the input signals are at a frequency of 2MHz with zero phase error,the circuits have a power consumption of 1.8[KG＊8]μW,and the maximum operation frequency is 1.25GHz.
基金funded by the State Grid Corporation Science and Technology Project(5108-202218280A-2-391-XG).
文摘The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution network.Firstly,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are established.Additionally,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the EVcharger.Amultiobjective optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy consumption.Then,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time scales.Themulti-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control optimization.Simulation results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution network.It effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.
基金supported by the Science and Technology Project of China Southern Power Grid Co.,Ltd under Grant 036000KC23090004(GDKJXM20231026).
文摘The integration of renewable energy sources(RESs)with inverter interfaces has fundamentally reshaped power system dynamics,challenging traditional stability analysis frameworks designed for synchronous generator-dominated grids.Conventional classifica-tions,which decouple voltage,frequency,and rotor angle stability,fail to address the emerging strong voltage‒angle coupling effects caused by RES dynamics.This coupling introduces complex oscillation modes and undermines system robustness,neces-sitating novel stability assessment tools.Recent studies focus on eigenvalue distributions and damping redistribution but lack quantitative criteria and interpretative clarity for coupled stability.This work proposes a transient energy-based framework to resolve these gaps.By decomposing transient energy into subsystem-dissipated components and coupling-induced energy exchange,the method establishes stability criteria compatible with a broad variety of inverter-interfaced devices while offering an intuitive energy-based interpretation for engineers.The coupling strength is also quantified by defining the relative coupling strength index,which is directly related to the transient energy interpretation of the coupled stability.Angle‒voltage coupling may induce instability by injecting transient energy into the system,even if the individual phase angle and voltage dynamics themselves are stable.The main contributions include a systematic stability evaluation framework and an energy decomposition approach that bridges theoretical analysis with practical applicability,addressing the urgent need for tools for managing modern power system evolving stability challenges.
基金financially supported by the National Natural Science Foundation of China (Nos. 51972023 and 51572024)
文摘Lithium-rich materials possess the ultra-high specific capacity,but the redox of oxygen is not completely reversible,resulting in voltage attenuation and structural instability.A stepwise co-precipitation method is used for the first time in this paper to achieve the control of the two-phase distribution through controlling the distribution of transition metal elements and realize the modification of particle surface structure without the aid of heterologous ions.The results of characterization tests show that the content of LiMO_(2) phase inside the particles and the content of Li_(2)MnO_(3) phase on the surface of the particles are successfully increased,and the surface induced formation of Li_(4)Mn_(5)O_(12) spinel phase or some disorderly ternary.The electrochemical performance of the modified sample is as follows:LR(pristine)shows specific discharge capacity of 72.7 mA·h·g^(−1)after 500 cycles at 1 C,while GR(modified sample)shows specific discharge capacity of 137.5 mA·h·g^(−1) at 1 C,and the discharge mid-voltage of GR still remains above 3 V when cycling to 220 cycles at 1 C(mid-voltage of LR remains above 3 V when cycling to 160 cycles at 1 C).Therefore,deliberately regulating the local state of the two phases is a successful way to reinforced the material structure and inhibition the voltage attenuation.
文摘Low-voltage distribution systems in our country are mostly used in agricultural loads and household loads. The value and using time of these kinds of loads are uncontrollable, which lead to the three-phase imbalance in low-voltage distribution system, and seriously affect the quality of power supply. A new type of the commutation system and an improved quantum genetic algorithm (IQGA) are proposed in the paper. At last, the rationality and the efficiency of the method are verified by a practical example.
基金funded by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(Grant No.2024ZD1002503)。
文摘Passive microseismic monitoring(PMM)serves as a fundamental technology for assessing hydraulic fracturing(HF)effectiveness,with a key focus on accurate and efficient phase detection/arrival picking and source location.In PMM data processing,the data-driven paradigm(deep learning based)outperforms the model-driven paradigm in characteristic extraction but lacks quality control and uncertainty quantification.Monte Carlo Dropout,a Bayesian uncertainty quantification technique,performs stochastic neuron deactivation through multiple forward propagation samplings.Therefore,this study proposes a deep learning neural network incorporating uncertainty quantification with manual quality control integration,establishing an optimized workflow spanning automated phase detection to robust source location.The methodology implementation comprises two principal components:(1)The MDNet employing Monte Carlo Dropout strategy enabling simultaneous phase detection/arrival picking and unce rtainty estimation;(2)an integrated hybrid-driven workflow with a traveltime-based inve rsion method for source location.Validation with field data demonstrates that MD-Net achieves superior performance under low signal-to-noise ratio conditions,maintaining detection accuracy exceeding 99%for both P-and S-waves.The phase arrival picking precision shows significant improvement,with a 40%reduction in standard deviation compared to the baseline model(P-S time difference decreasing from12.0 ms to 7.1 ms),while providing quantifiable uncertainty metrics for manual calibration.Source location results further reveal that our hybrid-driven workflow produces more physically plausible event distributions,with 100%of microseismic eve nts clustering along the primary fracture expanding direction.This performance surpasses traditional cross-correlation methods and single/multi-trace data-driven me thods in spatial rationality.This study establishes an inte rpretable,high-pre cision automated framework for HF-PMM applications,demonstrating potential for extension to diverse geological settings and monitoring configurations.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.U1809210)the International Science Technology Cooperation Program of China(Grant No.2014DFR51160)+3 种基金the One Belt and One Road International Cooperation Project from the Key Research and Development Program of Zhejiang Province,China(Grant No.2018C04021)the National Natural Science Foundation of China(Grant Nos.50972129,50602039,and 52102052)the Fund from Institute of Wenzhou,Zhejiang University(Grant Nos.XMGL-CX-202305 and XMGLKJZX-202307)the Project from Tanghe Scientific&Technology Company(Grant No.KYY-HX-20230024).
文摘It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-62 and lzujbky-2024-jdzx06)the National Natural Science Foundation of China(Grant No.12247101)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant Nos.22JR5RA389 and 23JRRA1740)the‘111 Center’Fund(Grant No.B20063).
文摘It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.
基金supported by the National Natural Science Foundation of China(Grant No.12175316).
文摘Phase transitions,as one of the most intriguing phenomena in nature,are divided into first-order phase transitions(FOPTs)and continuous ones in current classification.While the latter shows striking phenomena of scaling and universality,the former has recently also been demonstrated to exhibit scaling and universal behavior within a mesoscopic,coarse-grained Landau-Ginzburg theory.Here we apply this theory to a microscopic model-the paradigmatic Ising model,which undergoes FOPTs between two ordered phases below its critical temperature-and unambiguously demonstrate universal scaling behavior in such FOPTs.These results open the door for extending the theory to other microscopic FOPT systems and experimentally testing them to systematically uncover their scaling and universal behavior.
基金supported by National Natural Science Foundation of China under Grant No.62236007the specialized research projects of Huanjiang Laboratory.
文摘Modeling the dynamics of flapping wing aerial vehicle is challenging due to the complexity of aerodynamic effects and mechanical structures.The aim of this work is to develop an accurate dynamics model of flapping wing aerial vehicle based on real flight data.We propose a modeling framework that combines rigid body dynamics with a neural network to predict aerodynamic effects.By incorporating the concept of flapping phase,we significantly enhance the network’s ability to analyze transient aerodynamic behavior.We design and utilize a phase-functioned neural network structure for aerodynamic predictions and train the network using real flight data.Evaluation results show that the network can predict aerodynamic effects and demonstrate clear physical significance.We verify that the framework can be used for dynamic propagation and is expected to be utilized for building simulators for flapping wing aerial vehicles.
基金supported by the National Key R&D Program of China(2024YFB4609801)the National Natural Science Foundation of China(52075289)the Tsinghua-Jiangyin Innovation Special Fund(TJISF,2023JYTH0104).
文摘Photonic computing has emerged as a promising technology for the ever-increasing computational demands of machine learning and artificial intelligence.Due to the advantages in computing speed,integrated photonic chips have attracted wide research attention on performing convolutional neural network algorithm.Programmable photonic chips are vital for achieving practical applications of photonic computing.Herein,a programmable photonic chip based on ultrafast laser-induced phase change is fabricated for photonic computing.Through designing the ultrafast laser pulses,the Sb film integrated into photonic waveguides can be reversibly switched between crystalline and amorphous phase,resulting in a large contrast in refractive index and extinction coefficient.As a consequence,the light transmission of waveguides can be switched between write and erase states.To determine the phase change time,the transient laser-induced phase change dynamics of Sb film are revealed at atomic scale,and the time-resolved transient reflectivity is measured.Based on the integrated photonic chip,photonic convolutional neural networks are built to implement machine learning algorithm,and images recognition task is achieved.This work paves a route for fabricating programmable photonic chips by designed ultrafast laser,which will facilitate the application of photonic computing in artificial intelligence.
基金supported by the National Natural Science Foundation of China(Grant Nos.52161002,51661020 and 11364024)。
文摘As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,particularly when addressing high-dimensional and complex data in multicomponent systems.To overcome these challenges,this study proposes an innovative model,LSGWO-BP,which integrates an improved Grey Wolf Optimizer(GWO)with a backpropagation neural network(BP)to enhance the accuracy and efficiency of quasi-phase equilibrium predictions within the KKS phase-field framework.Three mapping enhancement strategies were investigated–Circle-Root,Tent-Cosine,and Logistic-Sine mappings-with the Logistic mapping further improved via Sine perturbation to boost global search capability and convergence speed in large-scale,complex data scenarios.Evaluation results demonstrate that the LSGWO-BP model significantly outperforms conventional machine learning approaches in predicting quasi-phase equilibrium,achieving a 14%–28%reduction in mean absolute error(MAE).Substantial improvements were also observed in mean squared error,root mean squared error,and mean absolute percentage error,alongside a 7%–33%increase in the coefficient of determination(R2).Furthermore,the model exhibits strong potential for microstructural simulation applications.Overall,the study confirms the effectiveness of the LSGWO-BP model in materials science,especially in enhancing phase-field modeling efficiency and enabling accurate,intelligent prediction for multicomponent alloy systems,thereby offering robust support for microstructure prediction and control.
基金the Shenzhen Fundamental Research Fund(No.JCYJ20210324122801005)the Fundamental Research Funds for the Central Universities(No.HIT.OCEF.2023022).
文摘The complex compositions of high-entropy alloys(HEAs)enable a variety of phase structures like FCC single phase,BCC single phase,or duplex FCC+BCC phase.Accurate and efficient prediction of phase structure is crucial for accelerating the discovery of new components and designing HEAs with desired phase structure.In this work,five machine learning strategies were utilized to predict the phase structures of HEAs with a dataset of 296.Specifically,a two-step feature selection strategy was proposed,enabling pronounced improvement in the computational efficiency from 2047 to 12 iterations for each model while ensuring fewer input features and higher prediction accuracy.Compared with traditional valence electron concentration criterion,the prediction accuracy of collected dataset was highly improved from 0.79 to 0.98 for random forest.Furthermore,HEAs with compositions of Al_(x)CoCu_(6)Ni_(6)Fe_(6)(x=1,3,6)were developed to validate the prediction results of machine learning models,and the mechanical properties as well as corrosion resistance were investigated.It is found that the higher Al content enhances the yield strength but deteriorates corrosion resistance.The present two-step feature selection strategy provides an alternative method that is feasible for predicting the phase structure of HEAs with high efficiency and accuracy.
基金supported in part by the National Natural Science Fundation of China(52225704 and 52107096).
文摘The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.
基金supported by the National Natural Science Foundation of China(Grant No.12304089)the start-up foundation from Shanghai University。
文摘LiFePO_(4)has normal olivine-structured(a-LFP)and high pressure(b-LFP)phases,with the former being one of the cathode materials for commercial Li-ion batteries.Despite extensive focus on the respective electrochemical properties of the two phases,there is a lack of comparative studies on their electronic and magnetic properties,and the origin of the structural phase transition remains unclear.By combining first-principles calculations with molecular dynamics simulations,we find that the anisotropic compression of Li-O bonds drives the structural phase transition from a-LFP to b-LFP at a critical pressure of 20 GPa,while b-LFP undergoes a transition from semiconductor to metal due to Fe^(3+)generated during delithiation.Their antiferromagnetic(AFM)ground states are predicted to arise from the negative magnetic exchange interactions between nearest and next-nearest neighbor sites,with the corresponding N'eel temperature showing significant enhancement under pressure.Furthermore,compared with a-LFP,b-LFP shows increases in bulk,shear,and Young’s moduli of 8%,13%,and 12%,respectively.These findings enrich the physical property data of LiFePO_(4)phase compounds,providing knowledge for expanding the application scenarios of the a-LFP phase under special operating conditions such as high pressure.
基金financially supported by the China Postdoctoral Science Foundation(No.2024M751205)。
文摘Flexible phase change materials(PCMs)have become increasingly critical to address the demand for thermal management in electronic technologies and energy conversion.However,their application remains challenging because of their rigidity,liquid leakage,and insufficient thermal conductivity.Herein,flexible glutamic acid@natural rubber/paraffin wax(PW)/carbon nanotubes-graphene nanoplatelets(GNR/PW/CGNP)phase change composites with high thermal conductivity,excellent shape stability,and recyclability were reported.Zn^(2+)-based dynamic crosslinking was constructed through the reaction of zinc acetate and carboxyl groups on glutamic acid@natural rubber(GNR),which was used as a flexible matrix to physically blend with paraffin wax/carbon nanotubes/graphene nanoplatelets(PW/CGNP)to achieve uniform dispersion of PW/CGNP,continuous thermal conductivity networks,and good encapsulation of PW.The GNR/PW/CGNP composites showed excellent mechanical strength,flexibility,and recycling ability,and effective encapsulation prevented the outflow of melted PW during the phase transition.Also,the phase change enthalpy could attain 111.1 J/g with a higher thermal conductivity of 1.055 W/m K,428%higher than that of pure PW owing to the formation of efficient thermal conductive pathways,which exhibited outstanding thermal management performance and superior temperature control behavior in electronic devices.The developed flexible composite PCMs may open new possibilities for next-generation flexible thermal management electronics.
基金financially supported by the National Natural Science Foundation of China(Grant No.52402215)the Anhui Provincial Natural Science Foundation(2408085QB036)+1 种基金the Natural Science Research Project of Anhui Province Education Department(Grant Nos.2022AH050334,2022AH030046,2023AH051119)the Scientific Research Foundation of Anhui University of Technology for Talent Introduction(DT2200001211)。
文摘Sodium-ion batteries are the prominent device for stationary energy storage system and low-speed electric vehicles.However,the practical application is still limited by the unsatisfied performance and high cost of the cathode side,which strictly requires the development of high voltage,high capacity,and earth-abundant cathode material.Ni-Fe-Mn ternary layered oxide has been recognized as one of the most promising standard type of cathodes.However,the composition and phase structure on high-voltage characteristics have not been well investigated.Herein,selecting the typically high-voltage cathode of P2-Na_(0.67)Ni_(0.33)Mn_(0.67)O_(2)as a parent material,we fabricate ten Ni-Fe-Mn ternary layered oxides through replacing the Ni,Mn,or both Ni and Mn by Fe.The thermodynamically stable phase diagram for those materials is presented.The electrochemical properties for all the samples are investigated in detail.Three potential Ni-Fe-Mn ternary layered oxides are picked up considering the energy density,cycle stability,kinetics,cost price,and working voltage,which demonstrate great potential for surpassing the performance of lithium iron phosphate.The related electrochemical reaction and fading mechanism are well revealed.This work provides some new foundational Ni-Fe-Mn ternary layered materials for high-voltage sodium-ion batteries.
基金supported by the Science and Technology Development Fund,Macao SAR,China(File Nos.0090/2021/A2 and 0104/2024/AFJ)University of Macao(MYRG-GRG2024-00158-IAPME)+3 种基金the support from the National Natural Science Foundation of China(No.52275467)the support from the National Natural Science Foundation of China(No.52271037)Shaanxi Provincial Natural Science Fundamental Research Program,China(No.2023-JC-ZD-23)the Fundamental Research Funds for the Central Universities of China(No.D5000240307)
文摘We present a comprehensive investigation into the physical properties of intermetallic ErPd_(2)Si_(2),a compound renowned for its intriguing magnetic and electronic characteristics.We confirm the tetragonal crystal structure of ErPd_(2)Si_(2)within the I4/mmm space group.Notably,we observed anisotropic thermal expansion,with the lattice constant a expanding and c contracting between 15 and300 K.This behaviour is attributed to lattice vibrations and electronic contributions.Heat capacity measurements revealed three distinct temperature regimes:T_(1)~3.0 K,T_(N)~4.20 K,and T_(2)~15.31 K.These correspond to thedisappearance of spin-density waves,the onset of an incommensurate antiferromagnetic(AFM)structure,and the crystal-field splitting and/or the presence of short-range spin fluctuations,respectively.Remarkably,the AFM phase transition anomaly was observed exclusively in lowfield magnetization data(120 Oe)at T_(N).A high magnetic field(B=3 T)effectively suppressed this anomaly,likely due to spin-flop and spin-flip transitions.Furthermore,the extracted effective paramagnetic(PM)moments closely matched the expected theoretical value,suggesting a dominant magnetic contribution from localized 4f spins of Er.Additionally,significant differences in resistance(R)values at low temperatures under applied B indicated a magnetoresistance(MR)effect with a minimum value of-4.36%.Notably,the measured MR effect exhibited anisotropic behavior,where changes in the strength or direction of the applied B induced variations in the MR effect.A twofold symmetry of R was discerned at 3 and9 T,originating from the orientation of spin moments relative to the applied B.Intriguingly,above T_(N),shortrange spin fluctuations also displayed a preferred orientation along the c-axis due to single-ion anisotropy.Moreover,the R demonstrated a clear B dependence below30 K.The magnetic-field point where R transitions from linear B dependence to a stable state increased with temperature:~3 T(at 2 K),~4.5 T(at 4 K),and~6 T(at 10 K).Our study sheds light on the magnetic and electronic properties of ErPd_(2)Si_(2),offering valuable insights for potential applications in spintronics and quantum technologies.
