Adaptive signal decomposition is an important signal processing method.The chirp-based signal representation,for example,the Gaussian chirplet decomposition,has been an active research topic in the field of signal pro...Adaptive signal decomposition is an important signal processing method.The chirp-based signal representation,for example,the Gaussian chirplet decomposition,has been an active research topic in the field of signal processing.A main challenge of the Gaussian chirplet decomposition is the numerical implementation of the matching pursuit,which is an adaptive signal decomposition scheme,and the challenge remains an open research topic.In this paper,a new optimal time-frequency atom search method based on the adaptive genetic algorithm is proposed,aiming to the low precision problem of the traditional methods.Firstly,a discrete formula of finite length time-frequency atom sequence is derived.Secondly,an algorithm based on the adaptive genetic algorithm is described in detail.Finally,a simulation is carried out,and the result displays its validity and stability.展开更多
Seismic time-frequency(TF)transforms are essential tools in reservoir interpretation and signal processing,particularly for characterizing frequency variations in non-stationary seismic data.Recently,sparse TF trans-f...Seismic time-frequency(TF)transforms are essential tools in reservoir interpretation and signal processing,particularly for characterizing frequency variations in non-stationary seismic data.Recently,sparse TF trans-forms,which leverage sparse coding(SC),have gained significant attention in the geosciences due to their ability to achieve high TF resolution.However,the iterative approaches typically employed in sparse TF transforms are computationally intensive,making them impractical for real seismic data analysis.To address this issue,we propose an interpretable convolutional sparse coding(CSC)network to achieve high TF resolution.The proposed model is generated based on the traditional short-time Fourier transform(STFT)transform and a modified UNet,named ULISTANet.In this design,we replace the conventional convolutional layers of the UNet with learnable iterative shrinkage thresholding algorithm(LISTA)blocks,a specialized form of CSC.The LISTA block,which evolves from the traditional iterative shrinkage thresholding algorithm(ISTA),is optimized for extracting sparse features more effectively.Furthermore,we create a synthetic dataset featuring complex frequency-modulated signals to train ULISTANet.Finally,the proposed method’s performance is subsequently validated using both synthetic and field data,demonstrating its potential for enhanced seismic data analysis.展开更多
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 eff...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.展开更多
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 improv...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.展开更多
A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization ...A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing.展开更多
We used daily return series for three pairs of datasets from the crude oil markets(WTI and Brent),stock indices(the Dow Jones Industrial Average and S&P 500),and benchmark cryptocurrencies(Bitcoin and Ethereum)to ...We used daily return series for three pairs of datasets from the crude oil markets(WTI and Brent),stock indices(the Dow Jones Industrial Average and S&P 500),and benchmark cryptocurrencies(Bitcoin and Ethereum)to examine the connections between various data during the COVID-19 pandemic.We consider two characteristics:time and frequency.Based on Diebold and Yilmaz’s(Int J Forecast 28:57-66,2012)technique,our findings indicate that comparable data have a substantially stronger correlation(regarding return)than volatility.Per Baruník and Křehlík’(J Financ Econ 16:271-296,2018)approach,interconnectedness among returns(volatilities)reduces(increases)as one moves from the short to the long term.A moving window analysis reveals a sudden increase in correlation,both in volatility and return,during the COVID-19 pandemic.In the context of wavelet coherence analysis,we observe a strong interconnection between data corresponding to the COVID-19 outbreak.The only exceptions are the behavior of Bitcoin and Ethereum.Specifically,Bitcoin combinations with other data exhibit a distinct behavior.The period precisely coincides with the COVID-19 pandemic.Evidently,volatility spillover has a long-lasting impact;policymakers should thus employ the appropriate tools to mitigate the severity of the relevant shocks(e.g.,the COVID-19 pandemic)and simultaneously reduce its side effects.展开更多
Seismic inversion can be divided into time-domain inversion and frequency-domain inversion based on different transform domains.Time-domain inversion has stronger stability and noise resistance compared to frequencydo...Seismic inversion can be divided into time-domain inversion and frequency-domain inversion based on different transform domains.Time-domain inversion has stronger stability and noise resistance compared to frequencydomain inversion.Frequency domain inversion has stronger ability to identify small-scale bodies and higher inversion resolution.Therefore,the research on the joint inversion method in the time-frequency domain is of great significance for improving the inversion resolution,stability,and noise resistance.The introduction of prior information constraints can effectively reduce ambiguity in the inversion process.However,the existing modeldriven time-frequency joint inversion assumes a specific prior distribution of the reservoir.These methods do not consider the original features of the data and are difficult to describe the relationship between time-domain features and frequency-domain features.Therefore,this paper proposes a high-resolution seismic inversion method based on joint data-driven in the time-frequency domain.The method is based on the impedance and reflectivity samples from logging,using joint dictionary learning to obtain adaptive feature information of the reservoir,and using sparse coefficients to capture the intrinsic relationship between impedance and reflectivity.The optimization result of the inversion is achieved through the regularization term of the joint dictionary sparse representation.We have finally achieved an inversion method that combines constraints on time-domain features and frequency features.By testing the model data and field data,the method has higher resolution in the inversion results and good noise resistance.展开更多
The T_(1)(Al_(2) CuLi)phase is one of the most effective strengthening nanoscale-precipitate in Al-Cu alloys with Li.However,its formation and evolution still need to be further clarified during aging due to the compl...The T_(1)(Al_(2) CuLi)phase is one of the most effective strengthening nanoscale-precipitate in Al-Cu alloys with Li.However,its formation and evolution still need to be further clarified during aging due to the complex precipitation sequences.Here,a detailed investigation has been carried out on the atomic struc-tural evolution of T_(1) precipitate in an aged Al-Cu-Li-Mg-Ag alloy using state-of-the-art Cs-corrected high-angle annular dark field(HAADF)-coupled with integrated differential phase contrast(iDPC)-scanning transmission electron microscopy(STEM)and energy-dispersive X-ray spectroscopy(EDXS)techniques.An intermediate T_(1)’phase between T_(1p) and T_(1) phase,with a crystal structure and orientation rela-tionship consistent with T_(1),but exhibiting different atomic occupancy and chemical composition was found.We observed the atomic structural transformation from T_(1p) to T_(1)’phase(fcc→hcp),involving only 1/12<112>Al shear component.DFT calculation results validated our proposed structural models and the precipitation sequence.Besides,the distributions of minor solute elements(Ag,Mg,and Zn)in the pre-cipitates exhibited significant differences.These findings may contribute to a further understanding of the nucleation mechanism of T_(1) precipitate.展开更多
Lithium-sulfur (Li-S) batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish ...Lithium-sulfur (Li-S) batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox dynamics.Herein,we supply a strategy to optimize the electron structure of Ni_(2)P by concurrently introducing B-doped atoms and P vacancies in Ni_(2)P (Vp-B-Ni_(2)P),thereby enhancing the bidirectional sulfur conversion.The study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni_(2)P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides (LiPSs) as well as expediting the bidirectional conversion kinetics of sulfur species.Meanwhile,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni_(2)P selectively promotes Li2S dissolution and nucleation processes.Thus,the Li-S batteries with Vp-B-Ni_(2)P-separators present outstanding rate ability of 777 m A h g^(-1)at 5 C and high areal capacity of 8.03 mA h cm^(-2)under E/S of 5μL mg^(-1)and sulfur loading of 7.20 mg cm^(-2).This work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion.展开更多
Exploiting non-precious metal catalysts with excellent oxygen reduction reaction(ORR)performance for energy devices is paramount essential for the green and sustainable society development.Herein,low-cost,high-perform...Exploiting non-precious metal catalysts with excellent oxygen reduction reaction(ORR)performance for energy devices is paramount essential for the green and sustainable society development.Herein,low-cost,high-performance biomass-derived ORR catalysts with an asymmetric Fe-N_(3)P configuration was prepared by a simple pyrolysis-etching technique,where carboxymethyl cellulose(CMC)was used as the carbon source,urea and 1,10-phenanthroline iron complex(FePhen)as additives,and Na_(3)PO_(4)as the phosphorus dopant and a pore-forming agent.The CMC-derived FeNPC catalyst displayed a large specific area(BET:1235 m^(2)g^(-1))with atomically dispersed Fe-N_(3)P active sites,which exhibited superior ORR activity and stability in alkaline solution(E_(1/2)=0.90 V vs.RHE)and Zn-air batteries(P_(max)=149 mW cm^(-2))to commercial Pt/C catalyst(E_(1/2)=0.87 V,P_(max)=118 mW cm^(-2))under similar experimental conditions.This work provides a feasible and costeffective route toward highly efficient ORR catalysts and their application to Zn-air batteries for energy conversion.展开更多
Broadband transparent films play a pivotal role in various applications such as lenses and solar cells,particularly porous structured transparent films exhibit significant potential.This study investigates a porous Si...Broadband transparent films play a pivotal role in various applications such as lenses and solar cells,particularly porous structured transparent films exhibit significant potential.This study investigates a porous SiO_(2) refractive index gradient anti-reflective film prepared by atomic layer deposition(ALD).A porous SiO_(2) film with gradual porosity was obtained by phosphoric acid etching of Al_(2)O_(3)/SiO_(2) multilayers with gradient Al2O3 ratios,achieving a gradual decrease in refractive index from the substrate to the surface.The film exhibited an average transmittance as high as 97.8%within the wavelength range from 320 nm to 1200 nm.The environmental adaptability was further enhanced by surface modification using rare earth oxide(REO)La_(2)O_(3),resulting in formation of a lotus leaf-like structure and achieving a water contact angle of 100.0°.These data proved that the modification significantly improved hydrophobic self-cleaning capability while maintaining exceptional transparency of the film.The surface structure of the modified film remained undamaged even after undergoing wipe testing,demonstrating its excellent surface durability.展开更多
Polymeric perylene diimide(PDI)has been evidenced as a good candidate for photocatalytic water oxidation,yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration.Her...Polymeric perylene diimide(PDI)has been evidenced as a good candidate for photocatalytic water oxidation,yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration.Herein,with crystal and atomic structures of the self-assembled PDI revealed from the X-ray diffraction pattern,the electronic structure is theoretically illustrated by the first-principles density functional theory calculations,suggesting the suitable band structure and the direct electronic transition for efficient photocatalytic oxygen evolution over PDI.It is confirmed that the carbonyl O atoms on the conjugation structure serve as the active sites for oxygen evolution reaction by the crystal orbital Hamiltonian group analysis.The calculations of reaction free energy changes indicate that the oxygen evolution reaction should follow the reaction pathway of H_(2)O→^(*)OH→^(*)O→^(*)OOH→^(*)O_(2)with an overpotential of 0.81 V.Through an in-depth theoretical computational analysis in the atomic and electronic structures,the origin of photocatalytic oxygen evolution activity for PDI is well illustrated,which would help the rational design and modification of polymeric photocatalysts for efficient oxygen evolution.展开更多
Single-atom catalysts(SACs),in which isolated metal atoms such as palladium(Pd)are anchored on solid supports,promise breakthroughs in energy conversion and catalysis.However,balancing their activity(reaction speed)an...Single-atom catalysts(SACs),in which isolated metal atoms such as palladium(Pd)are anchored on solid supports,promise breakthroughs in energy conversion and catalysis.However,balancing their activity(reaction speed)and stability(longevity)remains challenging,as the interplay between metal atoms,supports,and reactants is poorly understood.展开更多
The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This techniqu...The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This technique,adapted for blast furnace slag granulation using a circular seam nozzle,typically aims to produce solid slag particles sized 30–140μm,thereby allowing the utilization of slag as a resource.This study explores the atomization dynamics of liquid blast furnace slag,focusing on the effects of atomization pressure.Primary atomization is simulated using a combination of the Volume of Fluid(VOF)method and the Shear Stress Transport k-ωturbulence model,while secondary atomization is analyzed through the Discrete Phase Model(DPM).The results reveal that primary atomization progresses in three stages:the slag column transforms into an umbrella-shaped liquid film,whose leading edge fragments into particles while forming a cavity-like structure,which is eventually torn into ligaments.This primary deformation is driven by the interplay of airflow velocity in the recirculation zone and the guide tube outlet pressure(Fp).Increasing the atomization pressure amplifies airflow velocity,recirculation zone size,expansion and shock waves,though the guide tube outlet pressure variations remain irregular.Notably,at 4.5 MPa,the primary deformation is most pronounced.Secondary atomization yields finer slag particles as a result of more vigorous primary atomization.For this pressure,the smallest average particle size and the highest yield of particles within the target range(30–140μm)are achieved.展开更多
Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and c...Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and competition against the hydrogen evolution reaction hinder its practical implementation.To address these,the design of highly active catalysts is critical.Single-atom catalysts(SACs)have shown great potential because of their maximized atom utilization,but their limited stability and low metal loading restrict their performances.On the other hand,dual-atom catalysts(DACs)are atomic catalysts with two metal atoms nearby and offer enhanced electrocatalytic performances by aligning with the N≡N bond to enhance N2 reduction efficiency,potentially overcoming the limitations of SAC.This review discusses recent advances in SACs and more importantly DACs for ENRR,highlighting their advantages,limitations,and the need for advanced characterization techniques to better understand catalyst behavior.The review concludes by underscoring the importance of research to optimize these catalysts for efficient and sustainable nitrogen fixation.展开更多
Electrocatalytic reduction of carbon dioxide(CO_(2))to carbon monoxide(CO)is an effective strategy to achieve carbon neutrality.High selective and low-cost catalysts for the electrocatalytic reduction of CO_(2)have re...Electrocatalytic reduction of carbon dioxide(CO_(2))to carbon monoxide(CO)is an effective strategy to achieve carbon neutrality.High selective and low-cost catalysts for the electrocatalytic reduction of CO_(2)have received increasing attention.In contrast to the conventional tube furnace method,the high-temperature shock(HTS)method enables ultra-fast thermal processing,superior atomic efficiency,and a streamlined synthesis protocol,offering a simplified method for the preparation of high-performance single-atom catalysts(SACs).The reports have shown that nickel-based SACs can be synthesized quickly and conveniently using the HTS method,making their application in CO_(2)reduction reactions(CO_(2)RR)a viable and promising avenue for further exploration.In this study,the effect of heating temperature,metal loading and different nitrogen(N)sources on the catalyst morphology,coordination environment and electrocatalytic performance were investigated.Under optimal conditions,0.05Ni-DCD-C-1050 showed excellent performance in reducing CO_(2)to CO,with CO selectivity close to 100%(−0.7 to−1.0 V vs RHE)and current density as high as 130 mA/cm^(2)(−1.1 V vs RHE)in a flow cell under alkaline environment.展开更多
Here we present a highly efficient protocol utilizing nickel-hydride hydrogen atom transfer catalysis for the regio-and enantioselective hydrofluorination of internal alkenes.This method efficiently assembles a wide a...Here we present a highly efficient protocol utilizing nickel-hydride hydrogen atom transfer catalysis for the regio-and enantioselective hydrofluorination of internal alkenes.This method efficiently assembles a wide array of enantioenrichedβ-fluoro amides with excellent regio-and enantioselectivity from internal unactivated alkenes.Mechanistic investigations suggest that this transformation proceeds via a NiHhydrogen atom transfer to alkene,followed by a stereoselective fluorine atom transfer process.The weak coordination effect of the tethered amide group is identified as a crucial factor governing the observed regio-and enantioselectivity.展开更多
In this paper,we address the problem of multiple frequency-hopping(FH)signal parameters estimation in the presence of random missing observations.A space-time matrix with random missing observations is acquired by a u...In this paper,we address the problem of multiple frequency-hopping(FH)signal parameters estimation in the presence of random missing observations.A space-time matrix with random missing observations is acquired by a uniform linear array(ULA).We exploit the inherent incomplete data processing capability of atomic norm soft thresholding(AST)to analyze the space-time matrix and complete the accurate estimation of the hopping time and frequency of the received FH signals.The hopping time is obtained by the sudden changes of the spatial information,which is implemented as the boundary to divide the time domain signal so that each segment of the signal is a superposition of time-invariant multiple components.Then,the frequency of multiple signal components can be estimated precisely by AST within each segment.After obtaining the above two parameters of the hopping time and the frequency of signals,the direction of arrival(DOA)can be directly calculated by them,and the network sorting can be realized.Results of simulation show that the proposed method is superior to the existing technology.Even when a large portion of data observations is missing,as the number of array elements increases,the proposed method still achieves acceptable accuracy of multi-FH signal parameters estimation.展开更多
Atmospheric escape plays a critical role in shaping the long-term climate evolution of Mars.Among the various escape mechanisms,energetic neutral atoms(ENAs)generated through charge exchange between solar wind ions an...Atmospheric escape plays a critical role in shaping the long-term climate evolution of Mars.Among the various escape mechanisms,energetic neutral atoms(ENAs)generated through charge exchange between solar wind ions and exospheric neutrals serve as an important diagnostic for ion-neutral interactions and upper atmospheric loss.This study presents direct observations of hydrogen ENAs(H-ENAs)on the dayside of Mars by using the Mars Ion and Neutral Particle Analyzer(MINPA)onboard China’s Tianwen-1 orbiter.By analyzing H-ENA data during a coronal mass ejection and a stream interaction region from December 29,2021,to January 1,2022,and comparing these data with MAVEN/SWIA(Mars Atmosphere and Volatile EvolutioN/Solar Wind Ion Analyzer)solar wind measurements,we examine the temporal evolution of H-ENA flux and the associated sputtered escape of atmospheric constituents.The observed H-ENA velocity is consistent with upstream solar wind ions,and the H-ENA-to-ion intensity ratio is used to infer variations in exospheric density,revealing a delayed response to enhanced solar wind activity.Penetrating H-ENA intensities reach up to 5.3×10^(6)s^(−1) cm^(−2),with energy fluxes on the order of(0.5-8.1)×10^(−3) mW/m^(2).The estimated oxygen sputtered escape rate driven by penetrating H-ENAs ranges from 5.5×10^(23)s^(−1) to 5.2×10^(24)s^(−1),comparable to or exceeding previous estimates based on penetrating ions.The findings highlight the need for low-altitude H-ENA observations to better quantify their atmospheric interactions and refine our understanding of nonthermal escape processes at Mars.展开更多
Heat dissipation highly relies on the thermal conductivity(κ)of materials.Materials with large bandgaps and signifcant atomic mass ratios,such as BAs,SiC,andθ-TaN,have attracted considerable attention due to their p...Heat dissipation highly relies on the thermal conductivity(κ)of materials.Materials with large bandgaps and signifcant atomic mass ratios,such as BAs,SiC,andθ-TaN,have attracted considerable attention due to their potential for achieving ultra-highκ,with BAs serving as a particularly representative example due to its unique combination of large bandgap and high thermal conductivity.In this paper,the efects of atomic mass modifcation on phonon bandgap andκare systematically investigated using a BAs model,accounting for both three-and four-phonon scattering processes.A 20%increase inκcan be obtained by substituting B,achieved through widening the phonon bandgap,which suppresses phonon scattering.Notably,the AAOO four-phonon scattering channel is more suppressed than the AAO three-phonon channel,leading to an increased phonon lifetime(τ).For As,κcan also be enhanced by 5%when replaced by lighter atoms,such as^(69)As,primarily due to the increased phonon group velocity(υ).We systematically clarify how atomic-mass-induced bandgap variations afectτ,υ,and thereforeκin wide-bandgap systems.Our work provides a specifc scheme for further improving the ultra-highκof materials with large bandgaps,which possesses great guiding signifcance.展开更多
基金Sponsored by National Nature Science Foundation of China (60575013)
文摘Adaptive signal decomposition is an important signal processing method.The chirp-based signal representation,for example,the Gaussian chirplet decomposition,has been an active research topic in the field of signal processing.A main challenge of the Gaussian chirplet decomposition is the numerical implementation of the matching pursuit,which is an adaptive signal decomposition scheme,and the challenge remains an open research topic.In this paper,a new optimal time-frequency atom search method based on the adaptive genetic algorithm is proposed,aiming to the low precision problem of the traditional methods.Firstly,a discrete formula of finite length time-frequency atom sequence is derived.Secondly,an algorithm based on the adaptive genetic algorithm is described in detail.Finally,a simulation is carried out,and the result displays its validity and stability.
基金supported by the National Natural Science Foundation of China under Grant 42474139the Key Research and Development Program of Shaanxi under Grant 2024GX-YBXM-067.
文摘Seismic time-frequency(TF)transforms are essential tools in reservoir interpretation and signal processing,particularly for characterizing frequency variations in non-stationary seismic data.Recently,sparse TF trans-forms,which leverage sparse coding(SC),have gained significant attention in the geosciences due to their ability to achieve high TF resolution.However,the iterative approaches typically employed in sparse TF transforms are computationally intensive,making them impractical for real seismic data analysis.To address this issue,we propose an interpretable convolutional sparse coding(CSC)network to achieve high TF resolution.The proposed model is generated based on the traditional short-time Fourier transform(STFT)transform and a modified UNet,named ULISTANet.In this design,we replace the conventional convolutional layers of the UNet with learnable iterative shrinkage thresholding algorithm(LISTA)blocks,a specialized form of CSC.The LISTA block,which evolves from the traditional iterative shrinkage thresholding algorithm(ISTA),is optimized for extracting sparse features more effectively.Furthermore,we create a synthetic dataset featuring complex frequency-modulated signals to train ULISTANet.Finally,the proposed method’s performance is subsequently validated using both synthetic and field data,demonstrating its potential for enhanced seismic data analysis.
基金We would like to thank the associate editor and the reviewers for their constructive comments.This work was supported in part by the National Natural Science Foundation of China under Grant 62203234in part by the State Key Laboratory of Robotics of China under Grant 2023-Z03+1 种基金in part by the Natural Science Foundation of Liaoning Province under Grant 2023-BS-025in part by the Research Program of Liaoning Liaohe Laboratory under Grant LLL23ZZ-02-02.
文摘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.
基金Supported by the National Science Foundation of China(42055402)。
文摘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.
基金This project was supported by the National Natural Science Foundation of China (60472102)Shanghai Leading Academic Discipline Project (T0103).
文摘A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing.
文摘We used daily return series for three pairs of datasets from the crude oil markets(WTI and Brent),stock indices(the Dow Jones Industrial Average and S&P 500),and benchmark cryptocurrencies(Bitcoin and Ethereum)to examine the connections between various data during the COVID-19 pandemic.We consider two characteristics:time and frequency.Based on Diebold and Yilmaz’s(Int J Forecast 28:57-66,2012)technique,our findings indicate that comparable data have a substantially stronger correlation(regarding return)than volatility.Per Baruník and Křehlík’(J Financ Econ 16:271-296,2018)approach,interconnectedness among returns(volatilities)reduces(increases)as one moves from the short to the long term.A moving window analysis reveals a sudden increase in correlation,both in volatility and return,during the COVID-19 pandemic.In the context of wavelet coherence analysis,we observe a strong interconnection between data corresponding to the COVID-19 outbreak.The only exceptions are the behavior of Bitcoin and Ethereum.Specifically,Bitcoin combinations with other data exhibit a distinct behavior.The period precisely coincides with the COVID-19 pandemic.Evidently,volatility spillover has a long-lasting impact;policymakers should thus employ the appropriate tools to mitigate the severity of the relevant shocks(e.g.,the COVID-19 pandemic)and simultaneously reduce its side effects.
文摘Seismic inversion can be divided into time-domain inversion and frequency-domain inversion based on different transform domains.Time-domain inversion has stronger stability and noise resistance compared to frequencydomain inversion.Frequency domain inversion has stronger ability to identify small-scale bodies and higher inversion resolution.Therefore,the research on the joint inversion method in the time-frequency domain is of great significance for improving the inversion resolution,stability,and noise resistance.The introduction of prior information constraints can effectively reduce ambiguity in the inversion process.However,the existing modeldriven time-frequency joint inversion assumes a specific prior distribution of the reservoir.These methods do not consider the original features of the data and are difficult to describe the relationship between time-domain features and frequency-domain features.Therefore,this paper proposes a high-resolution seismic inversion method based on joint data-driven in the time-frequency domain.The method is based on the impedance and reflectivity samples from logging,using joint dictionary learning to obtain adaptive feature information of the reservoir,and using sparse coefficients to capture the intrinsic relationship between impedance and reflectivity.The optimization result of the inversion is achieved through the regularization term of the joint dictionary sparse representation.We have finally achieved an inversion method that combines constraints on time-domain features and frequency features.By testing the model data and field data,the method has higher resolution in the inversion results and good noise resistance.
基金supported by the Pre-research fund(No.412130024).
文摘The T_(1)(Al_(2) CuLi)phase is one of the most effective strengthening nanoscale-precipitate in Al-Cu alloys with Li.However,its formation and evolution still need to be further clarified during aging due to the complex precipitation sequences.Here,a detailed investigation has been carried out on the atomic struc-tural evolution of T_(1) precipitate in an aged Al-Cu-Li-Mg-Ag alloy using state-of-the-art Cs-corrected high-angle annular dark field(HAADF)-coupled with integrated differential phase contrast(iDPC)-scanning transmission electron microscopy(STEM)and energy-dispersive X-ray spectroscopy(EDXS)techniques.An intermediate T_(1)’phase between T_(1p) and T_(1) phase,with a crystal structure and orientation rela-tionship consistent with T_(1),but exhibiting different atomic occupancy and chemical composition was found.We observed the atomic structural transformation from T_(1p) to T_(1)’phase(fcc→hcp),involving only 1/12<112>Al shear component.DFT calculation results validated our proposed structural models and the precipitation sequence.Besides,the distributions of minor solute elements(Ag,Mg,and Zn)in the pre-cipitates exhibited significant differences.These findings may contribute to a further understanding of the nucleation mechanism of T_(1) precipitate.
基金Institute of Technology Research Fund Program for Young Scholars21C Innovation Laboratory Contemporary Amperex Technology Co.,Limited,Ninde, 352100, China (21C–OP-202314)。
文摘Lithium-sulfur (Li-S) batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox dynamics.Herein,we supply a strategy to optimize the electron structure of Ni_(2)P by concurrently introducing B-doped atoms and P vacancies in Ni_(2)P (Vp-B-Ni_(2)P),thereby enhancing the bidirectional sulfur conversion.The study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni_(2)P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides (LiPSs) as well as expediting the bidirectional conversion kinetics of sulfur species.Meanwhile,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni_(2)P selectively promotes Li2S dissolution and nucleation processes.Thus,the Li-S batteries with Vp-B-Ni_(2)P-separators present outstanding rate ability of 777 m A h g^(-1)at 5 C and high areal capacity of 8.03 mA h cm^(-2)under E/S of 5μL mg^(-1)and sulfur loading of 7.20 mg cm^(-2).This work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion.
基金supported by the National Natural Science Foundation of China(No.21571062)the Program for Professor of Special Appointment(Eastern Scholar)at the Shanghai Institutions of Higher Learning to JGL,and the Fundamental Research Funds for the Central Universities(No.222201717003)。
文摘Exploiting non-precious metal catalysts with excellent oxygen reduction reaction(ORR)performance for energy devices is paramount essential for the green and sustainable society development.Herein,low-cost,high-performance biomass-derived ORR catalysts with an asymmetric Fe-N_(3)P configuration was prepared by a simple pyrolysis-etching technique,where carboxymethyl cellulose(CMC)was used as the carbon source,urea and 1,10-phenanthroline iron complex(FePhen)as additives,and Na_(3)PO_(4)as the phosphorus dopant and a pore-forming agent.The CMC-derived FeNPC catalyst displayed a large specific area(BET:1235 m^(2)g^(-1))with atomically dispersed Fe-N_(3)P active sites,which exhibited superior ORR activity and stability in alkaline solution(E_(1/2)=0.90 V vs.RHE)and Zn-air batteries(P_(max)=149 mW cm^(-2))to commercial Pt/C catalyst(E_(1/2)=0.87 V,P_(max)=118 mW cm^(-2))under similar experimental conditions.This work provides a feasible and costeffective route toward highly efficient ORR catalysts and their application to Zn-air batteries for energy conversion.
文摘Broadband transparent films play a pivotal role in various applications such as lenses and solar cells,particularly porous structured transparent films exhibit significant potential.This study investigates a porous SiO_(2) refractive index gradient anti-reflective film prepared by atomic layer deposition(ALD).A porous SiO_(2) film with gradual porosity was obtained by phosphoric acid etching of Al_(2)O_(3)/SiO_(2) multilayers with gradient Al2O3 ratios,achieving a gradual decrease in refractive index from the substrate to the surface.The film exhibited an average transmittance as high as 97.8%within the wavelength range from 320 nm to 1200 nm.The environmental adaptability was further enhanced by surface modification using rare earth oxide(REO)La_(2)O_(3),resulting in formation of a lotus leaf-like structure and achieving a water contact angle of 100.0°.These data proved that the modification significantly improved hydrophobic self-cleaning capability while maintaining exceptional transparency of the film.The surface structure of the modified film remained undamaged even after undergoing wipe testing,demonstrating its excellent surface durability.
基金supported by National Natural Science Foundation of China(No.523B2070,No.52225606).
文摘Polymeric perylene diimide(PDI)has been evidenced as a good candidate for photocatalytic water oxidation,yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration.Herein,with crystal and atomic structures of the self-assembled PDI revealed from the X-ray diffraction pattern,the electronic structure is theoretically illustrated by the first-principles density functional theory calculations,suggesting the suitable band structure and the direct electronic transition for efficient photocatalytic oxygen evolution over PDI.It is confirmed that the carbonyl O atoms on the conjugation structure serve as the active sites for oxygen evolution reaction by the crystal orbital Hamiltonian group analysis.The calculations of reaction free energy changes indicate that the oxygen evolution reaction should follow the reaction pathway of H_(2)O→^(*)OH→^(*)O→^(*)OOH→^(*)O_(2)with an overpotential of 0.81 V.Through an in-depth theoretical computational analysis in the atomic and electronic structures,the origin of photocatalytic oxygen evolution activity for PDI is well illustrated,which would help the rational design and modification of polymeric photocatalysts for efficient oxygen evolution.
文摘Single-atom catalysts(SACs),in which isolated metal atoms such as palladium(Pd)are anchored on solid supports,promise breakthroughs in energy conversion and catalysis.However,balancing their activity(reaction speed)and stability(longevity)remains challenging,as the interplay between metal atoms,supports,and reactants is poorly understood.
基金the Tangshan University Doctor Innovation Fund(Project Number:1402306).
文摘The so-called close-coupled gas atomization process involves melting a metal and using a high-pressure gas jet positioned close to the melt stream to rapidly break it into fine,spherical powder particles.This technique,adapted for blast furnace slag granulation using a circular seam nozzle,typically aims to produce solid slag particles sized 30–140μm,thereby allowing the utilization of slag as a resource.This study explores the atomization dynamics of liquid blast furnace slag,focusing on the effects of atomization pressure.Primary atomization is simulated using a combination of the Volume of Fluid(VOF)method and the Shear Stress Transport k-ωturbulence model,while secondary atomization is analyzed through the Discrete Phase Model(DPM).The results reveal that primary atomization progresses in three stages:the slag column transforms into an umbrella-shaped liquid film,whose leading edge fragments into particles while forming a cavity-like structure,which is eventually torn into ligaments.This primary deformation is driven by the interplay of airflow velocity in the recirculation zone and the guide tube outlet pressure(Fp).Increasing the atomization pressure amplifies airflow velocity,recirculation zone size,expansion and shock waves,though the guide tube outlet pressure variations remain irregular.Notably,at 4.5 MPa,the primary deformation is most pronounced.Secondary atomization yields finer slag particles as a result of more vigorous primary atomization.For this pressure,the smallest average particle size and the highest yield of particles within the target range(30–140μm)are achieved.
基金supported by the National Research Foundation of Korea(2022R1C1C2005786,RS-2023-00256106,RS-2023-00207831,RS-2024-00346153).
文摘Electrochemical nitrogen reduction reaction(ENRR)is emerging as a favorable option to the power-intensive Haber-Bosch process for ammonia synthesis.However,obstacles such as poor selectivity,low production rates,and competition against the hydrogen evolution reaction hinder its practical implementation.To address these,the design of highly active catalysts is critical.Single-atom catalysts(SACs)have shown great potential because of their maximized atom utilization,but their limited stability and low metal loading restrict their performances.On the other hand,dual-atom catalysts(DACs)are atomic catalysts with two metal atoms nearby and offer enhanced electrocatalytic performances by aligning with the N≡N bond to enhance N2 reduction efficiency,potentially overcoming the limitations of SAC.This review discusses recent advances in SACs and more importantly DACs for ENRR,highlighting their advantages,limitations,and the need for advanced characterization techniques to better understand catalyst behavior.The review concludes by underscoring the importance of research to optimize these catalysts for efficient and sustainable nitrogen fixation.
基金supported by the National Key R&D Program of China(2024YFB4106400)National Natural Science Foundation of China(22209200,52302331)。
文摘Electrocatalytic reduction of carbon dioxide(CO_(2))to carbon monoxide(CO)is an effective strategy to achieve carbon neutrality.High selective and low-cost catalysts for the electrocatalytic reduction of CO_(2)have received increasing attention.In contrast to the conventional tube furnace method,the high-temperature shock(HTS)method enables ultra-fast thermal processing,superior atomic efficiency,and a streamlined synthesis protocol,offering a simplified method for the preparation of high-performance single-atom catalysts(SACs).The reports have shown that nickel-based SACs can be synthesized quickly and conveniently using the HTS method,making their application in CO_(2)reduction reactions(CO_(2)RR)a viable and promising avenue for further exploration.In this study,the effect of heating temperature,metal loading and different nitrogen(N)sources on the catalyst morphology,coordination environment and electrocatalytic performance were investigated.Under optimal conditions,0.05Ni-DCD-C-1050 showed excellent performance in reducing CO_(2)to CO,with CO selectivity close to 100%(−0.7 to−1.0 V vs RHE)and current density as high as 130 mA/cm^(2)(−1.1 V vs RHE)in a flow cell under alkaline environment.
基金This research was made possible as a result of a generous grant from the Fundamental Research Funds for the Central Universities(Nos.2232024Y-01,2232024A-03)the National Science Fund for Excellent Young Scholars(No.22122101).
文摘Here we present a highly efficient protocol utilizing nickel-hydride hydrogen atom transfer catalysis for the regio-and enantioselective hydrofluorination of internal alkenes.This method efficiently assembles a wide array of enantioenrichedβ-fluoro amides with excellent regio-and enantioselectivity from internal unactivated alkenes.Mechanistic investigations suggest that this transformation proceeds via a NiHhydrogen atom transfer to alkene,followed by a stereoselective fluorine atom transfer process.The weak coordination effect of the tethered amide group is identified as a crucial factor governing the observed regio-and enantioselectivity.
文摘In this paper,we address the problem of multiple frequency-hopping(FH)signal parameters estimation in the presence of random missing observations.A space-time matrix with random missing observations is acquired by a uniform linear array(ULA).We exploit the inherent incomplete data processing capability of atomic norm soft thresholding(AST)to analyze the space-time matrix and complete the accurate estimation of the hopping time and frequency of the received FH signals.The hopping time is obtained by the sudden changes of the spatial information,which is implemented as the boundary to divide the time domain signal so that each segment of the signal is a superposition of time-invariant multiple components.Then,the frequency of multiple signal components can be estimated precisely by AST within each segment.After obtaining the above two parameters of the hopping time and the frequency of signals,the direction of arrival(DOA)can be directly calculated by them,and the network sorting can be realized.Results of simulation show that the proposed method is superior to the existing technology.Even when a large portion of data observations is missing,as the number of array elements increases,the proposed method still achieves acceptable accuracy of multi-FH signal parameters estimation.
基金supported by the National Natural Science Foundation of China (Grant Nos. 42188101, 42274211, 41974170, 42374184, 42122032, and 41974196)the Chinese Academy of Sciences (Grant Nos. QYZDJSSW-JSC028, XDA15052500, XDA17010301, and XDB41000000)+3 种基金the CNSA (Grant No. D050103)the Specialized Research Fund for State Key Laboratories of Chinathe Specialized Research Fund for Laboratory of Geospace Environment of the University of Science and Technology of Chinasupported by the International Space Science Institute (ISSI) in Bern and Beijing through the ISSI/ISSI-BJ International Team Project titled “Understanding the Mars Space Environment Through Multi-Spacecraft Measurements” (ISSI Team Project No. 23-582 and ISSI-BJ Team Project No. 58)
文摘Atmospheric escape plays a critical role in shaping the long-term climate evolution of Mars.Among the various escape mechanisms,energetic neutral atoms(ENAs)generated through charge exchange between solar wind ions and exospheric neutrals serve as an important diagnostic for ion-neutral interactions and upper atmospheric loss.This study presents direct observations of hydrogen ENAs(H-ENAs)on the dayside of Mars by using the Mars Ion and Neutral Particle Analyzer(MINPA)onboard China’s Tianwen-1 orbiter.By analyzing H-ENA data during a coronal mass ejection and a stream interaction region from December 29,2021,to January 1,2022,and comparing these data with MAVEN/SWIA(Mars Atmosphere and Volatile EvolutioN/Solar Wind Ion Analyzer)solar wind measurements,we examine the temporal evolution of H-ENA flux and the associated sputtered escape of atmospheric constituents.The observed H-ENA velocity is consistent with upstream solar wind ions,and the H-ENA-to-ion intensity ratio is used to infer variations in exospheric density,revealing a delayed response to enhanced solar wind activity.Penetrating H-ENA intensities reach up to 5.3×10^(6)s^(−1) cm^(−2),with energy fluxes on the order of(0.5-8.1)×10^(−3) mW/m^(2).The estimated oxygen sputtered escape rate driven by penetrating H-ENAs ranges from 5.5×10^(23)s^(−1) to 5.2×10^(24)s^(−1),comparable to or exceeding previous estimates based on penetrating ions.The findings highlight the need for low-altitude H-ENA observations to better quantify their atmospheric interactions and refine our understanding of nonthermal escape processes at Mars.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFA1407001)the Department of Science and Technology of Jiangsu Province(Grant No.BK20220032)+1 种基金support from the Guang Dong Basic and Applied Basic Research Foundation(Grant No.2023A1515010365)support from the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant No.KYCX25_1934。
文摘Heat dissipation highly relies on the thermal conductivity(κ)of materials.Materials with large bandgaps and signifcant atomic mass ratios,such as BAs,SiC,andθ-TaN,have attracted considerable attention due to their potential for achieving ultra-highκ,with BAs serving as a particularly representative example due to its unique combination of large bandgap and high thermal conductivity.In this paper,the efects of atomic mass modifcation on phonon bandgap andκare systematically investigated using a BAs model,accounting for both three-and four-phonon scattering processes.A 20%increase inκcan be obtained by substituting B,achieved through widening the phonon bandgap,which suppresses phonon scattering.Notably,the AAOO four-phonon scattering channel is more suppressed than the AAO three-phonon channel,leading to an increased phonon lifetime(τ).For As,κcan also be enhanced by 5%when replaced by lighter atoms,such as^(69)As,primarily due to the increased phonon group velocity(υ).We systematically clarify how atomic-mass-induced bandgap variations afectτ,υ,and thereforeκin wide-bandgap systems.Our work provides a specifc scheme for further improving the ultra-highκof materials with large bandgaps,which possesses great guiding signifcance.
