Optimal Time-Frequency Atom Search Based on Adaptive Genetic Algorithm

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.

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

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

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

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

Parametric adaptive time-frequency representation based on time-sheared Gabor atoms

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.

Metal-organic framework-based single-atom electro-/ photocatalysts: Synthesis, energy applications, and opportunities

Single-atom catalysts(SACs)have gained substantial attention because of their exceptional catalytic properties.However,the high surface energy limits their synthesis,thus creating significant challenges for further development.In the last few years,metal–organic frameworks(MOFs)have received significant consideration as ideal candidates for synthesizing SACs due to their tailorable chemistry,tunable morphologies,high porosity,and chemical/thermal stability.From this perspective,this review thoroughly summarizes the previously reported methods and possible future approaches for constructing MOF-based(MOF-derived-supported and MOF-supported)SACs.Then,MOF-based SAC's identification techniques are briefly assessed to understand their coordination environments,local electronic structures,spatial distributions,and catalytic/electrochemical reaction mechanisms.This review systematically highlights several photocatalytic and electrocatalytic applications of MOF-based SACs for energy conversion and storage,including hydrogen evolution reactions,oxygen evolution reactions,O_(2)/CO_(2)/N_(2) reduction reactions,fuel cells,and rechargeable batteries.Some light is also shed on the future development of this highly exciting field by highlighting the advantages and limitations of MOF-based SACs.

Single-atom Pt on carbon nanotubes for selective electrocatalysis

Utilizing supported single atoms as catalysts presents an opportunity to reduce the usage of critical raw materials such as platinum,which are essential for electrochemical reactions such as hydrogen oxidation reaction(HOR).Herein,we describe the synthesis of a Pt single electrocatalyst inside single-walled carbon nanotubes(SWCNTs)via a redox reaction.Characterizations via electron microscopy,X-ray photoelectron microscopy,and X-ray absorption spectroscopy show the single-atom nature of the Pt.The electrochemical behavior of the sample to hydrogen and oxygen was investigated using the advanced floating electrode technique,which minimizes mass transport limitations and gives a thorough insight into the activity of the electrocatalyst.The single-atom samples showed higher HOR activity than state-of-the-art 30%Pt/C while almost no oxygen reduction reaction activity in the proton exchange membrane fuel cell operating range.The selective activity toward HOR arose as the main fingerprint of the catalyst confinement in the SWCNTs.

Strong synergy between physical and chemical properties:Insight into optimization of atomically dispersed oxygen reduction catalysts

Atomically dispersed catalysts exhibit significant influence on facilitating the sluggish oxygen reduction reaction(ORR)kinetics with high atom economy,owing to remarkable attributes including nearly 100%atomic utilization and exceptional catalytic functionality.Furthermore,accurately controlling atomic physical properties including spin,charge,orbital,and lattice degrees of atomically dispersed catalysts can realize the optimized chemical properties including maximum atom utilization efficiency,homogenous active centers,and satisfactory catalytic performance,but remains elusive.Here,through physical and chemical insight,we review and systematically summarize the strategies to optimize atomically dispersed ORR catalysts including adjusting the atomic coordination environment,adjacent electronic orbital and site density,and the choice of dual-atom sites.Then the emphasis is on the fundamental understanding of the correlation between the physical property and the catalytic behavior for atomically dispersed catalysts.Finally,an overview of the existing challenges and prospects to illustrate the current obstacles and potential opportunities for the advancement of atomically dispersed catalysts in the realm of electrocatalytic reactions is offered.

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

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

Atom substitution of the solid-state electrolyte Li_(10)GeP_(2)S_(12)for stabilized all-solid-state lithium metal batteries

Solid-state electrolyte Li_(10)GeP_(2)S_(12)(LGPS)has a high lithium ion conductivity of 12 mS cm^(-1)at room temperature,but its inferior chemical stability against lithium metal anode impedes its practical application.Among all solutions,Ge atom substitution of the solid-state electrolyte LGPS stands out as the most promising solution to this interface problem.A systematic screening framework for Ge atom substitution including ionic conductivity,thermodynamic stability,electronic and mechanical properties is utilized to solve it.For fast screening,an enhanced model Dop Net FC using chemical formulas for the dataset is adopted to predict ionic conductivity.Finally,Li_(10)SrP_(2)S_(12)(LSrPS)is screened out,which has high lithium ion conductivity(12.58 mS cm^(-1)).In addition,an enhanced migration of lithium ion across the LSr PS/Li interface is found.Meanwhile,compared to the LGPS/Li interface,LSrPS/Li interface exhibits a larger Schottky barrier(0.134 eV),smaller electron transfer region(3.103?),and enhanced ability to block additional electrons,all of which contribute to the stabilized interface.The applied theoretical atom substitution screening framework with the aid of machine learning can be extended to rapid determination of modified specific material schemes.

Optimizing high-coordination shell of Co-based single-atom catalysts for efficient ORR and zinc-air batteries

Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and charge distribution by introducing relatively weak electronegative atoms into the first/second shell is an efficient way,but it remains challenging for elucidating the underlying mechanism of interaction.Herein,a practical strategy was reported to rationally design single cobalt atoms coordinated with both phosphorus and nitrogen atoms in a hierarchically porous carbon derived from metal-organic frameworks.X-ray absorption spectrum reveals that atomically dispersed Co sites are coordinated with four N atoms in the first shell and varying numbers of P atoms in the second shell(denoted as Co-N/P-C).The prepared catalyst exhibits excellent oxygen reduction reaction(ORR)activity as well as zinc-air battery performance.The introduction of P atoms in the Co-SACs weakens the interaction between Co and N,significantly promoting the adsorption process of ^(*)OOH,resulting in the acceleration of reaction kinetics and reduction of thermodynamic barrier,responsible for the increased intrinsic activity.Our discovery provides insights into an ultimate design of single-atom catalysts with adjustable electrocatalytic activities for efficient electrochemical energy conversion.

Synthesis and Modulation of Low-Dimensional Transition Metal Chalcogenide Materials via Atomic Substitution

In recent years,low-dimensional transition metal chalcogenide(TMC)materials have garnered growing research attention due to their superior electronic,optical,and catalytic properties compared to their bulk counterparts.The controllable synthesis and manipulation of these materials are crucial for tailoring their properties and unlocking their full potential in various applications.In this context,the atomic substitution method has emerged as a favorable approach.It involves the replacement of specific atoms within TMC structures with other elements and possesses the capability to regulate the compositions finely,crystal structures,and inherent properties of the resulting materials.In this review,we present a comprehensive overview on various strategies of atomic substitution employed in the synthesis of zero-dimensional,one-dimensional and two-dimensional TMC materials.The effects of substituting elements,substitution ratios,and substitution positions on the structures and morphologies of resulting material are discussed.The enhanced electrocatalytic performance and photovoltaic properties of the obtained materials are also provided,emphasizing the role of atomic substitution in achieving these advancements.Finally,challenges and future prospects in the field of atomic substitution for fabricating low-dimensional TMC materials are summarized.

A frequency servo SoC with output power stabilization loop technology for miniaturized atomic clocks

A frequency servo system-on-chip(FS-SoC)featuring output power stabilization technology is introduced in this study for high-precision and miniaturized cesium(Cs)atomic clocks.The proposed power stabilization loop(PSL)technique,incorporating an off-chip power detector(PD),ensures that the output power of the FS-SoC remains stable,mitigating the impact of power fluctuations on the atomic clock's stability.Additionally,a one-pulse-per-second(1PPS)is employed to syn-chronize the clock with GPS.Fabricated using 65 nm CMOS technology,the measured phase noise of the FS-SoC stands at-69.5 dBc/Hz@100 Hz offset and-83.9 dBc/Hz@1 kHz offset,accompanied by a power dissipation of 19.7 mW.The Cs atomic clock employing the proposed FS-SoC and PSL obtains an Allan deviation of 1.7×10^(-11) with 1-s averaging time.

Atomically dispersed Ni electrocatalyst for superior urea-assisted water splitting

Urea oxidation reaction(UOR) has been selected as substitution for oxygen evolution reaction ascribing to its low thermodynamic voltage as well as utilization of nickel as electrocatalyst.Herein,we report the formation of nickel single atoms(Ni-SAs) as exceptional bifunctional electrocatalyst toward UOR and hydrogen evolution reaction(HER) in urea-assisted water splitting.In UOR catalysis,Ni-SAs perform a superior catalytic performance than Ni-NP/NC and Pt/C ascribing to the formation of HOO-Ni-N_(4) structure evidenced by in-situ Raman spectroscopy,corresponding to a boosted mass activity by 175-fold at 1.4 V vs.RHE than Ni-NP/NC.Furthermore,Ni-SAs requires only 450 mV overpotential to obtain HER current density of 500 mA cm^(-2).136 mA cm^(-2) is achieved in urea-assisted water splitting at1.7 V for Ni-SAs,boosted by 5.7 times than Pt/C-IrO_(2) driven water splitting.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO_(2)Sensing

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction.Herein,we present an ingen-ious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO_(2)sensing.We found that the single Pt sites on the MoS_(2)surface can induce easier volatiliza-tion of adjacent S species to activate the whole inert S plane.Reversely,the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms,thus creating a combined system involving S vacancy-assisted single Pt sites(Pt-Vs)to synergistically improve the adsorption ability of SO_(2)gas molecules.Further-more,in situ Raman,ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS_(2)supports in SO_(2)gas atmosphere.Equipped with wireless-sensing modules,the final Pt1-MoS_(2)-def sensors array can further realize real-time monitoring of SO_(2)levels and cloud-data storage for plant growth.Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

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

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

A simple atomization approach enables monolayer dispersion of nano graphenes in cementitious composites with excellent strength gains

Carbon nano additives(CNAs)are critical to achieving the unique properties of functionalized composites,however,controlling the dispersion of CNAs in material matrix is always a challenging task.In this study,a simple atomization approach was successfully developed to promote the dispersion efficiency of graphene nanoplatelets(GNPs)in cement composites.This atomization approach can be integrated with the direct,indirect and combined ultrasonic stirrings in a homemade automatic stirring-atomization device.Mechanical and microstructure tests were performed on hardened cement pastes blended with GNPs in different stirring and mixing approaches.Results show that the direct ultrasonic stirrings enabled more homogeneous dispersions of GNP particles with a smaller size for a longer duration.The atomized droplets with the mean size of~100μm largely mitigated GNPs’agglomerations.Monolayer GNPs were observed in the cement matrix with the strength gain by up to 54%,and the total porosity decrease by 21%in 0.3 wt%GNPs dosage.The greatly enhanced dispersion efficiency of GNPs in cement also raised the cement hydration.This work provides an effective and manpower saving technique toward dispersing CNAs in engineering materials with great industrialization prospects.

Precise construction of RuPt dual single-atomic sites to optimize oxygen electrocatalytic behaviors for high-performance Zn-air batteries

The development of redox bifunctional electrocatalysts with high performance,low cost,and long lifetimes is essential for achieving clean energy goals.This study proposed an atom capture strategy for anchoring dual single atoms(DSAs)in a zinc-zeolitic imidazolate framework(Zn-ZIF),followed by calcination under an N_(2) atmosphere to synthesize ruthenium-platinum DSAs supported on a nitrogendoped carbon substrate(RuPt DSAs-NC).Theoretical calculations showed that the degree of Ru 5dxz-~*O 2p_x orbital hybridization was high when^(*)O was adsorbed at the Ru site,indicating enhanced covalent hybridization of metal sites and oxygen ligands,which benefited the adsorption of intermediate species.The presence of the RuPtN_6 active center optimized the absorption-desorption behavior of intermediates,improving the electrocatalytic performance of the oxygen reduction reaction(ORR)and the oxygen evolution reaction(DER),RuPt DSAs-NC exhibited a 0.87 V high half-wave potential and a 268 mV low overpotential at 10 mA cm^(-2)in an alkaline environment.Furthermore,rechargeable zinc-air batteries(ZABs)achieved a peak power density of 171 MW cm^(-2).The RuPt DSAs-NC demonstrated long-term cycling for up to 500 h with superior round-trip efficiency.This study provided an effective structural design strategy to construct DSAs active sites for enhanced electrocata lytic performance.

Atomic layer deposition in advanced display technologies:from photoluminescence to encapsulation

Driven by the growing demand for next-generation displays,the development of advanced luminescent materials with exceptional photoelectric properties is rapidly accelerating,with such materials including quantum dots and phosphors,etc.Nevertheless,the primary challenge preventing the practical application of these luminescent materials lies in meeting the required durability standards.Atomic layer deposition(ALD)has,therefore,been employed to stabilize luminescent materials,and as a result,flexible display devices have been fabricated through material modification,surface and interface engineering,encapsulation,cross-scale manufacturing,and simulations.In addition,the appropriate equipment has been developed for both spatial ALD and fluidized ALD to satisfy the low-cost,high-efficiency,and high-reliability manufacturing requirements.This strategic approach establishes the groundwork for the development of ultra-stable luminescent materials,highly efficient light-emitting diodes(LEDs),and thin-film packaging.Ultimately,this significantly enhances their potential applicability in LED illumination and backlighted displays,marking a notable advancement in the display industry.

Superatomic-based chirality:Asymmetric structures constructed by superatoms

Chirality is one of the fundamental properties of molecules traditionally con-structed from atoms.Here,we report for thefirst time the successful construction of asymmetric chiral structures utilizing highly symmetric endohedral metallo-fullerene superatoms based on their own bonding properties.Specifically,stable mirror-symmetric sinister and rectus structures are obtained by selecting a super-atom capable of forming four chemical bonds as the chiral center.Further analysis shows that the chiral vibration frequency of superatomic assemblies can be as low as a few wavenumbers,which greatly expands the range of chiral spectra com-pared to atom-based molecules.We term this type of chirality based on superatoms as“superatomic-based chirality”.It is anticipated that this work will significantly expand the variety of chiral structures at the atomic level.

Single-atom photo-catalysts:Synthesis,characterization,and applications

Single-atom catalysts(SACs)are gaining popularity in catalytic reactions due to their nearly 100%atomic utilization and defined active sites,which provide great convenience for studying the catalytic mechanism of catalysts.However,SACs still present challenges such as complex formation processes,low loading and easy agglomeration of catalysts.Herein,we systematically discuss the synthesis methods for SACs,including coprecipitation,impregnation,atomic layer deposition,pyrolysis and Anti-Ostwald ripening etc.Various techniques for characterizing single-atom catalysts(SACs)are described in detail.The utilization of individual atoms in various photocatalytic reactions and their mechanisms of action in different reactions are explained.The purpose of this review is to introduce single-atom synthesis methods,characterization techniques,specific catalytic action and their applications in the direction of photocatalysis,and to provide a reference for the industrialization of photocatalytic single-atoms,which is currently impossible,in the hope of promoting further development of photocatalytic single-atoms.