Heterogeneities of grain boundary contact for simulation of laboratoryscale mechanical behavior of granitic rocks

From a practical point of view,grain structure heterogeneities are key parameters that control the rock response and still remains a challenge to incorporate in a quantitative manner.One of the less discussed topics in the context of the grain-based model(GBM)in the particle flow code(PFC)is the contact heterogeneities and the appropriate contact model to mimic the grain boundary behavior.Generally,the smooth joint(SJ)model and linear parallel bond(LPB)model are used to simulate the grain boundary behavior.However,the literature does not document the suitability of different models for specific problems.Another challenge in implementing GBM in PFC is that only a single bonding parameter is used at the grain boundaries.The aim of this study is to investigate the responses of a laboratory-scale specimen with SJ and LPB models,considering grain boundary heterogeneous and homogeneous contact parameters.Uniaxial and biaxial compression tests are performed to calibrate the response of Creighton granite.The stressestrain curves,volumetric dilation,inter-crack(crack in the grain boundary),and intra-crack(crack within the grain)development,and failure patterns associated with different contact models are examined.It was found that both the SJ and LPB models can reproduce the pre-peak behavior observed for a granitic rock type.However,the LPB model is unable to reproduce the post-peak behavior.Due to the large interlocking effect originating from the balls in contact and the ball size in the LPB model,local dilation is induced at the grain boundaries.This overestimates the volumetric dilation and residual shear strength.The LPB model tends to result in discontinuous inter-cracks and stress localization in the rock specimen,resulting in fine fragments at the rock surface during failure.

Insight into the spoilage heterogeneity of meat-borne bacteria isolates with high-producing collagenase

Chilled chicken is inevitably contaminated by microorganisms during slaughtering and processing,resulting in spoilage.Cutting parts of chilled chicken,especially wings,feet,and other skin-on products,are abundant in collagen,which may be the primary target for degradation by spoilage microorganisms.In this work,a total of 17 isolates of spoilage bacteria that could secrete both collagenase and lipase were determined by raw-chicken juice agar(RJA)method,and the results showed that 7 strains of Serratia,Aeromonas,and Pseudomonas could significantly decompose the collagen ingredients.The gelatin zymography showed that Serratia liquefaciens(F5)and(G7)had apparent degradation bands around 50 kDa,and Aeromonas veronii(G8)and Aeromonas salmonicida(H8)had a band around.65 and 95 kDa,respectively.The lipase and collagenase activities were detected isolate-by-isolate,with F5 showing the highest collagenase activity.For spoilage ability on meat in situ,F5 performed strongest in spoilage ability,indicated by the total viable counts,total volatile basic nitrogen content,sensory scores,lipase,and collagenase activity.This study provides a theoretical basis for spoilage heterogeneity of strains with high-producing collagenase in meat.

Enabling heterogeneous catalysis to achieve carbon neutrality: Directional catalytic conversion of CO_(2) into carboxylic acids

The increase in anthropogenic carbon dioxide(CO_(2))emissions has exacerbated the deterioration of the global environment,which should be controlled to achieve carbon neutrality.Central to the core goal of achieving carbon neutrality is the utilization of CO_(2) under economic and sustainable conditions.Recently,the strong need for carbon neutrality has led to a proliferation of studies on the direct conversion of CO_(2) into carboxylic acids,which can effectively alleviate CO_(2) emissions and create high-value chemicals.The purpose of this review is to present the application prospects of carboxylic acids and the basic principles of CO_(2) conversion into carboxylic acids through photo-,electric-,and thermal catalysis.Special attention is focused on the regulation strategy of the activity of abundant catalysts at the molecular level,inspiring the preparation of high-performance catalysts.In addition,theoretical calculations,advanced technologies,and numerous typical examples are introduced to elaborate on the corresponding process and influencing factors of catalytic activity.Finally,challenges and prospects are provided for the future development of this field.It is hoped that this review will contribute to a deeper understanding of the conversion of CO_(2) into carboxylic acids and inspire more innovative breakthroughs.

Synergy of heterogeneous Co/Ni dual atoms enabling selective C-O bond scission of lignin coupling with in-situ N-functionalization

Selective cleavage of Csp^(2)-OCH_(3)bond in lignin without breaking other types of C-O bonds followed by N-functionalization is fascinating for on-purpose valorization of biomass.Here,a Co/Ni-based dual-atom catalyst CoNiDA@NC prepared by in-situ evaporation and acid-etching of metal species from tailor-made metal–organic frameworks was efficient for reductive upgrading of various lignin-derived phenols to cyclohexanols(88.5%–99.9%yields),which had ca.4 times higher reaction rate than the single-atom catalyst and was superior to state-of-the-art heterogeneous catalysts.The synergistic catalysis of Co/Ni dual atoms facilitated both hydrogen dissociation and hydrogenolysis steps,and could optimize adsorption configuration of lignin-derived methoxylated phenols to further favor the Csp^(2)-OCH_(3)cleavage,as elaborated by theoretical calculations.Notably,the CoNi_(DA)@NC catalyst was highly recyclable,and exhibited excellent demethoxylation performance(77.1%yield)in real lignin monomer mixtures.Via in-situ cascade conversion processes assisted by dual-atom catalysis,various high-value N-containing chemicals,including caprolactams and cyclohexylamines,could be produced from lignin.

Multiple Tin Compounds Modified Carbon Fibers to Construct Heterogeneous Interfaces for Corrosion Prevention and Electromagnetic Wave Absorption

Currently,the demand for electromagnetic wave(EMW)absorbing materials with specific functions and capable of withstanding harsh environments is becoming increasingly urgent.Multi-component interface engineering is considered an effective means to achieve high-efficiency EMW absorption.However,interface modulation engineering has not been fully discussed and has great potential in the field of EMW absorption.In this study,multi-component tin compound fiber composites based on carbon fiber(CF)substrate were prepared by electrospinning,hydrothermal synthesis,and high-temperature thermal reduction.By utilizing the different properties of different substances,rich heterogeneous interfaces are constructed.This effectively promotes charge transfer and enhances interfacial polarization and conduction loss.The prepared SnS/SnS_(2)/SnO_(2)/CF composites with abundant heterogeneous interfaces have and exhibit excellent EMW absorption properties at a loading of 50 wt%in epoxy resin.The minimum reflection loss(RL)is−46.74 dB and the maximum effective absorption bandwidth is 5.28 GHz.Moreover,SnS/SnS_(2)/SnO_(2)/CF epoxy composite coatings exhibited long-term corrosion resistance on Q235 steel surfaces.Therefore,this study provides an effective strategy for the design of high-efficiency EMW absorbing materials in complex and harsh environments.

Role of heterogenous microstructure and deformation behavior in achieving superior strength-ductility synergy in zinc fabricated via laser powder bed fusion

Zinc(Zn)is considered a promising biodegradable metal for implant applications due to its appropriate degradability and favorable osteogenesis properties.In this work,laser powder bed fusion(LPBF)additive manufacturing was employed to fabricate pure Zn with a heterogeneous microstructure and exceptional strength-ductility synergy.An optimized processing window of LPBF was established for printing Zn samples with relative densities greater than 99%using a laser power range of 80∼90 W and a scanning speed of 900 mm s−1.The Zn sample printed with a power of 80 W at a speed of 900 mm s−1 exhibited a hierarchical heterogeneous microstructure consisting of millimeter-scale molten pool boundaries,micrometer-scale bimodal grains,and nanometer-scale pre-existing dislocations,due to rapid cooling rates and significant thermal gradients formed in the molten pools.The printed sample exhibited the highest ductility of∼12.1%among all reported LPBF-printed pure Zn to date with appreciable ultimate tensile strength(∼128.7 MPa).Such superior strength-ductility synergy can be attributed to the presence of multiple deformation mechanisms that are primarily governed by heterogeneous deformation-induced hardening resulting from the alternative arrangement of bimodal Zn grains with pre-existing dislocations.Additionally,continuous strain hardening was facilitated through the interactions between deformation twins,grains and dislocations as strain accumulated,further contributing to the superior strength-ductility synergy.These findings provide valuable insights into the deformation behavior and mechanisms underlying exceptional mechanical properties of LPBF-printed Zn and its alloys for implant applications.

Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.

Catalytic effect in lithium metal batteries: From heterogeneous catalyst to homogenous catalyst

Lithium metal batteries are regarded as prominent contenders to address the pressing needs owing to the high theoretical capacity.Toward the broader implementation,the primary obstacle lies in the intricate multi-electron,multi-step redox reaction associated with sluggish conversion kinetics,subsequently giving rise to a cascade of parasitic issues.In order to smooth reaction kinetics,catalysts are widely introduced to accelerate reaction rate via modulating the energy barrier.Over past decades,a large amount of research has been devoted to the catalyst design and catalytic mechanism exploration,and thus the great progress in electrochemical performance has been realized.Therefore,it is necessary to make a comprehensive review toward key progress in catalyst design and future development pathway.In this review,the basic mechanism of lithium metal batteries is provided along with corresponding advantages and existing challenges detailly described.The main catalysts employed to accelerate cathode reaction with emphasis on their catalytic mechanism are summarized as well.Finally,the rational design and innovative direction toward efficient catalysts are suggested for future application in metal-sulfur/gas battery and beyond.This review is expected to drive and benefit future research on rational catalyst design with multi-parameter synergistic impacts on the activity and stability of next-generation metal battery,thus opening new avenue for sustainable solution to climate change,energy and environmental issues,and the potential industrial economy.

Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

Silicon-based optoelectronic heterogeneous integration for optical interconnection

The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.

Intelligent Dynamic Heterogeneous Redundancy Architecture for IoT Systems

The conventional dynamic heterogeneous redundancy(DHR)architecture suffers from the security threats caused by the stability differences and similar vulnerabilities among the executors.To overcome these challenges,we propose an intelligent DHR architecture,which is more feasible by intelligently combining the random distribution based dynamic scheduling algorithm(RD-DS)and information weight and heterogeneity based arbitrament(IWHA)algorithm.In the proposed architecture,the random distribution function and information weight are employed to achieve the optimal selection of executors in the process of RD-DS,which avoids the case that some executors fail to be selected due to their stability difference in the conventional DHR architecture.Then,through introducing the heterogeneity to restrict the information weights in the procedure of the IWHA,the proposed architecture solves the common mode escape issue caused by the existence of multiple identical error output results of similar vulnerabilities.The experimental results characterize that the proposed architecture outperforms in heterogeneity,scheduling times,security,and stability over the conventional DHR architecture under the same conditions.

Individual dynamics and local heterogeneity provide a microscopic view of the epidemic spreading

The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features,their treatment usually lacks spatiotemporal variation.Here,we propose a stochastic individual dynamical(SID)model to mimic the random and heterogeneous nature of epidemic propagation.The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual.Using this model,we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak.The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective,enabling a quantitative assessment of different interventions.Seemingly,this model is also applicable to studying stochastic processes at the “meter scale”,e.g.,human society’s collective dynamics.

Editorial:Transcriptome analysis in tumor microenvironment and tumor heterogeneity

Cancer,a disease as intricate as it is devastating,continues to challenge the medical and scientific community[1].Its complex nature is epitomized by the tumor microenvironment and tumor heterogeneity.As we delve deeper into the realms of cancer research,the advent of transcriptome analysis has emerged as a powerful torchbearer,illuminating our understanding of these enigmatic facets of cancer biology[2].

Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network:A Comprehensive Survey

Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance,transportation,healthcare,education,and supply chain management.Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges.However,the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes.There is the biggest challenge of data integrity and scalability,including significant computing complexity and inapplicable latency on regional network diversity,operating system diversity,bandwidth diversity,node diversity,etc.,for decision-making of data transactions across blockchain-based heterogeneous networks.Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems.To address these issues,today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain.The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network.This paper proposes a full-fledged taxonomy to identify the main obstacles,research gaps,future research directions,effective solutions,andmost relevant blockchain-enabled cybersecurity systems.In addition,Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper tomeet the goal of maintaining optimal performance data transactions among organizations.Overall,this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network.

Assessment and Visualization of Ki67 Heterogeneity in Breast Cancers through Digital Image Analysis

The Ki67 index (KI) is a standard clinical marker for tumor proliferation;however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.

Effects of individual heterogeneity on social contagions

Despite having significant effects on social contagions,individual heterogeneity has frequently been overlooked in earlier studies.To better understand the complexity of social contagions,a non-Markovian model incorporating heterogeneous social influence and adoption thresholds is introduced.For theoretical analysis,a generalized edge-based compartmental theory which considers the heterogeneities of social influence and adoption thresholds is developed.Focusing on the final adoption size,the critical propagation probability,and the phase transition type,social contagions for adoption thresholds that follow normal distributions with various standard deviations,follow various distributions,and correlate with degrees are investigated.When thresholds follow normal distributions,a larger standard deviation results in a larger final adoption size when the information propagation probability is relatively low.However,when the information propagation probability is relatively high,a larger standard deviation results in a smaller final adoption size.When thresholds follow various distributions,crossover phenomena in phase transition are observed when investigating the relationship of the final adoption size versus the average adoption threshold for some threshold distributions.When thresholds are correlated with degrees,similar crossover phenomena occur when investigating the relationship of the final adoption size versus the degree correlation index.Additionally,we find that increasing the heterogeneity of social influence suppresses the effects of adoption threshold heterogeneity on social contagions in three cases.Our theory predictions agree well with the simulation results.

Dynamics and synchronization in a memristor-coupled discrete heterogeneous neuron network considering noise

Research on discrete memristor-based neural networks has received much attention.However,current research mainly focuses on memristor–based discrete homogeneous neuron networks,while memristor-coupled discrete heterogeneous neuron networks are rarely reported.In this study,a new four-stable discrete locally active memristor is proposed and its nonvolatile and locally active properties are verified by its power-off plot and DC V–I diagram.Based on two-dimensional(2D)discrete Izhikevich neuron and 2D discrete Chialvo neuron,a heterogeneous discrete neuron network is constructed by using the proposed discrete memristor as a coupling synapse connecting the two heterogeneous neurons.Considering the coupling strength as the control parameter,chaotic firing,periodic firing,and hyperchaotic firing patterns are revealed.In particular,multiple coexisting firing patterns are observed,which are induced by different initial values of the memristor.Phase synchronization between the two heterogeneous neurons is discussed and it is found that they can achieve perfect synchronous at large coupling strength.Furthermore,the effect of Gaussian white noise on synchronization behaviors is also explored.We demonstrate that the presence of noise not only leads to the transition of firing patterns,but also achieves the phase synchronization between two heterogeneous neurons under low coupling strength.

A geochemical perspective on the genesis of Cenozoic basic volcanism in northeastern Turkey:an overview of metasomatism and heterogeneity of the sub-continental lithospheric mantle in a post-collisional setting

The post-collisional Cenozoic basic volcanic rocks in NE Turkey show temporal variations in whole-rock lithophile element and highly siderophile element(HSE)systematics that are mainly associated with the nature of sub-continental lithospheric mantle(SCLM)sources and parental melt generation.So far,the traditional whole-rock lithophile geochemical data of these basic volcanic rocks have provided important constraints on the nature of SCLM sources.Integrated lithophile element and HSE geochemical data of these basic volcanic rocks also reveal the heterogeneity of the SCLM source,which is principally related to variable metasomatism resulting from previous subduction(s)and post-collisional mantle-crust interactions in an extensional setting.Lithophile element geochemical features suggest that the parental magmas have derived from metasomatized spinel-to garnet-bearing SCLM sources for Eocene and Miocene basic volcanic rocks with subduction signatures whereas originated from spinel-to garnet-bearing SCLM sources for Mio-Pliocene and Plio-Quaternary basaltic volcanic rocks without the subduction signature.Lithophile element and HSE geo-chemistry also reveal that Eocene and Miocene basic vol-canic rocks were affected by more pronounced crustal contamination than the basaltic volcanic rocks of Mio-Pliocene and Quaternary.Furthermore,the integrated lithophile element and HSE compositions of these basic volcanic rocks,together with the regional asymmetric lithospheric delamination model,reveal that the compositional variation(especially due to metasomatism)was significant temporally in the heterogeneity of the SCLM sources from which parental magmas formed during the Cenozoic era.

Phase reconfiguration of heterogeneous CoFeS/CoNiS nanoparticles for superior battery-type supercapacitors

Developing advanced battery-type materials with abundant active sites,high conductivity,versatile morphologies,and hierarchically porous structures is crucial for realizing high-quality hybrid supercapacitors.Herein,heterogeneous FeS@NiS is synthesized by cationic Co doping via surface-structure engineering.The density functional theory(DFT)theoretical calculations are firstly performed to predict the advantages of Co dopant by improving the OH^(−)adsorption properties and adjusting electronic structure,benefiting ions/electron transfer.The dynamic surface evolution is further explored which demonstrates that CoFeS@CoNiS could be quickly reconstructed to Ni(Co)Fe_(2)O_(4)during the charging process,while the unstable structure of the amorphous Ni(Co)Fe_(2)O_(4)results in partial conversion to Ni/Co/FeOOH at high potentials,which contributes to the more reactive active site and good structural stability.Thus,the free-standing electrode reveals excellent electrochemical performance with a superior capacity(335.6 mA h g^(−1),2684 F g^(−1))at 3 A g^(−1).Furthermore,the as-fabricated device shows a quality energy density of 78.1 W h kg^(−1)at a power density of 750 W kg^(−1)and excellent cycle life of 92.1%capacitance retention after 5000 cycles.This work offers a facile strategy to construct versatile morphological structures using electrochemical activation and holds promising applications in energy-related fields.

Sulfur vacancies and heterogeneous interfaces promote high performance sodium storage of bimetallic chalcogenide hollow nanospheres

Transition metal sulfides have high theoretical capacities and are considered as potential anode materials for sodium-ion batteries.However,due to low inherent conductivity and significant volume expansion,the electrochemical performance is greatly limited.In this study,a nickel/manganese sulfide material(Ni_(0.96)S_(x)/MnS_(y)-NC)with adjustable sulfur vacancies and heterogeneous hollow spheres was prepared using a simple method.The introduction of a concentration-adjustable sulfur vacancy enables the generation of a heterogeneous interface between bimetallic sulfide and sulfur vacancies.This interface collectively creates an internal electric field,improving the mobility of electrons and ions,increasing the number of electrochemically active sites,and further optimizing the performance of Na~+storage.The direction of electron flow is confirmed by Density functional theory(DFT)calculations.The hollow nano-spherical material provides a buffer for expansion,facilitating rapid transfer kinetics.Our innovative discovery involves the interaction between the ether-based electrolyte and copper foil,leading to the formation of Cu_9S_5,which grafts the active material and copper current collector,reinforcing mechanical supporting.This results in a new heterostructure of Cu_9S_5 with Ni_(0.96)S_(x)/MnS_(y),contributing to the stabilization of structural integrity for long-cycle performance.Therefore,Ni_(0.96)S_(x)/MnS_(y)-NC exhibits excellent electrochemical properties following our modification route.Regarding stability performance,Ni0_(.96)S_(x)/MnS_(y)-NC demonstrates an average decay rate of 0.00944%after 10,000 cycles at an extremely high current density of 10000 mA g^(-1),A full cell with a high capacity of 304.2 mA h g^(-1)was also successfully assembled by using Na_(3)V_(2)(PO_(4))_(3)/C as the cathode.This study explores a novel strategy for interface/vacancy co-modification in the fabrication of high-performance sodium-ion batteries electrode.