Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their sim...Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their simplicity and efficiency.This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering performance.The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)algorithm.Firstly,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population diversity.Secondly,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence speed.Finally,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation effectively.The performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic algorithms.To further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven datasets.Experimental results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering approaches.This study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.展开更多
To ensure a long-term safety and reliability of electric vehicle and energy storage system,an accurate estimation of the state of health(SOH)for lithium-ion battery is important.In this study,a method for estimating t...To ensure a long-term safety and reliability of electric vehicle and energy storage system,an accurate estimation of the state of health(SOH)for lithium-ion battery is important.In this study,a method for estimating the lithium-ion battery SOH was proposed based on an improved extreme learning machine(ELM).Input weights and hidden layer biases were generated randomly in traditional ELM.To improve the estimation accuracy of ELM,the differential evolution algorithm was used to optimize these parameters in feasible solution spaces.First,incremental capacity curves were obtained by incremental capacity analysis and smoothed by Gaussian filter to extract health interests.Then,the ELM based on differential evolution algorithm(DE-ELM model)was used for a lithium-ion battery SOH estimation.At last,four battery historical aging data sets and one random walk data set were employed to validate the prediction performance of DE-ELM model.Results show that the DE-ELM has a better performance than other studied algorithms in terms of generalization ability.展开更多
In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding struct...In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding structures typically need to be lightweight,miniaturized,and radiation-protected,which is a multi-parameter and multi-objective optimization problem.The conventional multi-objective(two or three objectives)optimization method for radiation-shielding design exhibits limitations for a number of optimization objectives and variable parameters,as well as a deficiency in achieving a global optimal solution,thereby failing to meet the requirements of shielding optimization for newly developed reactors.In this study,genetic and artificial bee-colony algorithms are combined with a reference-point-selection strategy and applied to the many-objective(having four or more objectives)optimal design of reactor radiation shielding.To validate the reliability of the methods,an optimization simulation is conducted on three-dimensional shielding structures and another complicated shielding-optimization problem.The numerical results demonstrate that the proposed algorithms outperform conventional shielding-design methods in terms of optimization performance,and they exhibit their reliability in practical engineering problems.The many-objective optimization algorithms developed in this study are proven to efficiently and consistently search for Pareto-front shielding schemes.Therefore,the algorithms proposed in this study offer novel insights into improving the shielding-design performance and shielding quality of new reactor types.展开更多
Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi...Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.展开更多
With the development of economic globalization,distributedmanufacturing is becomingmore andmore prevalent.Recently,integrated scheduling of distributed production and assembly has captured much concern.This research s...With the development of economic globalization,distributedmanufacturing is becomingmore andmore prevalent.Recently,integrated scheduling of distributed production and assembly has captured much concern.This research studies a distributed flexible job shop scheduling problem with assembly operations.Firstly,a mixed integer programming model is formulated to minimize the maximum completion time.Secondly,a Q-learning-assisted coevolutionary algorithmis presented to solve themodel:(1)Multiple populations are developed to seek required decisions simultaneously;(2)An encoding and decoding method based on problem features is applied to represent individuals;(3)A hybrid approach of heuristic rules and random methods is employed to acquire a high-quality population;(4)Three evolutionary strategies having crossover and mutation methods are adopted to enhance exploration capabilities;(5)Three neighborhood structures based on problem features are constructed,and a Q-learning-based iterative local search method is devised to improve exploitation abilities.The Q-learning approach is applied to intelligently select better neighborhood structures.Finally,a group of instances is constructed to perform comparison experiments.The effectiveness of the Q-learning approach is verified by comparing the developed algorithm with its variant without the Q-learning method.Three renowned meta-heuristic algorithms are used in comparison with the developed algorithm.The comparison results demonstrate that the designed method exhibits better performance in coping with the formulated problem.展开更多
In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classificati...In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classification methods that utilize evolutionary algorithms(EAs)for gene expression profiles in cancer or medical applications based on research motivations,challenges,and recommendations.Relevant studies were retrieved from four major academic databases-IEEE,Scopus,Springer,and ScienceDirect-using the keywords‘cancer classification’,‘optimization’,‘FS’,and‘gene expression profile’.A total of 67 papers were finally selected with key advancements identified as follows:(1)The majority of papers(44.8%)focused on developing algorithms and models for FS and classification.(2)The second category encompassed studies on biomarker identification by EAs,including 20 papers(30%).(3)The third category comprised works that applied FS to cancer data for decision support system purposes,addressing high-dimensional data and the formulation of chromosome length.These studies accounted for 12%of the total number of studies.(4)The remaining three papers(4.5%)were reviews and surveys focusing on models and developments in prediction and classification optimization for cancer classification under current technical conditions.This review highlights the importance of optimizing FS in EAs to manage high-dimensional data effectively.Despite recent advancements,significant limitations remain:the dynamic formulation of chromosome length remains an underexplored area.Thus,further research is needed on dynamic-length chromosome techniques for more sophisticated biomarker gene selection techniques.The findings suggest that further advancements in dynamic chromosome length formulations and adaptive algorithms could enhance cancer classification accuracy and efficiency.展开更多
The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the micro...The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.展开更多
Gradient magnetic heterointerfaces have injected infinite vitality in optimizing impedance matching,adjusting dielectric/magnetic resonance and promoting electromagnetic(EM)wave absorption,but still exist a significan...Gradient magnetic heterointerfaces have injected infinite vitality in optimizing impedance matching,adjusting dielectric/magnetic resonance and promoting electromagnetic(EM)wave absorption,but still exist a significant challenging in regulating local phase evolution.Herein,accordion-shaped Co/Co_(3)O_(4)@N-doped carbon nanosheets(Co/Co_(3)O_(4)@NC)with gradient magnetic heterointerfaces have been fabricated via the cooperative high-temperature carbonization and lowtemperature oxidation process.The results indicate that the surface epitaxial growth of crystal Co_(3)O_(4) domains on local Co nanoparticles realizes the adjustment of magnetic-heteroatomic components,which are beneficial for optimizing impedance matching and interfacial polarization.Moreover,gradient magnetic heterointerfaces simultaneously realize magnetic coupling,and long-range magnetic diffraction.Specifically,the synthesized Co/Co_(3)O_(4)@NC absorbents display the strong electromagnetic wave attenuation capability of−53.5 dB at a thickness of 3.0 mm with an effective absorption bandwidth of 5.36 GHz,both are superior to those of single magnetic domains embedded in carbon matrix.This design concept provides us an inspiration in optimizing interfacial polarization,regulating magnetic coupling and promoting electromagnetic wave absorption.展开更多
Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then...Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then Ru3+was introduced for ion exchange,and the porous Ru-doped Co_(3)O_(4)/rGO(Ru-Co_(3)O_(4)/rGO)composite electrocatalyst was prepared by annealing.The phase structure,morphology,and valence state of the catalyst were analyzed by X-ray powder diffraction(XRD),scanning electron microscope(SEM),transmission electron microscopy(TEM),and X-ray photoelectron spectroscopy(XPS).In 1 mol·L^(-1)KOH,the oxygen evolution reaction(OER)performance of the catalyst was measured by linear sweep voltammetry,cyclic voltammetry,and chronoamperometry.The results show that the combination of Ru doping and rGO provides a fast channel for collaborative electron transfer.At the same time,rGO as a carbon carrier can improve the electrical conductivity of Ru-Co_(3)O_(4)particles,and the uniformly dispersed nanoparticles enable the reactants to diffuse freely on the catalyst.The results showed that the electrochemical performance of Ru-Co_(3)O_(4)/rGO was much better than that of Co_(3)O_(4)/rGO,and the overpotential of Ru-Co_(3)O_(4)/rGO was 363.5 mV at the current density of 50 mA·cm^(-2).展开更多
Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler ...Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.展开更多
The design of cost-effective and efficient metal-free carbon-based catalysts for the hydrogen evolution reaction(HER)is of great significance for increasing the production of clean hydrogen by the electrolysis of alka...The design of cost-effective and efficient metal-free carbon-based catalysts for the hydrogen evolution reaction(HER)is of great significance for increasing the production of clean hydrogen by the electrolysis of alkaline water.Precise control of the electronic structure by heteroatom doping has proven to be efficient for increasing catalytic activity.Nevertheless,both the structural characteristics and the underlying mechanism are not well understood,especially for doping with two different atoms,thus limiting the use of these catalysts.We report the production of phosphorus and nitrogen co-doped hollow carbon nanospheres(HCNs)by the copolymerization of pyrrole and aniline at a Triton X-100 micelle-interface,followed by doping with phytic acid and carbonization.The unique pore structure and defect-rich framework of the HCNs expose numerous active sites.Crucially,the combined effect of graphitic nitrogen and phosphorus-carbon bonds modulate the local electronic structure of adjacent C atoms and facilitates electron transfer.As a res-ult,the HCN carbonized at 1100°C exhibited superior HER activity and an outstanding stability(70 h at a current density of 10 mA cm^(−2))in alkaline water,because of the large number of graphitic nitrogen and phosphorus-carbon bonds.展开更多
Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nano...Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nanorods,which had many voids.The S-FeCoTA catalysts exhibited excellent electrochemical oxygen evolution reaction(OER)performance with a low overpotential of 273 mV at 10 mA·cm^(-2)and a small Tafel slope of 36 mV·dec^(-1)in 1 mol·L^(-1)KOH.The potential remained at 1.48 V(vs RHE)at 10 mA·cm^(-2)under continuous testing for 15 h,implying that S-FeCoTA had good stability.The Faraday efficiency of S-FeCoTA was 94%.The outstanding OER activity of S-FeCoTA is attributed to the synergistic effects among S,Fe,and Co,thus promoting electron transfer,reducing the reaction kinetic barrier,and enhancing the OER performance.展开更多
Several physical mechanisms of earthquake nucleation,such as pre-slip,cascade triggering,aseismic slip,and fluid-driven models,have been proposed.However,it is still not clear which model plays the most important role...Several physical mechanisms of earthquake nucleation,such as pre-slip,cascade triggering,aseismic slip,and fluid-driven models,have been proposed.However,it is still not clear which model plays the most important role in driving foreshocks and mainshock nucleation for given cases.In this study,we focus on the relationship between an intensive earthquake swarm that started beneath the Noto Peninsula in Central Japan since November 2020 and the nucleation of the 2024 M 7.6 Noto Hanto earthquake.We relocate earthquakes listed in the standard Japan Meteorological Agency(JMA)catalog since 2018 with the double-different relocation method.Relocated seismicity revealed that the 2024 M 7.6 mainshock likely ruptured a thrust fault above a parallel fault where the M 6.5 Suzu earthquake occurred in May 2023.We find possible along-strike and along-dip expansion of seismicity in the first few months at the beginning of the swarm sequence,while no obvious migration pattern in the last few days before the M 7.6 mainshock was observed.Several smaller events occurred in between the M 5.5 and M 4.6 foreshocks that occurred about 4min and 2 min before the M 7.6 mainshock.The Coulomb stress changes from the M 5.5 foreshock were negative at the hypocenter of the M 7.6 mainshock,which is inconsistent with a simple cascade triggering model.Moreover,an M 5.9 foreshock was identified in the JMA catalog 14 s before the mainshock.Results from backprojection of high-frequency teleseismic P waves show a prolonged initial rupture process near the mainshock hypocenter lasting for~25 s,before propagating bilaterally outward.Our results suggest a complex evolution process linking the earthquake swarm to the nucleation of the M 7.6 mainshock at a region of complex structures associated with the bend of a mapped large-scale reverse fault.A combination of fluid migration,aseismic slip and elastic stress triggering likely work in concert to drive both the prolonged earthquake swarm and the nucleation of the M 7.6 mainshock.展开更多
The characterization techniques were employed like transmission electron microscope,X-ray diffraction and microstructural characterization to investigate microstructural evolution and impact of precipitate-phase preci...The characterization techniques were employed like transmission electron microscope,X-ray diffraction and microstructural characterization to investigate microstructural evolution and impact of precipitate-phase precipitation on strength and toughness of a self-developed 32Si_(2)CrNi_(2)MoVNb steel during the quenching and tempering process.Research outputs indicated that the steel microstructure under the quenching state could be composed of martensite with a high dislocation density,a small amount of residual austenite,and many dispersed spherical MC carbides.In details,after tempering at 200℃,fine needle-shapedε-carbides would precipitate,which may improve yield strength and toughness of the steel.However,as compared to that after tempering at 200℃,the average length of needle-shapedε-carbides was found to increase to 144.1±4 from 134.1±3 nm after tempering at 340℃.As a result,the yield strength may increase to 1505±40 MPa,and the impact absorption energy(V-notch)may also decrease.Moreover,after tempering at 450℃,thoseε-carbides in the steel may transform into coarse rod-shaped cementite,and dislocation recoveries at such high tempering temperature may lead to decrease of strength and toughness of the steel.Finally,the following properties could be obtained:a yield strength of 1440±35 MPa,an ultimate tensile strength of 1864±50 MPa and an impact absorption energy of 45.9±4 J,by means of rational composition design and microstructural control.展开更多
A complex system is inherently high-dimensional.Recent studies indicate that,even without complete knowledge of its evolutionary dynamics,the future behavior of such a system can be predicted using time-series data(da...A complex system is inherently high-dimensional.Recent studies indicate that,even without complete knowledge of its evolutionary dynamics,the future behavior of such a system can be predicted using time-series data(data-driven prediction).This suggests that the essential dynamics of a complex system can be captured through a low-dimensional representation.Virus evolution and climate change are two examples of complex,time-varying systems.In this article,we show that mutations in the spike protein provide valuable data for predicting SARS-CoV-2 variants,forecasting the possible emergence of the new macro-lineage Q in the near future.Our analysis also demonstrates that carbon dioxide concentration is a reliable indicator for predicting the evolution of the climate system,extending global surface air temperature(GSAT)forecasts through 2500.展开更多
The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various ...The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.展开更多
Objective Poxviruses are zoonotic pathogens that infect humans,mammals,vertebrates,and arthropods.However,the specific role of ticks in transmission and evolution of these viruses remains unclear.Methods Transcriptomi...Objective Poxviruses are zoonotic pathogens that infect humans,mammals,vertebrates,and arthropods.However,the specific role of ticks in transmission and evolution of these viruses remains unclear.Methods Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses.Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences.Results Fifty-eight poxvirus species,representing two subfamilies and 20 genera,were identified,with 212 poxviral sequences assembled.A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes.These genomic sequences contained fragments originating from rodents,archaea,and arthropods.Conclusion Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses.These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer,gene recombination,and gene mutations,thereby promoting co-existence and co-evolution with their hosts.This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.展开更多
Organic nanophotocatalysts are promising candidates for solar fuels production,but they still face the challenge of unfavorable geminate recombination due to the limited exciton diffusion lengths.Here,we introduce a b...Organic nanophotocatalysts are promising candidates for solar fuels production,but they still face the challenge of unfavorable geminate recombination due to the limited exciton diffusion lengths.Here,we introduce a binary nanophotocatalyst fabricated by blending two polymers,PS-PEG5(PS)and PBT-PEG5(PBT),with matched absorption and emission spectra,enabling a Forster resonance energy transfer(FRET)process for enhanced photocatalysis.These heterostructure nanophotocatalysts are processed using a facile and scalable flash nanoprecipitation(FNP)technique with precious kinetic control over binary nanoparticle formation.The resulting nanoparticles exhibit an exceptional photocatalytic hydrogen evolution rate up to 65 mmol g^(-1) h^(-1),2.5 times higher than that single component nanoparticles.Characterizations through fluorescence spectra and transient absorption spectra confirm the hetero-energy transfer within the binary nanoparticles,which prolongs the excited-state lifetime and extends the namely“effective exciton diffusion length”.Our finding opens new avenues for designing efficient organic photocatalysts by improving exciton migration.展开更多
An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of t...An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.展开更多
In the application of high-pressure water jet assisted breaking of deep underground rock engineering,the influence mechanism of rock temperature on the rock fragmentation process under jet action is still unclear.Ther...In the application of high-pressure water jet assisted breaking of deep underground rock engineering,the influence mechanism of rock temperature on the rock fragmentation process under jet action is still unclear.Therefore,the fluid evolution characteristics and rock fracture behavior during jet impingement were studied.The results indicate that the breaking process of high-temperature rock by jet impact can be divided into four stages:initial fluid-solid contact stage,intense thermal exchange stage,perforation and fracturing stage,and crack propagation and penetration stage.With the increase of rock temperature,the jet reflection angles and the time required for complete cooling of the impact surface significantly decrease,while the number of cracks and crack propagation rate significantly increase,and the rock breaking critical time is shortened by up to 34.5%.Based on numerical simulation results,it was found that the center temperature of granite at 400℃ rapidly decreased from 390 to 260℃ within 0.7 s under jet impact.In addition,a critical temperature and critical heat flux prediction model considering the staged breaking of hot rocks was established.These findings provide valuable insights to guide the water jet technology assisted deep ground hot rock excavation project.展开更多
文摘Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis.Traditional clustering algorithms,such as K-means,are widely used due to their simplicity and efficiency.This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering performance.The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)algorithm.Firstly,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population diversity.Secondly,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence speed.Finally,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation effectively.The performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic algorithms.To further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven datasets.Experimental results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering approaches.This study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.
文摘To ensure a long-term safety and reliability of electric vehicle and energy storage system,an accurate estimation of the state of health(SOH)for lithium-ion battery is important.In this study,a method for estimating the lithium-ion battery SOH was proposed based on an improved extreme learning machine(ELM).Input weights and hidden layer biases were generated randomly in traditional ELM.To improve the estimation accuracy of ELM,the differential evolution algorithm was used to optimize these parameters in feasible solution spaces.First,incremental capacity curves were obtained by incremental capacity analysis and smoothed by Gaussian filter to extract health interests.Then,the ELM based on differential evolution algorithm(DE-ELM model)was used for a lithium-ion battery SOH estimation.At last,four battery historical aging data sets and one random walk data set were employed to validate the prediction performance of DE-ELM model.Results show that the DE-ELM has a better performance than other studied algorithms in terms of generalization ability.
基金supported by the National Natural Science Foundation of China(Nos.12475174 and 12175101)Yue Lu Shan Center Industrial Innovation(No.2024YCII0108)。
文摘In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding structures typically need to be lightweight,miniaturized,and radiation-protected,which is a multi-parameter and multi-objective optimization problem.The conventional multi-objective(two or three objectives)optimization method for radiation-shielding design exhibits limitations for a number of optimization objectives and variable parameters,as well as a deficiency in achieving a global optimal solution,thereby failing to meet the requirements of shielding optimization for newly developed reactors.In this study,genetic and artificial bee-colony algorithms are combined with a reference-point-selection strategy and applied to the many-objective(having four or more objectives)optimal design of reactor radiation shielding.To validate the reliability of the methods,an optimization simulation is conducted on three-dimensional shielding structures and another complicated shielding-optimization problem.The numerical results demonstrate that the proposed algorithms outperform conventional shielding-design methods in terms of optimization performance,and they exhibit their reliability in practical engineering problems.The many-objective optimization algorithms developed in this study are proven to efficiently and consistently search for Pareto-front shielding schemes.Therefore,the algorithms proposed in this study offer novel insights into improving the shielding-design performance and shielding quality of new reactor types.
文摘Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.
文摘With the development of economic globalization,distributedmanufacturing is becomingmore andmore prevalent.Recently,integrated scheduling of distributed production and assembly has captured much concern.This research studies a distributed flexible job shop scheduling problem with assembly operations.Firstly,a mixed integer programming model is formulated to minimize the maximum completion time.Secondly,a Q-learning-assisted coevolutionary algorithmis presented to solve themodel:(1)Multiple populations are developed to seek required decisions simultaneously;(2)An encoding and decoding method based on problem features is applied to represent individuals;(3)A hybrid approach of heuristic rules and random methods is employed to acquire a high-quality population;(4)Three evolutionary strategies having crossover and mutation methods are adopted to enhance exploration capabilities;(5)Three neighborhood structures based on problem features are constructed,and a Q-learning-based iterative local search method is devised to improve exploitation abilities.The Q-learning approach is applied to intelligently select better neighborhood structures.Finally,a group of instances is constructed to perform comparison experiments.The effectiveness of the Q-learning approach is verified by comparing the developed algorithm with its variant without the Q-learning method.Three renowned meta-heuristic algorithms are used in comparison with the developed algorithm.The comparison results demonstrate that the designed method exhibits better performance in coping with the formulated problem.
基金funded by the Ministry of Higher Education of Malaysia,grant number FRGS/1/2022/ICT02/UPSI/02/1.
文摘In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classification methods that utilize evolutionary algorithms(EAs)for gene expression profiles in cancer or medical applications based on research motivations,challenges,and recommendations.Relevant studies were retrieved from four major academic databases-IEEE,Scopus,Springer,and ScienceDirect-using the keywords‘cancer classification’,‘optimization’,‘FS’,and‘gene expression profile’.A total of 67 papers were finally selected with key advancements identified as follows:(1)The majority of papers(44.8%)focused on developing algorithms and models for FS and classification.(2)The second category encompassed studies on biomarker identification by EAs,including 20 papers(30%).(3)The third category comprised works that applied FS to cancer data for decision support system purposes,addressing high-dimensional data and the formulation of chromosome length.These studies accounted for 12%of the total number of studies.(4)The remaining three papers(4.5%)were reviews and surveys focusing on models and developments in prediction and classification optimization for cancer classification under current technical conditions.This review highlights the importance of optimizing FS in EAs to manage high-dimensional data effectively.Despite recent advancements,significant limitations remain:the dynamic formulation of chromosome length remains an underexplored area.Thus,further research is needed on dynamic-length chromosome techniques for more sophisticated biomarker gene selection techniques.The findings suggest that further advancements in dynamic chromosome length formulations and adaptive algorithms could enhance cancer classification accuracy and efficiency.
基金financially supported by the National Science Foundation of China(Nos.51974212 and 52274316)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202116)+1 种基金the Science and Technology Major Project of Wuhan(No.2023020302020572)the Foundation of Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of Education(No.FMRUlab23-04)。
文摘The utilization of iron coke provides a green pathway for low-carbon ironmaking.To uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was investigated.Furthermore,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric method.The findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and interconnect.This provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron coke.Accelerating the heating rate in non-isothermal gasification can enhance the reactivity of iron coke.The metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon atoms.The kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore structure.Moreover,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.
基金financially supported by the National Natural Science Foundation of China(52373271)Science,Technology and Innovation Commission of Shenzhen Municipality under Grant(KCXFZ20201221173004012)+1 种基金National Key Research and Development Program of Shaanxi Province(No.2023-YBNY-271)Open Testing Foundation of the Analytical&Testing Center of Northwestern Polytechnical University(2023T019).
文摘Gradient magnetic heterointerfaces have injected infinite vitality in optimizing impedance matching,adjusting dielectric/magnetic resonance and promoting electromagnetic(EM)wave absorption,but still exist a significant challenging in regulating local phase evolution.Herein,accordion-shaped Co/Co_(3)O_(4)@N-doped carbon nanosheets(Co/Co_(3)O_(4)@NC)with gradient magnetic heterointerfaces have been fabricated via the cooperative high-temperature carbonization and lowtemperature oxidation process.The results indicate that the surface epitaxial growth of crystal Co_(3)O_(4) domains on local Co nanoparticles realizes the adjustment of magnetic-heteroatomic components,which are beneficial for optimizing impedance matching and interfacial polarization.Moreover,gradient magnetic heterointerfaces simultaneously realize magnetic coupling,and long-range magnetic diffraction.Specifically,the synthesized Co/Co_(3)O_(4)@NC absorbents display the strong electromagnetic wave attenuation capability of−53.5 dB at a thickness of 3.0 mm with an effective absorption bandwidth of 5.36 GHz,both are superior to those of single magnetic domains embedded in carbon matrix.This design concept provides us an inspiration in optimizing interfacial polarization,regulating magnetic coupling and promoting electromagnetic wave absorption.
文摘Binary composites(ZIF-67/rGO)were synthesized by one-step precipitation method using cobalt nitrate hexahydrate as metal source,2-methylimidazole as organic ligand,and reduced graphene oxide(rGO)as carbon carrier.Then Ru3+was introduced for ion exchange,and the porous Ru-doped Co_(3)O_(4)/rGO(Ru-Co_(3)O_(4)/rGO)composite electrocatalyst was prepared by annealing.The phase structure,morphology,and valence state of the catalyst were analyzed by X-ray powder diffraction(XRD),scanning electron microscope(SEM),transmission electron microscopy(TEM),and X-ray photoelectron spectroscopy(XPS).In 1 mol·L^(-1)KOH,the oxygen evolution reaction(OER)performance of the catalyst was measured by linear sweep voltammetry,cyclic voltammetry,and chronoamperometry.The results show that the combination of Ru doping and rGO provides a fast channel for collaborative electron transfer.At the same time,rGO as a carbon carrier can improve the electrical conductivity of Ru-Co_(3)O_(4)particles,and the uniformly dispersed nanoparticles enable the reactants to diffuse freely on the catalyst.The results showed that the electrochemical performance of Ru-Co_(3)O_(4)/rGO was much better than that of Co_(3)O_(4)/rGO,and the overpotential of Ru-Co_(3)O_(4)/rGO was 363.5 mV at the current density of 50 mA·cm^(-2).
基金National Natural Science Foundation of China(U22A20191)。
文摘Brazing filler metals are widely applied,which serve as an industrial adhesive in the joining of dissimilar structures.With the continuous emergence of new structures and materials,the demand for novel brazing filler metals is ever-increasing.It is of great significance to investigate the optimized composition design methods and to establish systematic design guidelines for brazing filler metals.This study elucidated the fundamental rules for the composition design of brazing filler metals from a three-dimensional perspective encompassing the basic properties of applied brazing filler metals,formability and processability,and overall cost.The basic properties of brazing filler metals refer to their mechanical properties,physicochemical properties,electromagnetic properties,corrosion resistance,and the wettability and fluidity during brazing.The formability and processability of brazing filler metals include the processes of smelting and casting,extrusion,rolling,drawing and ring-making,as well as the processes of granulation,powder production,and the molding of amorphous and microcrystalline structures.The cost of brazing filler metals corresponds to the sum of materials value and manufacturing cost.Improving the comprehensive properties of brazing filler metals requires a comprehensive and systematic consideration of design indicators.Highlighting the unique characteristics of brazing filler metals should focus on relevant technical indicators.Binary or ternary eutectic structures can effectively enhance the flow spreading ability of brazing filler metals,and solid solution structures contribute to the formability.By employing the proposed design guidelines,typical Ag based,Cu based,Zn based brazing filler metals,and Sn based solders were designed and successfully applied in major scientific and engineering projects.
基金financially supported by the project of the National Natural Science Foundation of China(52322203)the Key Research and Development Program of Shaanxi Province(2024GHZDXM-21)。
文摘The design of cost-effective and efficient metal-free carbon-based catalysts for the hydrogen evolution reaction(HER)is of great significance for increasing the production of clean hydrogen by the electrolysis of alkaline water.Precise control of the electronic structure by heteroatom doping has proven to be efficient for increasing catalytic activity.Nevertheless,both the structural characteristics and the underlying mechanism are not well understood,especially for doping with two different atoms,thus limiting the use of these catalysts.We report the production of phosphorus and nitrogen co-doped hollow carbon nanospheres(HCNs)by the copolymerization of pyrrole and aniline at a Triton X-100 micelle-interface,followed by doping with phytic acid and carbonization.The unique pore structure and defect-rich framework of the HCNs expose numerous active sites.Crucially,the combined effect of graphitic nitrogen and phosphorus-carbon bonds modulate the local electronic structure of adjacent C atoms and facilitates electron transfer.As a res-ult,the HCN carbonized at 1100°C exhibited superior HER activity and an outstanding stability(70 h at a current density of 10 mA cm^(−2))in alkaline water,because of the large number of graphitic nitrogen and phosphorus-carbon bonds.
文摘Sulfur-doped iron-cobalt tannate nanorods(S-FeCoTA)derived from metal-organic frameworks(MOFs)as electrocatalysts were synthesized via a one-step hydrothermal method.The optimized S-FeCoTA was interlaced by loose nanorods,which had many voids.The S-FeCoTA catalysts exhibited excellent electrochemical oxygen evolution reaction(OER)performance with a low overpotential of 273 mV at 10 mA·cm^(-2)and a small Tafel slope of 36 mV·dec^(-1)in 1 mol·L^(-1)KOH.The potential remained at 1.48 V(vs RHE)at 10 mA·cm^(-2)under continuous testing for 15 h,implying that S-FeCoTA had good stability.The Faraday efficiency of S-FeCoTA was 94%.The outstanding OER activity of S-FeCoTA is attributed to the synergistic effects among S,Fe,and Co,thus promoting electron transfer,reducing the reaction kinetic barrier,and enhancing the OER performance.
基金partially supported by U.S.National Science Foundation grants EAR1925965 and RISE-2425889support from the European Research Council under the European Union Horizon 2020 research and innovation program(grant agreement no.742335,FIMAGE)。
文摘Several physical mechanisms of earthquake nucleation,such as pre-slip,cascade triggering,aseismic slip,and fluid-driven models,have been proposed.However,it is still not clear which model plays the most important role in driving foreshocks and mainshock nucleation for given cases.In this study,we focus on the relationship between an intensive earthquake swarm that started beneath the Noto Peninsula in Central Japan since November 2020 and the nucleation of the 2024 M 7.6 Noto Hanto earthquake.We relocate earthquakes listed in the standard Japan Meteorological Agency(JMA)catalog since 2018 with the double-different relocation method.Relocated seismicity revealed that the 2024 M 7.6 mainshock likely ruptured a thrust fault above a parallel fault where the M 6.5 Suzu earthquake occurred in May 2023.We find possible along-strike and along-dip expansion of seismicity in the first few months at the beginning of the swarm sequence,while no obvious migration pattern in the last few days before the M 7.6 mainshock was observed.Several smaller events occurred in between the M 5.5 and M 4.6 foreshocks that occurred about 4min and 2 min before the M 7.6 mainshock.The Coulomb stress changes from the M 5.5 foreshock were negative at the hypocenter of the M 7.6 mainshock,which is inconsistent with a simple cascade triggering model.Moreover,an M 5.9 foreshock was identified in the JMA catalog 14 s before the mainshock.Results from backprojection of high-frequency teleseismic P waves show a prolonged initial rupture process near the mainshock hypocenter lasting for~25 s,before propagating bilaterally outward.Our results suggest a complex evolution process linking the earthquake swarm to the nucleation of the M 7.6 mainshock at a region of complex structures associated with the bend of a mapped large-scale reverse fault.A combination of fluid migration,aseismic slip and elastic stress triggering likely work in concert to drive both the prolonged earthquake swarm and the nucleation of the M 7.6 mainshock.
基金the National Natural Science Foundation of China(Key Program)(52031004).
文摘The characterization techniques were employed like transmission electron microscope,X-ray diffraction and microstructural characterization to investigate microstructural evolution and impact of precipitate-phase precipitation on strength and toughness of a self-developed 32Si_(2)CrNi_(2)MoVNb steel during the quenching and tempering process.Research outputs indicated that the steel microstructure under the quenching state could be composed of martensite with a high dislocation density,a small amount of residual austenite,and many dispersed spherical MC carbides.In details,after tempering at 200℃,fine needle-shapedε-carbides would precipitate,which may improve yield strength and toughness of the steel.However,as compared to that after tempering at 200℃,the average length of needle-shapedε-carbides was found to increase to 144.1±4 from 134.1±3 nm after tempering at 340℃.As a result,the yield strength may increase to 1505±40 MPa,and the impact absorption energy(V-notch)may also decrease.Moreover,after tempering at 450℃,thoseε-carbides in the steel may transform into coarse rod-shaped cementite,and dislocation recoveries at such high tempering temperature may lead to decrease of strength and toughness of the steel.Finally,the following properties could be obtained:a yield strength of 1440±35 MPa,an ultimate tensile strength of 1864±50 MPa and an impact absorption energy of 45.9±4 J,by means of rational composition design and microstructural control.
基金Natural science foundation of Inner Mongolia(2024LHMS06018)The basic scientific research funding for directly affiliated universities in the Inner Mongolia(JY20250094)。
文摘A complex system is inherently high-dimensional.Recent studies indicate that,even without complete knowledge of its evolutionary dynamics,the future behavior of such a system can be predicted using time-series data(data-driven prediction).This suggests that the essential dynamics of a complex system can be captured through a low-dimensional representation.Virus evolution and climate change are two examples of complex,time-varying systems.In this article,we show that mutations in the spike protein provide valuable data for predicting SARS-CoV-2 variants,forecasting the possible emergence of the new macro-lineage Q in the near future.Our analysis also demonstrates that carbon dioxide concentration is a reliable indicator for predicting the evolution of the climate system,extending global surface air temperature(GSAT)forecasts through 2500.
基金in part supported by the Key Research and Development Project of Hubei Province(Nos.2020BAB1141,2023BAB094)the Key Project of Science and Technology Research ProgramofHubei Educational Committee(No.D20211402)+1 种基金the Teaching Research Project of Hubei University of Technology(No.XIAO2018001)the Project of Xiangyang Industrial Research Institute of Hubei University of Technology(No.XYYJ2022C04).
文摘The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.
基金financially supported by the Shanghai New Three-Year Action Plan for Public Health(Grant No.GWVI-11.1-03)National Natural Science Foundation of China(Grant No.81872673).
文摘Objective Poxviruses are zoonotic pathogens that infect humans,mammals,vertebrates,and arthropods.However,the specific role of ticks in transmission and evolution of these viruses remains unclear.Methods Transcriptomic and metatranscriptomic raw data from 329 sampling pools of seven tick species across five continents were mined to assess the diversity and abundance of poxviruses.Chordopoxviral sequences were assembled and subjected to phylogenetic analysis to trace the origins of the unblasted fragments within these sequences.Results Fifty-eight poxvirus species,representing two subfamilies and 20 genera,were identified,with 212 poxviral sequences assembled.A substantial proportion of AT-rich fragments were detected in the assembled poxviral genomes.These genomic sequences contained fragments originating from rodents,archaea,and arthropods.Conclusion Our findings indicate that ticks play a significant role in the transmission and evolution of poxviruses.These viruses demonstrate the capacity to modulate virulence and adaptability through horizontal gene transfer,gene recombination,and gene mutations,thereby promoting co-existence and co-evolution with their hosts.This study advances understanding of the ecological dynamics of poxvirus transmission and evolution and highlights the potential role of ticks as vectors and vessels in these processes.
基金supported by National Natural Science Foundation of China(NSFC,22338006,92356301,9235630033 and 22375062)Shanghai Municipal Science and Technology Major Project(21JC1401700)+4 种基金Shanghai Pilot Program for Basic Research(22TQ1400100-10)Fundamental Research Funds for the Central UniversitiesShanghai Pujiang Program(22PJ1402400)“Chenguang Program”supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission(22CGA32)the Young Elite Scientists Sponsorship Program by CAST(2023QNRC001).
文摘Organic nanophotocatalysts are promising candidates for solar fuels production,but they still face the challenge of unfavorable geminate recombination due to the limited exciton diffusion lengths.Here,we introduce a binary nanophotocatalyst fabricated by blending two polymers,PS-PEG5(PS)and PBT-PEG5(PBT),with matched absorption and emission spectra,enabling a Forster resonance energy transfer(FRET)process for enhanced photocatalysis.These heterostructure nanophotocatalysts are processed using a facile and scalable flash nanoprecipitation(FNP)technique with precious kinetic control over binary nanoparticle formation.The resulting nanoparticles exhibit an exceptional photocatalytic hydrogen evolution rate up to 65 mmol g^(-1) h^(-1),2.5 times higher than that single component nanoparticles.Characterizations through fluorescence spectra and transient absorption spectra confirm the hetero-energy transfer within the binary nanoparticles,which prolongs the excited-state lifetime and extends the namely“effective exciton diffusion length”.Our finding opens new avenues for designing efficient organic photocatalysts by improving exciton migration.
基金supported by the National Natural Science Foundation of China(No.51905123)Major Scientific and Technological Innovation Program of Shandong Province,China(Nos.2020CXGC010303,2022ZLGX04)Key R&D Programme of Shandong Province,China(No.2022JMRH0308).
文摘An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.
基金supported by National Natural Science Foundation of China (No.U23A20597)National Major Science and Technology Project of China (No.2024ZD1003803)+1 种基金Chongqing Science Fund for Distinguished Young Scholars of Chongqing Municipality (No.CSTB2022NSCQ-JQX0028)Natural Science Foundation of Chongqing (No.CSTB2024NSCQ-MSX0503)。
文摘In the application of high-pressure water jet assisted breaking of deep underground rock engineering,the influence mechanism of rock temperature on the rock fragmentation process under jet action is still unclear.Therefore,the fluid evolution characteristics and rock fracture behavior during jet impingement were studied.The results indicate that the breaking process of high-temperature rock by jet impact can be divided into four stages:initial fluid-solid contact stage,intense thermal exchange stage,perforation and fracturing stage,and crack propagation and penetration stage.With the increase of rock temperature,the jet reflection angles and the time required for complete cooling of the impact surface significantly decrease,while the number of cracks and crack propagation rate significantly increase,and the rock breaking critical time is shortened by up to 34.5%.Based on numerical simulation results,it was found that the center temperature of granite at 400℃ rapidly decreased from 390 to 260℃ within 0.7 s under jet impact.In addition,a critical temperature and critical heat flux prediction model considering the staged breaking of hot rocks was established.These findings provide valuable insights to guide the water jet technology assisted deep ground hot rock excavation project.
