Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability...Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.展开更多
Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis proce...Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis procedures impede in-depth clarification of their catalytic mechanisms.To this end,herein we developed an efficient one-step dimension-reduction carbonization strategy,with which we successfully architected a highly-efficient catalyst for oxygen reduction reaction(ORR),featured with symbiotic cobalt single atoms and clusters decorated in two-dimensional(2D)ultra-thin(3.5 nm thickness)nitrogen-carbon nanosheets.The synergistic effects of the two components afford excellent oxygen reduction activity in alkaline media(E_(1/2)=0.823 V vs.RHE)and thereof a high power density(146.61 mW cm^(-2))in an assembled Zn-air battery.As revealed by theoretical calculations,the cobalt clusters can regulate electrons surrounding those individual atoms and affect the adsorption of intermediate species.As a consequence,the derived active sites of single cobalt atoms lead to a significant improvement of the ORR performance.Thus,our work may fuel interests to delicate architectu re of single atoms and clusters coexisting 2D support toward optimal electrocatalytic performance.展开更多
We investigated the ionization and dissociation processes of ammonia clusters ranging from dimer to pentamer induced by 800-nm femtosecond laser fields.Time-of-flight(TOF)mass spectra of the ammonia clusters were reco...We investigated the ionization and dissociation processes of ammonia clusters ranging from dimer to pentamer induced by 800-nm femtosecond laser fields.Time-of-flight(TOF)mass spectra of the ammonia clusters were recorded over a range of laser intensities from 2.1×10^(12)W/cm^(2) to 5.6×10^(12)W/cm^(2).The protonated ion signals dominate the spectra,which is consistent with the stability of the geometric structures.The ionization and dissociation channels of ammonia clusters are discussed.The competition and switching among observed dissociation channels are revealed by analyzing the variations in the relative ionic yields of specific protonated and unprotonated clusters under different laser intensities.These results indicate that the ionization of the neutral multiple-ammonia units,produced through the dissociation of cluster ions,may start to contribute,as well as the additional processes to consume protonated ions and/or produce unprotonated ions induced by the femtosecond laser fields when the laser intensity is above^4×10^(12)W/cm^(2).These findings provide deeper insights into the ionization and dissociation dynamics in multi-photon ionization experiments involving ammonia clusters.展开更多
In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clu...In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.展开更多
Correction to:Nano-Micro Letters(2025)17:123 https://doi.org/10.1007/s40820-025-01654-y Following publication of the original article[1],the authors reported that Dr.Mohamed Bououdina’s affiliation needed to be corre...Correction to:Nano-Micro Letters(2025)17:123 https://doi.org/10.1007/s40820-025-01654-y Following publication of the original article[1],the authors reported that Dr.Mohamed Bououdina’s affiliation needed to be corrected from 1 to 2.The correct author affiliation has been provided in this Correction and the original article[1]has been corrected.展开更多
Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing...Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized guest single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized guest single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
In recent years,many unknown protocols are constantly emerging,and they bring severe challenges to network security and network management.Existing unknown protocol recognition methods suffer from weak feature extract...In recent years,many unknown protocols are constantly emerging,and they bring severe challenges to network security and network management.Existing unknown protocol recognition methods suffer from weak feature extraction ability,and they cannot mine the discriminating features of the protocol data thoroughly.To address the issue,we propose an unknown application layer protocol recognition method based on deep clustering.Deep clustering which consists of the deep neural network and the clustering algorithm can automatically extract the features of the input and cluster the data based on the extracted features.Compared with the traditional clustering methods,deep clustering boasts of higher clustering accuracy.The proposed method utilizes network-in-network(NIN),channel attention,spatial attention and Bidirectional Long Short-term memory(BLSTM)to construct an autoencoder to extract the spatial-temporal features of the protocol data,and utilizes the unsupervised clustering algorithm to recognize the unknown protocols based on the features.The method firstly extracts the application layer protocol data from the network traffic and transforms the data into one-dimensional matrix.Secondly,the autoencoder is pretrained,and the protocol data is compressed into low dimensional latent space by the autoencoder and the initial clustering is performed with K-Means.Finally,the clustering loss is calculated and the classification model is optimized according to the clustering loss.The classification results can be obtained when the classification model is optimal.Compared with the existing unknown protocol recognition methods,the proposed method utilizes deep clustering to cluster the unknown protocols,and it can mine the key features of the protocol data and recognize the unknown protocols accurately.Experimental results show that the proposed method can effectively recognize the unknown protocols,and its performance is better than other methods.展开更多
Tri-axial fracturing studies were carried out to understand the impact of lateral mechanical parameters on fracture propagation from multiple in-plane perforations in horizontal wells. Additionally, the discussion cov...Tri-axial fracturing studies were carried out to understand the impact of lateral mechanical parameters on fracture propagation from multiple in-plane perforations in horizontal wells. Additionally, the discussion covered the effects of geology, treatment, and perforation characteristics on the non-planar propagation behavior. According to experimental findings, two parallel transverse fractures can be successfully initiated from in-plane perforation clusters in the horizontal well because of the in-plane perforation, the guide nonuniform fishbone structure fracture propagation still can be exhibited. The emergence of transverse fractures and axial fractures combined as complex fractures under low horizontal principal stress difference and large pump rate conditions. The injection pressure was also investigated, and the largest breakdown pressure can be also found for samples under these conditions.The increase in perforation number or decrease in the cluster spacing could provide more chances to increase the complexity of the target stimulated zone, thus affecting the pressure fluctuation. In a contrast, the increase in fracturing fluid viscosity can reduce the multiple fracture complexity. The fracture propagation is significantly affected by the change in the rock mechanical properties. The fracture geometry in the high brittle zone seems to be complicated and tends to induce fracture reorientation from the weak-brittle zone. The stress shadow effect can be used to explain the fracture attraction, branch, connection, and repulsion in the multiple perforation clusters for the horizontal well.The increase in the rock heterogeneity can enhance the stress shadow effect, resulting in more complex fracture geometry. In addition, the variable density perforation and temporary plugging fracturing were also conducted, demonstrating higher likelihood for non-uniform multiple fracture propagation. Thus, to increase the perforation efficiency along the horizontal well, it is necessary to consider the lateral fracability of the horizontal well on target formation.展开更多
Au is considered as one of the most promising catalysts for nitrogen reduction reaction(NRR),however maximizing the activity utilization rate of Au and understanding the synergistic effects between Au and carriers pos...Au is considered as one of the most promising catalysts for nitrogen reduction reaction(NRR),however maximizing the activity utilization rate of Au and understanding the synergistic effects between Au and carriers pose ongoing challenges.Herein,we systematically explore the synergistic catalytic effect of incorporating Au with boron clusters for accelerating NRR kinetics.An in-situ abinitio strategy is employed to construct B-doped Au nanoparticles(2-6 nm in diameter)loaded on BO_(x) substrates(AuBO_(x)),in which B not only modulates the surface electronic structure of Au but also forms strong coupling interactions to stabilize the nanoparticles.The electrochemical results show that Au-BO_(x) possesses excellent NRR activity(NH_(3) yield of 48.52μg h^(-1)mg_(cat)^(-1),Faraday efficiency of 56.18%),and exhibits high stability and reproducibility throughout the electrocatalytic NRR process.Theoretical calculations reveal that the introduction of B induces the formation of both Au dangling bond and Au-B coupling bond.which considerably facilitates the hydrogenation of~*N_(2)^(-)~*NH_(3).The present work provides a new avenue for the preparation of metal-boron materials achieved by one-step reduction and doping process,utilizing boron clusters as reducing and stabilizing agents.展开更多
Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for t...Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.展开更多
With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of th...With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.展开更多
The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in...The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in the literature.The number density and average diameter of the dislocation loops obtained from the CD simulations are in good agreement with the experimental data obtained from transmission electron microscopy(TEM)observations of Fe~+-irradiated Solution Annealed 304,Cold Worked 316,and HR3 austenitic steels in the literature.The CD simulation results demonstrate that the diffusion of in-cascade interstitial clusters plays a major role in the dislocation loop density and dislocation loop growth;in particular,for the HR3 austenitic steel,the CD model has verified the effect of temperature on the density and size of the dislocation loops.展开更多
We propose an approach for generating robust two-dimensional(2D)vortex clusters(VCs)in a Rydberg atomic system by utilizing parity-time(PT)symmetric optical Bessel potential.We show that the system supports novel mult...We propose an approach for generating robust two-dimensional(2D)vortex clusters(VCs)in a Rydberg atomic system by utilizing parity-time(PT)symmetric optical Bessel potential.We show that the system supports novel multicore VCs with four and eight cores,corresponding to topological charges 2 and 4,respectively.The stability of these VCs can be dynamically adjusted through the manipulation of the gain-loss component,Kerr nonlinearities,and the degree of nonlocality inherent in the Rydberg atoms.These VCs are confined within the first lattice well of the Bessel potential,and both the power and width of lights undergo a quasi-periodic breathing phenomenon,which is attributed to the power exchange between the light fields and Bessel potential.Both self-attractive and self-repulsive Kerr interactions can sustain robust VCs within this system.The insights presented here not only facilitate the creation and manipulation of 2D VCs through PT-symmetric potentials but also pave the way for potential applications in optical information processing and transmission.展开更多
The exploration of exotic shapes and properties of atomic nuclei,e.g.,αcluster and toroidal shape,is a fascinating field in nuclear physics.To study the decay of these nuclei,a novel detector aimed at detecting multi...The exploration of exotic shapes and properties of atomic nuclei,e.g.,αcluster and toroidal shape,is a fascinating field in nuclear physics.To study the decay of these nuclei,a novel detector aimed at detecting multipleα-particle events was designed and constructed.The detector comprises two layers of double-sided silicon strip detectors(DSSD)and a cesium iodide scintillator array coupled with silicon photomultipliers array as light sensors,which has the advantages of their small size,fast response,and large dynamic range.DSSDs coupled with cesium iodide crystal arrays are used to distinguish multipleαhits.The detector array has a compact and integrated design that can be adapted to different experimental conditions.The detector array was simulated using Geant4,and the excitation energy spectra of someα-clustering nuclei were reconstructed to demonstrate the performance.The simulation results show that the detector array has excellent angular and energy resolutions,enabling effective reconstruction of the nuclear excited state by multipleαparticle events.This detector offers a new and powerful tool for nuclear physics experiments and has the potential to discover interesting physical phenomena related to exotic nuclear structures and their decay mechanisms.展开更多
Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enh...Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enhanced electrocatalytic performance,simultaneously provide a radical analysis of the interrelationship between structure and activity.In this review,the recent advances of single-atomic site catalysts coupled with clusters or nanoparticles are emphasized.Firstly,the synthetic strategies,characterization,dynamics and types of single atoms coupled with clusters/nanoparticles are introduced,and then the key factors controlling the structure of the composite catalysts are discussed.Next,several clean energy catalytic reactions performed over the synergistic composite catalysts are illustrated.Eventually,the encountering challenges and recommendations for the future advancement of synergistic structure in energy-transformation electrocatalysis are outlined.展开更多
文摘Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.
基金supported by the National Natural Science Foundation of China(51872115 and 12234018)Beijing Synchrotron Radiation Facility(BSRF)4B9A.
文摘Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis procedures impede in-depth clarification of their catalytic mechanisms.To this end,herein we developed an efficient one-step dimension-reduction carbonization strategy,with which we successfully architected a highly-efficient catalyst for oxygen reduction reaction(ORR),featured with symbiotic cobalt single atoms and clusters decorated in two-dimensional(2D)ultra-thin(3.5 nm thickness)nitrogen-carbon nanosheets.The synergistic effects of the two components afford excellent oxygen reduction activity in alkaline media(E_(1/2)=0.823 V vs.RHE)and thereof a high power density(146.61 mW cm^(-2))in an assembled Zn-air battery.As revealed by theoretical calculations,the cobalt clusters can regulate electrons surrounding those individual atoms and affect the adsorption of intermediate species.As a consequence,the derived active sites of single cobalt atoms lead to a significant improvement of the ORR performance.Thus,our work may fuel interests to delicate architectu re of single atoms and clusters coexisting 2D support toward optimal electrocatalytic performance.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.92261201,12134005,12334011)。
文摘We investigated the ionization and dissociation processes of ammonia clusters ranging from dimer to pentamer induced by 800-nm femtosecond laser fields.Time-of-flight(TOF)mass spectra of the ammonia clusters were recorded over a range of laser intensities from 2.1×10^(12)W/cm^(2) to 5.6×10^(12)W/cm^(2).The protonated ion signals dominate the spectra,which is consistent with the stability of the geometric structures.The ionization and dissociation channels of ammonia clusters are discussed.The competition and switching among observed dissociation channels are revealed by analyzing the variations in the relative ionic yields of specific protonated and unprotonated clusters under different laser intensities.These results indicate that the ionization of the neutral multiple-ammonia units,produced through the dissociation of cluster ions,may start to contribute,as well as the additional processes to consume protonated ions and/or produce unprotonated ions induced by the femtosecond laser fields when the laser intensity is above^4×10^(12)W/cm^(2).These findings provide deeper insights into the ionization and dissociation dynamics in multi-photon ionization experiments involving ammonia clusters.
基金partially supported by the National Natural Science Foundation of China(62161016)the Key Research and Development Project of Lanzhou Jiaotong University(ZDYF2304)+1 种基金the Beijing Engineering Research Center of Highvelocity Railway Broadband Mobile Communications(BHRC-2022-1)Beijing Jiaotong University。
文摘In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.
文摘Correction to:Nano-Micro Letters(2025)17:123 https://doi.org/10.1007/s40820-025-01654-y Following publication of the original article[1],the authors reported that Dr.Mohamed Bououdina’s affiliation needed to be corrected from 1 to 2.The correct author affiliation has been provided in this Correction and the original article[1]has been corrected.
基金financially supported by the Shanghai RisingStar Program(No.23QA1403700)the National Natural Science Foundation of China(NSFC,Grant No.U2230102)+1 种基金the sponsored by National Key Research and Development Program of China(No.2021YFB3502200)the Shanghai Technical Service Center of Science and Engineering Computing,Shanghai University.
文摘Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized guest single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized guest single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
基金This work is supported by the National Key R&D Program of China(2017YFB0802900).
文摘In recent years,many unknown protocols are constantly emerging,and they bring severe challenges to network security and network management.Existing unknown protocol recognition methods suffer from weak feature extraction ability,and they cannot mine the discriminating features of the protocol data thoroughly.To address the issue,we propose an unknown application layer protocol recognition method based on deep clustering.Deep clustering which consists of the deep neural network and the clustering algorithm can automatically extract the features of the input and cluster the data based on the extracted features.Compared with the traditional clustering methods,deep clustering boasts of higher clustering accuracy.The proposed method utilizes network-in-network(NIN),channel attention,spatial attention and Bidirectional Long Short-term memory(BLSTM)to construct an autoencoder to extract the spatial-temporal features of the protocol data,and utilizes the unsupervised clustering algorithm to recognize the unknown protocols based on the features.The method firstly extracts the application layer protocol data from the network traffic and transforms the data into one-dimensional matrix.Secondly,the autoencoder is pretrained,and the protocol data is compressed into low dimensional latent space by the autoencoder and the initial clustering is performed with K-Means.Finally,the clustering loss is calculated and the classification model is optimized according to the clustering loss.The classification results can be obtained when the classification model is optimal.Compared with the existing unknown protocol recognition methods,the proposed method utilizes deep clustering to cluster the unknown protocols,and it can mine the key features of the protocol data and recognize the unknown protocols accurately.Experimental results show that the proposed method can effectively recognize the unknown protocols,and its performance is better than other methods.
基金financially supported by the National Natural Science Foundation of China (51704324, 52374027)Natural Science Foundation of Shandong Province (ZR2023ME158, ZR2022ME025)Open Fund of Key Laboratory of Tectonics and Petroleum Resources (TPR-2020-14)。
文摘Tri-axial fracturing studies were carried out to understand the impact of lateral mechanical parameters on fracture propagation from multiple in-plane perforations in horizontal wells. Additionally, the discussion covered the effects of geology, treatment, and perforation characteristics on the non-planar propagation behavior. According to experimental findings, two parallel transverse fractures can be successfully initiated from in-plane perforation clusters in the horizontal well because of the in-plane perforation, the guide nonuniform fishbone structure fracture propagation still can be exhibited. The emergence of transverse fractures and axial fractures combined as complex fractures under low horizontal principal stress difference and large pump rate conditions. The injection pressure was also investigated, and the largest breakdown pressure can be also found for samples under these conditions.The increase in perforation number or decrease in the cluster spacing could provide more chances to increase the complexity of the target stimulated zone, thus affecting the pressure fluctuation. In a contrast, the increase in fracturing fluid viscosity can reduce the multiple fracture complexity. The fracture propagation is significantly affected by the change in the rock mechanical properties. The fracture geometry in the high brittle zone seems to be complicated and tends to induce fracture reorientation from the weak-brittle zone. The stress shadow effect can be used to explain the fracture attraction, branch, connection, and repulsion in the multiple perforation clusters for the horizontal well.The increase in the rock heterogeneity can enhance the stress shadow effect, resulting in more complex fracture geometry. In addition, the variable density perforation and temporary plugging fracturing were also conducted, demonstrating higher likelihood for non-uniform multiple fracture propagation. Thus, to increase the perforation efficiency along the horizontal well, it is necessary to consider the lateral fracability of the horizontal well on target formation.
基金supported by the National Natural Science Foundation of China(22075133,62288102,22375091,21971114,and 21701086)the Jiangsu Provincial Funds(BX2022013)。
文摘Au is considered as one of the most promising catalysts for nitrogen reduction reaction(NRR),however maximizing the activity utilization rate of Au and understanding the synergistic effects between Au and carriers pose ongoing challenges.Herein,we systematically explore the synergistic catalytic effect of incorporating Au with boron clusters for accelerating NRR kinetics.An in-situ abinitio strategy is employed to construct B-doped Au nanoparticles(2-6 nm in diameter)loaded on BO_(x) substrates(AuBO_(x)),in which B not only modulates the surface electronic structure of Au but also forms strong coupling interactions to stabilize the nanoparticles.The electrochemical results show that Au-BO_(x) possesses excellent NRR activity(NH_(3) yield of 48.52μg h^(-1)mg_(cat)^(-1),Faraday efficiency of 56.18%),and exhibits high stability and reproducibility throughout the electrocatalytic NRR process.Theoretical calculations reveal that the introduction of B induces the formation of both Au dangling bond and Au-B coupling bond.which considerably facilitates the hydrogenation of~*N_(2)^(-)~*NH_(3).The present work provides a new avenue for the preparation of metal-boron materials achieved by one-step reduction and doping process,utilizing boron clusters as reducing and stabilizing agents.
基金the National Natural Science Foundation of China(Grant No.62101579).
文摘Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.
基金supported by the Key Technology Projects of the China Southern Power Grid Corporation(STKJXM20200059)the Key Support Project of the Joint Fund of the National Natural Science Foundation of China(U22B20123)。
文摘With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.
基金supported by the National Natural Science Foundation of China(No.U1967212)the Fundamental Research Funds for the Central Universities(No.2021MS032)the Nuclear Materials Innovation Foundation(No.WDZC-2023-AW-0305)。
文摘The evolution of dislocation loops in austenitic steels irradiated with Fe^(+)is investigated using cluster dynamics(CD)simulations by developing a CD model.The CD predictions are compared with experimental results in the literature.The number density and average diameter of the dislocation loops obtained from the CD simulations are in good agreement with the experimental data obtained from transmission electron microscopy(TEM)observations of Fe~+-irradiated Solution Annealed 304,Cold Worked 316,and HR3 austenitic steels in the literature.The CD simulation results demonstrate that the diffusion of in-cascade interstitial clusters plays a major role in the dislocation loop density and dislocation loop growth;in particular,for the HR3 austenitic steel,the CD model has verified the effect of temperature on the density and size of the dislocation loops.
基金Project supported by the National Natural Science Foundation of China(Grant No.62275075)the Science and Technology Research Program of the Education Department of Hubei Province,China(Grant No.B2022188)+2 种基金the Natural Science Foundation of Hubei Province,China(Grant No.2023AFC042)the Training Program of Innovation and Entrepreneurship for Undergraduates of Hubei Province,China(Grant No.S202210927003)the Medical Project of Hubei University of Science and Technology(Grant No.2023YKY08)。
文摘We propose an approach for generating robust two-dimensional(2D)vortex clusters(VCs)in a Rydberg atomic system by utilizing parity-time(PT)symmetric optical Bessel potential.We show that the system supports novel multicore VCs with four and eight cores,corresponding to topological charges 2 and 4,respectively.The stability of these VCs can be dynamically adjusted through the manipulation of the gain-loss component,Kerr nonlinearities,and the degree of nonlocality inherent in the Rydberg atoms.These VCs are confined within the first lattice well of the Bessel potential,and both the power and width of lights undergo a quasi-periodic breathing phenomenon,which is attributed to the power exchange between the light fields and Bessel potential.Both self-attractive and self-repulsive Kerr interactions can sustain robust VCs within this system.The insights presented here not only facilitate the creation and manipulation of 2D VCs through PT-symmetric potentials but also pave the way for potential applications in optical information processing and transmission.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB34030000)the National Key Research and Development Program of China(No.2022YFA1602404)+1 种基金National Natural Science Foundation(Nos.U1832129 and 11975210)Youth Innovation Promotion Association CAS(No.2017309)。
文摘The exploration of exotic shapes and properties of atomic nuclei,e.g.,αcluster and toroidal shape,is a fascinating field in nuclear physics.To study the decay of these nuclei,a novel detector aimed at detecting multipleα-particle events was designed and constructed.The detector comprises two layers of double-sided silicon strip detectors(DSSD)and a cesium iodide scintillator array coupled with silicon photomultipliers array as light sensors,which has the advantages of their small size,fast response,and large dynamic range.DSSDs coupled with cesium iodide crystal arrays are used to distinguish multipleαhits.The detector array has a compact and integrated design that can be adapted to different experimental conditions.The detector array was simulated using Geant4,and the excitation energy spectra of someα-clustering nuclei were reconstructed to demonstrate the performance.The simulation results show that the detector array has excellent angular and energy resolutions,enabling effective reconstruction of the nuclear excited state by multipleαparticle events.This detector offers a new and powerful tool for nuclear physics experiments and has the potential to discover interesting physical phenomena related to exotic nuclear structures and their decay mechanisms.
基金financially supported by the National Natural Science Foundation of China(22279036)the Innovation Talent Recruitment Base of New Energy Chemistry Device(B21003)the Fundamental Research Funds for the Central Universities(no.2019kfyRCPY100).
文摘Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enhanced electrocatalytic performance,simultaneously provide a radical analysis of the interrelationship between structure and activity.In this review,the recent advances of single-atomic site catalysts coupled with clusters or nanoparticles are emphasized.Firstly,the synthetic strategies,characterization,dynamics and types of single atoms coupled with clusters/nanoparticles are introduced,and then the key factors controlling the structure of the composite catalysts are discussed.Next,several clean energy catalytic reactions performed over the synergistic composite catalysts are illustrated.Eventually,the encountering challenges and recommendations for the future advancement of synergistic structure in energy-transformation electrocatalysis are outlined.
