Understanding CO_(2) diffusion behavior in functional nanoporous materials is beneficial for improving the CO_(2) adsorption,separation,and conversion performances.However,it is a great challenge for studying the diff...Understanding CO_(2) diffusion behavior in functional nanoporous materials is beneficial for improving the CO_(2) adsorption,separation,and conversion performances.However,it is a great challenge for studying the diffusion process in experiments.Herein,CO_(2) diffusion in 962 metal–organic frameworks(MOFs)with open Cu sites was systematically investigated by theoretical methods in the combination of molecular dynamic simulations and density functional theory(DFT)calculations.A specific force field was derived from DFT-D2 method combined with Grimme’s dispersion-corrected(D2)density functional to well describe the interaction energies between Cu and CO_(2).It is observed that the suitable topology is conductive to CO_(2) diffusion,and 2D-MOFs are more flexible in tuning and balancing the CO_(2) adsorption and diffusion behaviors than 3D-MOFs.In addition,analysis of diffusive trajectories and the residence times on different positions indicate that CO_(2) diffusion is mainly along with the frameworks in these MOFs,jumping from one strong adsorption site to another.It is also influenced by the electrostatic interaction of the frameworks.Therefore,the obtained information may provide useful guidance for the rational design and synthesis of MOFs with enhanced CO_(2) diffusion performance for specific applications.展开更多
The global rapid transition towards sustainable energy systems has heightened the demand for highperformance lithium metal batteries(LMBs),where understanding interfacial phenomena is paramount.In this contribution,we...The global rapid transition towards sustainable energy systems has heightened the demand for highperformance lithium metal batteries(LMBs),where understanding interfacial phenomena is paramount.In this contribution,we present an on-the-fly machine learning molecular dynamics(OTF-MLMD)approach to probe the complex side reactions at lithium metal anode–electrolyte interfaces with exceptional accuracy and computational efficiency.The machine learning force field(MLFF)was firstly validated in a bulk-phase system comprising twenty 1,2-dimethoxyethane(DME)molecules,demonstrating energy fluctuations and structural parameters in close agreement with ab initio molecular dynamics(AIMD)benchmarks.Subsequent simulations of lithium–DME and lithium–electrolyte interfaces revealed minimal discrepancies in energy,bond lengths,and net charge variations(notably in FSI-species),underscoring the method's DFT-level precision of the approach.A further small-scale interfacial model enabled on-the-fly training over a mere of 340 fs,which was then successfully transferred to a large-scale simulation encompassing nearly 300,000 atoms,representing the largest interfacial model in LMB research up to date.The hierarchical validation strategy not only establishes the robustness of the MLFF in capturing both interfacial and bulk-phase chemistry but also paves the way for statistically meaningful simulations of battery interfaces.The fruitful findings highlight the transformative potential of OTF-MLMD in bridging the gap between atomistic accuracy and macroscopic modeling,affording a universal approach to understand interfacial reactions in LMBs.展开更多
Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise re...Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.展开更多
Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theori...Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theories and algorithms.This paper begins by providing illustrative examples that highlight the differences between large-scale SO problems and those of a more moderate scale.Subsequently,it reviews several widely employed techniques for addressing large-scale SOproblems,such as divide-and-conquer,dimension reduction,and gradient-based algorithms.Additionally,the paper examines parallelization techniques leveraging widely accessible parallel computing environments to facilitate the resolution of large-scale SO problems.展开更多
Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynam...Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.展开更多
Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities ofte...Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.展开更多
Summer rainfall in the Yangtze River basin(YRB)is favored by two key factors in the lower troposphere:the tropical anticyclonic anomaly over the western North Pacific and the extratropical northeasterly anomalies to t...Summer rainfall in the Yangtze River basin(YRB)is favored by two key factors in the lower troposphere:the tropical anticyclonic anomaly over the western North Pacific and the extratropical northeasterly anomalies to the north of the YRB.This study,however,found that approximately 46%of heavy rainfall events in the YRB occur when only one factor appears and the other is opposite signed.Accordingly,these heavy rainfall events can be categorized into two types:the extratropical northeasterly anomalies but tropical cyclonic anomaly(first unconventional type),and the tropical anticyclonic anomaly but extratropical southwesterly anomalies(second unconventional type).Anomalous water vapor convergence and upward motion exists for both types,but through different mechanisms.For the first type,the moisture convergence and upward motion are induced by a cyclonic anomaly over the YRB,which appears in the mid and lower troposphere and originates from the upstream region.For the second type,a mid-tropospheric cyclonic anomaly over Lake Baikal extends southward and results in southwesterly anomalies over the YRB,in conjunction with the tropical anticyclonic anomaly.The southwesterly anomalies transport water vapor to the YRB and lead to upward motion through warm advection.This study emphasizes the role of mid-tropospheric circulations in inducing heavy rainfall in the YRB.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.展开更多
This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the ...This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the design process,we transform the studied system into the form of a fully actuated system through a state transformation.Then,to address the unknown nonlinear functions and actuator fault parameters,we employ neural networks and adaptive estimation techniques,respectively.Moreover,to reduce the control cost and improve the control efficiency,we introduce event-triggered inputs into the control strategy.It is proved by the Lyapunov stability analysis that all signals of the closed-loop system are bounded and the output of system eventually converge to a bounded region.The efficacy of the control approach is ultimately demonstrated via the simulation of an actual machine feeding system.展开更多
Atomistic simulations were adopted to study the solute segregation effect on dislocation transmutation across the{1012}twin boundaries in magnesium.For pure magnesium,the dislocation-twin reaction resulted in the form...Atomistic simulations were adopted to study the solute segregation effect on dislocation transmutation across the{1012}twin boundaries in magnesium.For pure magnesium,the dislocation-twin reaction resulted in the formation of sessile dislocations accompanied by the fast migration of the twin boundary,and no〈c+a〉dislocation occurred.With Al segregation,instead,two basal dislocations transmuted into one prismatic〈c+a〉dislocation in the twin.Twin migration was significantly impeded,and the resultant twin disconnections stayed localized and had a higher step character than in pure Mg.To reveal the mechanism of the effect of solute segregation,the Peierls barriers of twin disconnections were calculated,and the dynamic evolutions of twin disconnection dipoles were simulated.The results suggested that Al segregation softened the Peierls barrier of twin disconnections but imposed a high pinning force on twin disconnections,thus attenuating their mobility.Moreover,given the same Al segregation,the twin disconnection dipole with a higher step showed greater stability,which explained the presence of localized twin disconnections with a higher step in the cases with Al segregation than in pure magnesium.The solute segregation induced low mobility of twin disconnections contributed to the occurrence of〈c+a〉dislocations.展开更多
The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segmen...The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segment forming the ATP catalytic pocket is highly conserved.Single-molecule experiments,however,have revealed subtle differences in efficiency between the F_(1) and V_(1) motors.Here,we perform both atomistic and coarse-grained molecular dynamics simulations to investigate the mechanochemical coupling and coordination in F_(1) and V_(1) ATPase.Our results show that the correlation between conformational changes in F_(1) is stronger than that in V_(1),indicating that the mechanochemical coupling in F_(1) is tighter than in V_(1).Moreover,the unidirectional rotation of F_(1) is more processive than that of V_(1),which accounts for the higher efficiency observed in F_(1) and explains the occasional backward steps detected in single-molecule experiments on V_(1).展开更多
The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-ti...The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.展开更多
Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between th...Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.展开更多
In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mec...In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mechanisms during aggregation,it is difficult to conduct effective backdoor attacks.In addition,existing backdoor attack methods are faced with challenges,such as low backdoor accuracy,poor ability to evade anomaly detection,and unstable model training.To address these challenges,a method called adaptive simulation backdoor attack(ASBA)is proposed.Specifically,ASBA improves the stability of model training by manipulating the local training process and using an adaptive mechanism,the ability of the malicious model to evade anomaly detection by combing large simulation training and clipping,and the backdoor accuracy by introducing a stimulus model to amplify the impact of the backdoor in the global model.Extensive comparative experiments under five advanced defense scenarios show that ASBA can effectively evade anomaly detection and achieve high backdoor accuracy in the global model.Furthermore,it exhibits excellent stability and effectiveness after multiple rounds of attacks,outperforming state-of-the-art backdoor attack methods.展开更多
UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechani...UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechanical properties are unclear.Molecular dynamics simulations are valuable but often limited by computational constraints.Our aim is to simulate higher molecular weights to better represent real UHMWPE fibers.We used Packmol and Polyply methodologies to construct PE systems,with Polyply reproducing more reasonable properties of UHMWPE fibers.Additionally,tensile simulations showed that orientation and crystallinity greatly impact Young's modulus more than molecular weight.Energy decomposition indicated that higher molecular weights lead to covalent bonds that can withstand more energy during stretching,thus increasing breaking strength.Combining simulations with machine learning,we found that orientation has the most significant impact on Young's modulus,contributing 60%,and molecular weight plays the most crucial role in determining the breaking strength,accounting for 65%.This study provides a theoretical basis and guidelines for enhancing UHMWPE's modulus and strength.展开更多
With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyz...With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.展开更多
基金supported by National Key Research and Develop-ment Program of China(2016YFB0600901)the Natural Science Foundation of China(22038010,21878229,22078024 and 21978005).
文摘Understanding CO_(2) diffusion behavior in functional nanoporous materials is beneficial for improving the CO_(2) adsorption,separation,and conversion performances.However,it is a great challenge for studying the diffusion process in experiments.Herein,CO_(2) diffusion in 962 metal–organic frameworks(MOFs)with open Cu sites was systematically investigated by theoretical methods in the combination of molecular dynamic simulations and density functional theory(DFT)calculations.A specific force field was derived from DFT-D2 method combined with Grimme’s dispersion-corrected(D2)density functional to well describe the interaction energies between Cu and CO_(2).It is observed that the suitable topology is conductive to CO_(2) diffusion,and 2D-MOFs are more flexible in tuning and balancing the CO_(2) adsorption and diffusion behaviors than 3D-MOFs.In addition,analysis of diffusive trajectories and the residence times on different positions indicate that CO_(2) diffusion is mainly along with the frameworks in these MOFs,jumping from one strong adsorption site to another.It is also influenced by the electrostatic interaction of the frameworks.Therefore,the obtained information may provide useful guidance for the rational design and synthesis of MOFs with enhanced CO_(2) diffusion performance for specific applications.
基金supported by the National Key Research and Development Program(2021YFB2500300)the National Natural Science Foundation of China(T2322015,92472101,22393903,22393900,and 52394170)+1 种基金the Beijing Municipal Natural Science Foundation(L247015 and L233004)Tsinghua University Initiative Scientific Research Program。
文摘The global rapid transition towards sustainable energy systems has heightened the demand for highperformance lithium metal batteries(LMBs),where understanding interfacial phenomena is paramount.In this contribution,we present an on-the-fly machine learning molecular dynamics(OTF-MLMD)approach to probe the complex side reactions at lithium metal anode–electrolyte interfaces with exceptional accuracy and computational efficiency.The machine learning force field(MLFF)was firstly validated in a bulk-phase system comprising twenty 1,2-dimethoxyethane(DME)molecules,demonstrating energy fluctuations and structural parameters in close agreement with ab initio molecular dynamics(AIMD)benchmarks.Subsequent simulations of lithium–DME and lithium–electrolyte interfaces revealed minimal discrepancies in energy,bond lengths,and net charge variations(notably in FSI-species),underscoring the method's DFT-level precision of the approach.A further small-scale interfacial model enabled on-the-fly training over a mere of 340 fs,which was then successfully transferred to a large-scale simulation encompassing nearly 300,000 atoms,representing the largest interfacial model in LMB research up to date.The hierarchical validation strategy not only establishes the robustness of the MLFF in capturing both interfacial and bulk-phase chemistry but also paves the way for statistically meaningful simulations of battery interfaces.The fruitful findings highlight the transformative potential of OTF-MLMD in bridging the gap between atomistic accuracy and macroscopic modeling,affording a universal approach to understand interfacial reactions in LMBs.
基金supported by the National Natural Science Foundation of China(Grant Nos.12302435 and 12221002)。
文摘Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.
基金supported by the National Natural Science Foundation of China(Nos.72071146,72091211,72293562,and 72031006).
文摘Large-scale simulation optimization(SO)problems encompass both large-scale ranking-and-selection problems and high-dimensional discrete or continuous SO problems,presenting significant challenges to existing SO theories and algorithms.This paper begins by providing illustrative examples that highlight the differences between large-scale SO problems and those of a more moderate scale.Subsequently,it reviews several widely employed techniques for addressing large-scale SOproblems,such as divide-and-conquer,dimension reduction,and gradient-based algorithms.Additionally,the paper examines parallelization techniques leveraging widely accessible parallel computing environments to facilitate the resolution of large-scale SO problems.
基金Supported by the National Natural Science Foundation of China(Nos.52293472,22473096 and 22471164)。
文摘Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.
文摘Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.
基金supported by the National Natural Science Foundation of China(Grant No.42275041)the Hainan Province Science and Technology Special Fund(Grant No.SOLZSKY2025006).
文摘Summer rainfall in the Yangtze River basin(YRB)is favored by two key factors in the lower troposphere:the tropical anticyclonic anomaly over the western North Pacific and the extratropical northeasterly anomalies to the north of the YRB.This study,however,found that approximately 46%of heavy rainfall events in the YRB occur when only one factor appears and the other is opposite signed.Accordingly,these heavy rainfall events can be categorized into two types:the extratropical northeasterly anomalies but tropical cyclonic anomaly(first unconventional type),and the tropical anticyclonic anomaly but extratropical southwesterly anomalies(second unconventional type).Anomalous water vapor convergence and upward motion exists for both types,but through different mechanisms.For the first type,the moisture convergence and upward motion are induced by a cyclonic anomaly over the YRB,which appears in the mid and lower troposphere and originates from the upstream region.For the second type,a mid-tropospheric cyclonic anomaly over Lake Baikal extends southward and results in southwesterly anomalies over the YRB,in conjunction with the tropical anticyclonic anomaly.The southwesterly anomalies transport water vapor to the YRB and lead to upward motion through warm advection.This study emphasizes the role of mid-tropospheric circulations in inducing heavy rainfall in the YRB.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
基金supported by the Science Center Program of National Natural Science Foundation of China under Grant 62188101the National Natural Science Foundation of China under Grant 62573265.
文摘This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the design process,we transform the studied system into the form of a fully actuated system through a state transformation.Then,to address the unknown nonlinear functions and actuator fault parameters,we employ neural networks and adaptive estimation techniques,respectively.Moreover,to reduce the control cost and improve the control efficiency,we introduce event-triggered inputs into the control strategy.It is proved by the Lyapunov stability analysis that all signals of the closed-loop system are bounded and the output of system eventually converge to a bounded region.The efficacy of the control approach is ultimately demonstrated via the simulation of an actual machine feeding system.
基金supported by the National Natural Science Foundation of China(52071039 and 52301156)National Natural Science Foundation of Jiangsu Province of China(BK20241873)Natural Science Foundation of Jiangsu Province(BK20232025 and BK20243005)are greatly acknowledged.
文摘Atomistic simulations were adopted to study the solute segregation effect on dislocation transmutation across the{1012}twin boundaries in magnesium.For pure magnesium,the dislocation-twin reaction resulted in the formation of sessile dislocations accompanied by the fast migration of the twin boundary,and no〈c+a〉dislocation occurred.With Al segregation,instead,two basal dislocations transmuted into one prismatic〈c+a〉dislocation in the twin.Twin migration was significantly impeded,and the resultant twin disconnections stayed localized and had a higher step character than in pure Mg.To reveal the mechanism of the effect of solute segregation,the Peierls barriers of twin disconnections were calculated,and the dynamic evolutions of twin disconnection dipoles were simulated.The results suggested that Al segregation softened the Peierls barrier of twin disconnections but imposed a high pinning force on twin disconnections,thus attenuating their mobility.Moreover,given the same Al segregation,the twin disconnection dipole with a higher step showed greater stability,which explained the presence of localized twin disconnections with a higher step in the cases with Al segregation than in pure magnesium.The solute segregation induced low mobility of twin disconnections contributed to the occurrence of〈c+a〉dislocations.
基金supported by the National Natural Science Foundation of China(Grant Nos.22193032 and 32401033)the Research Fund of Wenzhou Institute,Chinese Academy of Sciences(Grant Nos.WIUCASQD2020009,WIUCASQD2023005,XSZD2024004,2021HZSY0061,and WIUCASICTP2022)。
文摘The F_(1)-ATPase and V_(1)-ATPase are rotary biomotors.Alignment of their amino acid sequences,which originate from bovine heart mitochondria(1BMF)and Enterococcus hirae(3VR6),respectively,demonstrates that the segment forming the ATP catalytic pocket is highly conserved.Single-molecule experiments,however,have revealed subtle differences in efficiency between the F_(1) and V_(1) motors.Here,we perform both atomistic and coarse-grained molecular dynamics simulations to investigate the mechanochemical coupling and coordination in F_(1) and V_(1) ATPase.Our results show that the correlation between conformational changes in F_(1) is stronger than that in V_(1),indicating that the mechanochemical coupling in F_(1) is tighter than in V_(1).Moreover,the unidirectional rotation of F_(1) is more processive than that of V_(1),which accounts for the higher efficiency observed in F_(1) and explains the occasional backward steps detected in single-molecule experiments on V_(1).
基金supported by the Advanced Materials-National Science and Technology Major Project(Grant No.2025ZD0618401)the National Natural Science Foundation of China(Grant No.12504285)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20250472)NFSG grant from BITS-Pilani,Dubai campus。
文摘The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.
基金financially supported by the National Natural Science Foundation of China(Nos.52173020 and 52573023)。
文摘Vitrimers belong to a class of polymeric materials capable of bond exchange reactions,showing great promise for environmental protection and sustainable development.However,studies on the coupling mechanism between the bond exchange kinetics and segmental dynamics near the glass transition temperature(T_(g))remain scarce.Herein,we employed molecular dynamics simulations to investigate the dynamic heterogeneity of the segment motion and bond exchange in vitrimers.The simulation results revealed that the bond exchange energy barrier exerts a much stronger influence on the bond exchange kinetics than on the segmental dynamics.At lower temperatures,slower segmental relaxation further constraind the bond exchange rate.Additionally,increasing the bond exchange energy barrier markedly enhanced the dynamic heterogeneity of segment motion.A close correlation was observed between heterogeneity and bond exchange.This study elucidated the coupling mechanism between bond exchange and segmental dynamics at the molecular scale,thereby providing a theoretical basis for designing vitrimer materials with tunable dynamic properties.
文摘In federated learning,backdoor attacks have become an important research topic with their wide application in processing sensitive datasets.Since federated learning detects or modifies local models through defense mechanisms during aggregation,it is difficult to conduct effective backdoor attacks.In addition,existing backdoor attack methods are faced with challenges,such as low backdoor accuracy,poor ability to evade anomaly detection,and unstable model training.To address these challenges,a method called adaptive simulation backdoor attack(ASBA)is proposed.Specifically,ASBA improves the stability of model training by manipulating the local training process and using an adaptive mechanism,the ability of the malicious model to evade anomaly detection by combing large simulation training and clipping,and the backdoor accuracy by introducing a stimulus model to amplify the impact of the backdoor in the global model.Extensive comparative experiments under five advanced defense scenarios show that ASBA can effectively evade anomaly detection and achieve high backdoor accuracy in the global model.Furthermore,it exhibits excellent stability and effectiveness after multiple rounds of attacks,outperforming state-of-the-art backdoor attack methods.
基金financially supported by the National Natural Science Foundation of China(Nos.52303298 and 52233002)。
文摘UHMWPE fibers exhibit impressive modulus and strength,but they have not reached their theoretical limits.Researchers focus on molecular weight,orientation,and crystallinity of UHMWPE,yet their contributions to mechanical properties are unclear.Molecular dynamics simulations are valuable but often limited by computational constraints.Our aim is to simulate higher molecular weights to better represent real UHMWPE fibers.We used Packmol and Polyply methodologies to construct PE systems,with Polyply reproducing more reasonable properties of UHMWPE fibers.Additionally,tensile simulations showed that orientation and crystallinity greatly impact Young's modulus more than molecular weight.Energy decomposition indicated that higher molecular weights lead to covalent bonds that can withstand more energy during stretching,thus increasing breaking strength.Combining simulations with machine learning,we found that orientation has the most significant impact on Young's modulus,contributing 60%,and molecular weight plays the most crucial role in determining the breaking strength,accounting for 65%.This study provides a theoretical basis and guidelines for enhancing UHMWPE's modulus and strength.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China,grant number 21YJA790009National Natural Science Foundation of China,grant number 72140001.
文摘With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.
