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
Tunneling diodes hold significant promise for future rectification in the terahertz(THz)and visible light spectra,thanks to their femtosecond-scale transit-time tunneling capabilities.In this work,TiN/ZnO/Pt fin tunne...Tunneling diodes hold significant promise for future rectification in the terahertz(THz)and visible light spectra,thanks to their femtosecond-scale transit-time tunneling capabilities.In this work,TiN/ZnO/Pt fin tunneling diodes(FTDs)with tunneling distances of 10 and 5 nm are fabricated,which demonstrate remarkable characteristics,including ultrahigh asymmetry(1.6×10^(4)for 10 nm device and 1.6×10^(3) for 5 nm device),high responsivity(25.3 V^(-1) for 10 nm device and 28.3 V^(-1) for 5 nm device)at zero bias,surpassing the thermal voltage limit of conventional Schottky diodes,and low turn-on voltage(V_(on))of approximately 100 mV for both devices,making them ideal for power conversion applications.Using technology computer-aided design(TCAD)simulations,the observed asymmetry in electronic transport is attributed to the transition between Fowler-Nordheim tunneling(FNT)and trap-assisted tunneling(TAT)under different biasing conditions,as illustrated by the corresponding energy band profiles.Furthermore,by integrating the FTDs,a rectifier bridge circuit is designed and exhibits full-wave rectification behavior,validated through SPICE simulations for THz-band operations.This advancement offers a highly efficient solution for THz-band energy conversion and effective detection applications.展开更多
Combining the phase-field method and the moving boundary method,a three-dimensional phase-field simulation was conducted for the growth and grain evolution of Ti films deposited by physical vapor deposition under diff...Combining the phase-field method and the moving boundary method,a three-dimensional phase-field simulation was conducted for the growth and grain evolution of Ti films deposited by physical vapor deposition under different deposition rates and grain orientations.The evolution of grain morphology and grain orientation was also taken into consideration.Simulation results show that at lower deposition rates,the surface of the formed Ti film exhibits a distinct oriented texture structure.The surface roughness of the Ti film is positively correlated with the grain misorientation.Moreover,the surface roughness obtained from the simulation is in good agreement with the experiment results.展开更多
The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the...The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the TiNb binary alloy system during spinodal decomposition,and then the formation mechanism of core-shell structure was revealed.In addition,the influences of initial temperature gradient,average temperature,and initial concentration distribution of the system on the core-shell structure were investigated.Results show that the initial concentration gradient is the key factor for forming the core-shell structure.Besides,larger initial temperature gradient and higher average temperature can promote the formation of core-shell structure,which can be stabilized by adjusting the initial concentration distribution of the Nb-rich region in TiNb binary alloy.As a theoretical basis,this research provides a novel and simple strategy for the preparation of TiNb-based alloys and other materials with peculiar core-shell structures and desirable mechanical and physical properties.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
There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution...There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.展开更多
Water storage in the Three Gorges Reservoir in China has increased the regional microseismicity.Bedding-rock landslides,one of the most common slope structures in the Three Gorges Reservoir,are highly prone to sliding...Water storage in the Three Gorges Reservoir in China has increased the regional microseismicity.Bedding-rock landslides,one of the most common slope structures in the Three Gorges Reservoir,are highly prone to sliding under seismic loading.Existing research primarily focuses on the stability of bedding rock landslides under strong earthquakes,while studies on the cumulative damage and long-term stability of bedding rock landslides under high-frequency microseismicity remain immature.In this study,we considered bedding rock landslides under high-frequency microseismicity in the Three Gorges Reservoir area as the research subject and equivalent microseismicity as pre-peak cyclic loading.First,we analyzed the shear strength deterioration of rock mass structural planes under pre-peak cyclic loading conditions and found that the deformation and failure of structural planes involve contact and damage effects.The shear strength of the rock mass structural planes under pre-peak cyclic loading conditions is affected by the confining pressure,loading rate,loading amplitude,and number of loading cycles.Among these factors,the shear strength of the structural planes was the most sensitive to the number of loading cycles.As the number of cycles increased,the rock mass structural planes underwent three stages:stress adjustment(increase in shear strength),fatigue damage(gradual decrease in shear strength),and structural failure(rapid decrease in shear strength).The stability of bedding rock landslides under high-frequency microseismicity was analyzed,revealing that the stability of bedding rock landslides under high-frequency microseismicity can be divided into three stages:short-term enhancement,gradual degradation,and rapid deterioration,exhibiting characteristics of gradual and sudden changes.展开更多
Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicate...Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.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
In this paper,a fast step heterodyne light-induced thermoelastic spectroscopy(SH-LITES)sensor using a high-frequency quartz tuning fork(QTF)with resonant frequency of~100 kHz is reported for the first time.The theoret...In this paper,a fast step heterodyne light-induced thermoelastic spectroscopy(SH-LITES)sensor using a high-frequency quartz tuning fork(QTF)with resonant frequency of~100 kHz is reported for the first time.The theoretical principle of heterodyne LITES(H-LITES)signal generation is analyzed firstly,and an acetylene(C_(2)H_(2))H-LITES sensor is established to verify its performance.Experimental comparisons between the high-frequency QTF and a standard commercial QTF with resonant frequency of~32.768 kHz reveal that the high-frequency QTF exhibits a tenfold faster response time.Specifically,the H-LITES sensor with this QTF achieves a 33 ms measurement cycle,90%shorter than commercial counterparts.Furthermore,The SH-LITES technique is proposed to further shorten the scanning time to 15 ms,which achieves the shortest LITES measurement time known to date.To demonstrate its advantages in dynamic gas detection,an H_(2)O-LITES system integrating both QTF types is constructed for real-time monitoring of H_(2)O concentration during different respiration patterns.Comparative measurements show that the SH-LITES more accurately captures dynamic H_(2)O concentration fluctuations during respiration,outperforming the commercial QTF-based H-LITES sensor in rapid response scenarios.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
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National Key Research and Development Program of China(2024YFA1410700,2021YFA1200700)National Natural Science Foundation of China(62474065,T2222025,62174053)+3 种基金Natural Science Foundation of Chongqing(CSTB2024NSCQ-JQX0005)Shanghai Science and Technology Innovation Action Plan(24QA2702300,24YF2710400)National Postdoctoral Program(GZB20240225)Fundamental Research Funds for the Central Universities。
文摘Tunneling diodes hold significant promise for future rectification in the terahertz(THz)and visible light spectra,thanks to their femtosecond-scale transit-time tunneling capabilities.In this work,TiN/ZnO/Pt fin tunneling diodes(FTDs)with tunneling distances of 10 and 5 nm are fabricated,which demonstrate remarkable characteristics,including ultrahigh asymmetry(1.6×10^(4)for 10 nm device and 1.6×10^(3) for 5 nm device),high responsivity(25.3 V^(-1) for 10 nm device and 28.3 V^(-1) for 5 nm device)at zero bias,surpassing the thermal voltage limit of conventional Schottky diodes,and low turn-on voltage(V_(on))of approximately 100 mV for both devices,making them ideal for power conversion applications.Using technology computer-aided design(TCAD)simulations,the observed asymmetry in electronic transport is attributed to the transition between Fowler-Nordheim tunneling(FNT)and trap-assisted tunneling(TAT)under different biasing conditions,as illustrated by the corresponding energy band profiles.Furthermore,by integrating the FTDs,a rectifier bridge circuit is designed and exhibits full-wave rectification behavior,validated through SPICE simulations for THz-band operations.This advancement offers a highly efficient solution for THz-band energy conversion and effective detection applications.
基金National MCF Energy R&D Program of China(2018YFE0306100)Natural Science Foundation of Hunan Province for Distinguished Young Scholars(2021JJ10062)+1 种基金National Natural Science Foundation of China(52101028)China Postdoctoral Science Foundation(2021M703628)。
文摘Combining the phase-field method and the moving boundary method,a three-dimensional phase-field simulation was conducted for the growth and grain evolution of Ti films deposited by physical vapor deposition under different deposition rates and grain orientations.The evolution of grain morphology and grain orientation was also taken into consideration.Simulation results show that at lower deposition rates,the surface of the formed Ti film exhibits a distinct oriented texture structure.The surface roughness of the Ti film is positively correlated with the grain misorientation.Moreover,the surface roughness obtained from the simulation is in good agreement with the experiment results.
基金National Natural Science Foundation of China(12372152)Guangdong Basic and Applied Basic Research Foundation(2023A1515011819,2024A1515012469)Shandong Provincial Natural Science Foundation(ZR2023MA058)。
文摘The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the TiNb binary alloy system during spinodal decomposition,and then the formation mechanism of core-shell structure was revealed.In addition,the influences of initial temperature gradient,average temperature,and initial concentration distribution of the system on the core-shell structure were investigated.Results show that the initial concentration gradient is the key factor for forming the core-shell structure.Besides,larger initial temperature gradient and higher average temperature can promote the formation of core-shell structure,which can be stabilized by adjusting the initial concentration distribution of the Nb-rich region in TiNb binary alloy.As a theoretical basis,this research provides a novel and simple strategy for the preparation of TiNb-based alloys and other materials with peculiar core-shell structures and desirable mechanical and physical properties.
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 National Nature Science Foundation of China(Nos.12027901 and 12041202)Synchrotron Radiation Joint Fund of University of Science and Technology of China(Nos.KY2090000059 and KY2090000054)。
文摘There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.
基金sponsored by the General Program of the National Natural Science Foundation of China(Grant No.42407221)the Open Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Grant No.SKLGP2024K009)the Hubei Provincial Natural Science Foun-dation,China(Grant No.2023AFB567).
文摘Water storage in the Three Gorges Reservoir in China has increased the regional microseismicity.Bedding-rock landslides,one of the most common slope structures in the Three Gorges Reservoir,are highly prone to sliding under seismic loading.Existing research primarily focuses on the stability of bedding rock landslides under strong earthquakes,while studies on the cumulative damage and long-term stability of bedding rock landslides under high-frequency microseismicity remain immature.In this study,we considered bedding rock landslides under high-frequency microseismicity in the Three Gorges Reservoir area as the research subject and equivalent microseismicity as pre-peak cyclic loading.First,we analyzed the shear strength deterioration of rock mass structural planes under pre-peak cyclic loading conditions and found that the deformation and failure of structural planes involve contact and damage effects.The shear strength of the rock mass structural planes under pre-peak cyclic loading conditions is affected by the confining pressure,loading rate,loading amplitude,and number of loading cycles.Among these factors,the shear strength of the structural planes was the most sensitive to the number of loading cycles.As the number of cycles increased,the rock mass structural planes underwent three stages:stress adjustment(increase in shear strength),fatigue damage(gradual decrease in shear strength),and structural failure(rapid decrease in shear strength).The stability of bedding rock landslides under high-frequency microseismicity was analyzed,revealing that the stability of bedding rock landslides under high-frequency microseismicity can be divided into three stages:short-term enhancement,gradual degradation,and rapid deterioration,exhibiting characteristics of gradual and sudden changes.
基金Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。
文摘Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.
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financial supports from the National Natural Science Foundation of China(Grant No.62335006,62275065,624B2050,62022032,and 62405078)Open Subject of Hebei Key Laboratory of Advanced Laser Technology and Equipment(HBKL-ALTE2025001)+2 种基金Heilongjiang Postdoctoral Fund(Grant No.LBH-Z23144 and LBH-Z24155)Natural Science Foundation of Heilongjiang Province(Grant No.LH2024F031)China Postdoctoral Science Foundation(Grant No.2024M764172).
文摘In this paper,a fast step heterodyne light-induced thermoelastic spectroscopy(SH-LITES)sensor using a high-frequency quartz tuning fork(QTF)with resonant frequency of~100 kHz is reported for the first time.The theoretical principle of heterodyne LITES(H-LITES)signal generation is analyzed firstly,and an acetylene(C_(2)H_(2))H-LITES sensor is established to verify its performance.Experimental comparisons between the high-frequency QTF and a standard commercial QTF with resonant frequency of~32.768 kHz reveal that the high-frequency QTF exhibits a tenfold faster response time.Specifically,the H-LITES sensor with this QTF achieves a 33 ms measurement cycle,90%shorter than commercial counterparts.Furthermore,The SH-LITES technique is proposed to further shorten the scanning time to 15 ms,which achieves the shortest LITES measurement time known to date.To demonstrate its advantages in dynamic gas detection,an H_(2)O-LITES system integrating both QTF types is constructed for real-time monitoring of H_(2)O concentration during different respiration patterns.Comparative measurements show that the SH-LITES more accurately captures dynamic H_(2)O concentration fluctuations during respiration,outperforming the commercial QTF-based H-LITES sensor in rapid response scenarios.
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.
