In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the...In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the critical elementary reaction of molybdenum catalysis.However,the relevant density functional theory(DFT)studies are relatively scarce,especially regarding the rational selection of functionals.In this work,14 functionals were employed to investigate the Mo-catalyzed carbonyl oxidative addition step.A benchmark study was carried out to evaluate their performance in structure optimization and energy calculation.Analyses of mean absolute error(MAE)and mean squared error(MSE)indicated that the B3LYP-D3(BJ),TPSSh,and ωB97X-D functionals exhibited superior performance in structure optimization.Using the DLPNO-CCSD(T)functional as the reference,the M06,M06-L,and MN15-L functionals exhibited good performance for energy calculation based on the structures optimized using the B3LYP-D3(BJ)functional.In particular,MN15-L provided the best performance with the smallest MAE and MSE.展开更多
The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous flui...The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.展开更多
Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overco...Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overcoming resistance in granular media when burrowing with forelimbs.In the absence of effective forepaw design strategies,most robotic designs rely on increased power to enhance performance.To address this issue,this paper employs Resistive Force Theory to optimize mole-inspired forepaws,aiming to enhance burrowing efficiency.By analyzing the relationship between geometric parameters and burrowing forces,we propose several forepaw design variations.Through granular resistance assessments,an effective forepaw configuration is identified and further refined using parameters such as longitudinal and transverse curvature.Subsequently,the Particle Swarm Optimization algorithm is applied to determine the optimal forepaw design.In force-loading tests,the optimized forepaw demonstrated a 79.44%reduction in granular lift force and a 22.55%increase in propulsive force compared with the control group.In robotic burrowing experiments,the optimized forepaw achieved the longest burrow displacement(179.528 mm)and the lowest burrowing lift force(0.9355 mm/s),verifying its effectiveness in reducing the lift force and enhancing the propulsive force.展开更多
In the wave of urbanization,waterfront landscape optimization is very important,but it is faced with ecological deterioration and other problems.By combing the relevant theories and practices at home and abroad and ma...In the wave of urbanization,waterfront landscape optimization is very important,but it is faced with ecological deterioration and other problems.By combing the relevant theories and practices at home and abroad and making a comparison and summary,the future direction of waterfront research was analyzed.In theory,foreign research has experienced multi-stage development,covering definition classification,design methods,etc.China started late,and is mainly in the exploration stage of learning from foreign experience and combining with local characteristics.The current research and practice have shortcomings such as ignoring users’needs and lacking quantitative evaluation.In the future,the construction of waterfront should focus on the needs of users,use scientific methods to build an evaluation system,integrate multi-disciplines,excavate regional culture,and establish a monitoring mechanism to achieve sustainable and coordinated development of the ecology,society and economy of waterfront.展开更多
Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse ...Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse of warm dense matter theory is thermal density functional theory(DFT),which,however,suffers from two limitations:(i)its accuracy can depend on the utilized exchange-correlation functional,which has to be approximated,and(ii)it is generally limited to single-electron properties such as the density distribution.Here,we present a new ansatz combining time-dependent DFT results for the dynamic structure factor S_(ee)(q,ω)with static DFT results for the density response.This allows us to estimate the electron-electron static structure factor S_(ee)(q)of warm dense hydrogen with high accuracy over a broad range of densities and temperatures.In addition to its value for the study of warm dense matter,our work opens up new avenues for the future study of electronic correlations exclusively within the framework of DFT for a host of applications.展开更多
Though the formation of polysulfide is desirable,as it contributes to the capacity build-up,it must not leak into the electrolyte.The loss of polysulfide causes capacity fade,a change in the local chemistry of the ele...Though the formation of polysulfide is desirable,as it contributes to the capacity build-up,it must not leak into the electrolyte.The loss of polysulfide causes capacity fade,a change in the local chemistry of the electrolyte,and anode poisoning.Constant efforts are in progress to find suitable polysulfide-absorbing materials;however,the magical polysulfide absorber is yet to be discovered or developed.Experimental methods alone often fall short in accelerating the investigations may be due to the complex Nature of the testing.This review focuses on the importance of computational methods,particularly density functional theory(DFT),in screening suitable polysulfide absorbers.It highlights the critical role of anchoring materials in improving Na-S battery performance,including pristine and doped graphene,metal–organic frameworks,carbon Nanofibers,vanadium disulfide,MXenes,and metal sulfides.By examining adsorption energies,charge transfer mechanisms,and catalytic properties,this review provides insights into the design of advanced materials that can effectively immobilize polysulfides and enhance battery stability.The review aims to guide future research efforts toward the development of high-performance RT Na-S batteries through a comprehensive understanding of the polysulfide-absorbing materials.展开更多
Understanding the patterns and drivers of biomass allocation among organs at a broad scale is crucial for predicting the responses of plant growth and carbon sequestration to environmental change.However,the extent to...Understanding the patterns and drivers of biomass allocation among organs at a broad scale is crucial for predicting the responses of plant growth and carbon sequestration to environmental change.However,the extent to which the general rules govern these patterns and the key factors affecting biomass allocation remain poorly understood.Using a global dataset of 239 tree species,we tested the two prevailing theories(i.e.,the allometric partitioning theory(APT)and the optimal partitioning theory(OPT))by investigating the scaling relationships between plant organs and how environmental factors and phylogeny shape the patterns of biomass allocation.Our results generally support APT at the global scale,with variations in biomass allocation patterns explained by OPT.As plant size increased,a significant shift in biomass allocation from leaves to roots and stems,as well as from roots to stems,was observed.Specific environmental factors(including temperature,precipitation variables,and soil properties)significantly influenced biomass allocation with distinct patterns in the angiosperms and gymnosperms,even when the allometric effects were taken into account.We conclude that tree biomass allocation among organs(i.e.,the ratios of leaf to stem,leaf to root,stem to root,and aboveground to belowground)is governed by allometry but modulated by optimization at the global scale.Our findings highlight the importance of considering both the ontogenetic and environmental effects in predicting the responses of biomass sequestration to phylogenetic and environmental factors.展开更多
Efficient surface passivation is critical for achieving high-performance perovskite solar cells(PSCs),yet the discovery of optimal passivators remains a time-consuming,trial-and-error process.Here,we report a synergis...Efficient surface passivation is critical for achieving high-performance perovskite solar cells(PSCs),yet the discovery of optimal passivators remains a time-consuming,trial-and-error process.Here,we report a synergistic machine learning(ML)and density functional theory(DFT)approach that enables predictive and rapid identification of effective passivation materials.By training an XGBoost model(91.3%accuracy)with DFT-derived molecular descriptors and activity calculations,we identify 2-(4-aminophenyl)-3H-benzimidazol-5-amine(APBIA)as a promising passivator.Experimental validation demonstrates that APBIA effectively removes surface impurities and passivates defects within perovskite films,leading to a significant increase in power conversion efficiency(PCE)from 22.48%to 25.55%(certified as 25.02%).This ML-DFT framework provides a generalizable pathway for accelerating the development of advanced functional materials for photovoltaic applications.展开更多
In two-scale topology optimization,enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability.This ...In two-scale topology optimization,enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability.This paper proposes a two-scale concurrent topology optimization strategy aimed at improving the interface connection strength.This method employs a parametric approach to explicitly divide the micro-design domain into a“boundary connection region”and a“free design domain”at the initial stage of optimization.The boundary connection region is used to generate a connection layer that enhances the interface strength,while the free design domain is not constrained by this layer,thus fully exploiting the design potential of the material layout.During the optimization process,the solid isotropic material with penalization(SIMP)method is first used to optimize the material distribution in the free design domain,and filtering and projection techniques are employed to alleviate numerical instability and obtain a clear topological structure.Subsequently,the effective performance of the microstructure is calculated through homogenization and transferred to the macro-scale for global response analysis.Throughout the iterative process,the geometry of the connection layer remains unchanged,and only the free design domain is optimized,thereby achieving a balance between high performance and good manufacturability.The effectiveness of the proposed method is verified through numerical examples.展开更多
A systematic and effective optimization is proposed for the design of a three-dimensional （3-D） vehicle suspension model with eight degrees of freedom （DOF）, including vertical seat motion, vehicle suspension, pit...A systematic and effective optimization is proposed for the design of a three-dimensional （3-D） vehicle suspension model with eight degrees of freedom （DOF）, including vertical seat motion, vehicle suspension, pitching and rolling motions, and vertical wheel motions using the evolutionary game theory. A new design of the passive suspension is aided by game theory to attain the best compromise between ride quality and suspension deflections. Extensive simulations are performed on three type road surface models A, B, C pavement grades based on the guidelines provided by ISO-2631 with the Matlab/Simulink environment. The preliminary results show that, when the passive suspension is optimized via the proposed approach, a substantial improvement in the vertical ride quality is obtained while keeping the suspension deflections within their allowable clearance when the vehicle moves at a constant velocity v=20 m/s, and the comfort performance of a suspension seat can be enhanced by 20%-30%.展开更多
Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly ...Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly defined and the kill network theory is established by combining super network and kill chain theory.Two cases of the SoSs are considered:(a)The kill chains are relatively homogenous;(b)The kill chains are relatively heterogenous.Meanwhile,two capability assessment methods,which are based on the number of kill chains and improved self-information quantity,respectively,are proposed.The improved self-information quantity modeled based on nodes and edges can achieve qualitative and quantitative assessment of the combat capability by using linguistic Pythagorean fuzzy sets.Then,a resilient evaluation index consisting of risk response,survivability,and quick recovery is proposed accordingly.Finally,network models for regional air defense and anti-missile SoSs are established respectively,and the resilience measurement results are verified and analyzed under different attack and recovery strategies,and the optimization strategies are also proposed.The proposed theory and method can meet different demands to evaluate combat capability and optimize resilience of various types of air&space defense and similar SoSs.展开更多
Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three ...Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission' linkage and inside-to-outside ‘negative transmission' movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores(i.e., ‘single, ring, axis, and pole core') progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security.展开更多
Based on density functional theory(DFT)and basic structure models,the chemical reactions on the surface of vanadium-titanium based selective catalytic reduction(SCR)denitrification catalysts were summarized.Reasonable...Based on density functional theory(DFT)and basic structure models,the chemical reactions on the surface of vanadium-titanium based selective catalytic reduction(SCR)denitrification catalysts were summarized.Reasonable structural models(non-periodic and periodic structural models)are the basis of density functional calculations.A periodic structure model was more appropriate to represent the catalyst surface,and its theoretical calculation results were more comparable with the experimental results than a nonperiodic model.It is generally believed that the SCR mechanism where NH3 and NO react to produce N2 and H2 O follows an Eley-Rideal type mechanism.NH2 NO was found to be an important intermediate in the SCR reaction,with multiple production routes.Simultaneously,the effects of H2 O,SO2 and metal on SCR catalysts were also summarized.展开更多
The elliptical cross-section spiral equal-channel extrusion （ECSEE） process is simulated by using Deform-3D finite element software. The ratio m of major-axis to minor-axis length for ellipse-cross-section, the tors...The elliptical cross-section spiral equal-channel extrusion （ECSEE） process is simulated by using Deform-3D finite element software. The ratio m of major-axis to minor-axis length for ellipse-cross-section, the torsion angle u, the round-ellipse cross-section transitional channel L1, the elliptical rotation cross-section transitional channel L2 and the ellipse-round cross-section transitional channel L3 are destined for the extrusion process parameters. The average effective strain eave on cross-section of blank, the deformation uniformity coefficient a and the value of maximum damage dmax are chosen to be the optimize indexes, and the virtual orthogonal experiment of L16 （45） is designed. The correlation degree of the process factors affecting eave, a and dmax is analyzed by the numerical simulation results using the weights and grey association model. The process parameters are optimized by introducing the grey situation decision theory and the ECSEE optimal combination of process parameters is obtained： u of 120 , m of 1.55, L1 of 7 mm, L2 of 10 mm, and L3 of 10 mm. Simulation and experimental results show that the material can be refined with the optimized structural parameters of die. Therefore, the optimization results are satisfactory.展开更多
A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis ca...A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.展开更多
It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-pr...It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.展开更多
基金Project supported by the Fundamental Research Funds for the Central Universities(No.2042025kf0052)。
文摘In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the critical elementary reaction of molybdenum catalysis.However,the relevant density functional theory(DFT)studies are relatively scarce,especially regarding the rational selection of functionals.In this work,14 functionals were employed to investigate the Mo-catalyzed carbonyl oxidative addition step.A benchmark study was carried out to evaluate their performance in structure optimization and energy calculation.Analyses of mean absolute error(MAE)and mean squared error(MSE)indicated that the B3LYP-D3(BJ),TPSSh,and ωB97X-D functionals exhibited superior performance in structure optimization.Using the DLPNO-CCSD(T)functional as the reference,the M06,M06-L,and MN15-L functionals exhibited good performance for energy calculation based on the structures optimized using the B3LYP-D3(BJ)functional.In particular,MN15-L provided the best performance with the smallest MAE and MSE.
基金supported by National Key Research and Development Program of China under Grant 2024YFE0210800National Natural Science Foundation of China under Grant 62495062Beijing Natural Science Foundation under Grant L242017.
文摘The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.
基金financially supported in-part by the National Natural Science Foundation of China(52275011)the Natural Science Foundation of Guangdong Province(2023B1515020080)+3 种基金the Natural Science Foundation of Guangzhou(2024A04J2552)the Fundamental Research Funds for the Central Universities,the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(CAST)(2021QNRC001)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011253)the Higher Education Institution Featured Innovation Project of Department of Education of Guangdong Province(GrantNo.2023KTSCX138).
文摘Moles exhibit highly effective capabilities due to their unique body structures and digging techniques,making them ideal models for biomimetic research.However,a major challenge for mole-inspired robots lies in overcoming resistance in granular media when burrowing with forelimbs.In the absence of effective forepaw design strategies,most robotic designs rely on increased power to enhance performance.To address this issue,this paper employs Resistive Force Theory to optimize mole-inspired forepaws,aiming to enhance burrowing efficiency.By analyzing the relationship between geometric parameters and burrowing forces,we propose several forepaw design variations.Through granular resistance assessments,an effective forepaw configuration is identified and further refined using parameters such as longitudinal and transverse curvature.Subsequently,the Particle Swarm Optimization algorithm is applied to determine the optimal forepaw design.In force-loading tests,the optimized forepaw demonstrated a 79.44%reduction in granular lift force and a 22.55%increase in propulsive force compared with the control group.In robotic burrowing experiments,the optimized forepaw achieved the longest burrow displacement(179.528 mm)and the lowest burrowing lift force(0.9355 mm/s),verifying its effectiveness in reducing the lift force and enhancing the propulsive force.
文摘In the wave of urbanization,waterfront landscape optimization is very important,but it is faced with ecological deterioration and other problems.By combing the relevant theories and practices at home and abroad and making a comparison and summary,the future direction of waterfront research was analyzed.In theory,foreign research has experienced multi-stage development,covering definition classification,design methods,etc.China started late,and is mainly in the exploration stage of learning from foreign experience and combining with local characteristics.The current research and practice have shortcomings such as ignoring users’needs and lacking quantitative evaluation.In the future,the construction of waterfront should focus on the needs of users,use scientific methods to build an evaluation system,integrate multi-disciplines,excavate regional culture,and establish a monitoring mechanism to achieve sustainable and coordinated development of the ecology,society and economy of waterfront.
基金partially supported by the Center for Advanced Systems Understanding (CASUS), financed by Germany’s Federal Ministry of Education and Research and the Saxon State Government out of the State Budget approved by the Saxon State Parliamentthe European Union’s Just Transition Fund (JTF) within the project Röntgenlaser Optimierung der Laserfusion (ROLF), Contract No. 5086999001, co-financed by the Saxon State Government out of the State Budget approved by the Saxon State Parliament+3 种基金the European Research Council (ERC) under the European Union’s Horizon 2022 Research and Innovation Programme (Grant Agreement No. 101076233, “PREXTREME”)Computations were performed on a Bull Cluster at the Center for Information Services and High-Performance Computing (ZIH) at Technische Universität Dresden and at the Norddeutscher Verbund für Hoch- und Höchstleistungsrechnen (HLRN) under Grant No. mvp00024support by the National Natural Science Foundation of China under Grant No. 12274171support by the Advanced Materials–National Science and Technology Major Project (Grant No. 2024ZD0606900)
文摘Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse of warm dense matter theory is thermal density functional theory(DFT),which,however,suffers from two limitations:(i)its accuracy can depend on the utilized exchange-correlation functional,which has to be approximated,and(ii)it is generally limited to single-electron properties such as the density distribution.Here,we present a new ansatz combining time-dependent DFT results for the dynamic structure factor S_(ee)(q,ω)with static DFT results for the density response.This allows us to estimate the electron-electron static structure factor S_(ee)(q)of warm dense hydrogen with high accuracy over a broad range of densities and temperatures.In addition to its value for the study of warm dense matter,our work opens up new avenues for the future study of electronic correlations exclusively within the framework of DFT for a host of applications.
基金supported by the Indian Institute of Technology Delhi (IIT Delhi)
文摘Though the formation of polysulfide is desirable,as it contributes to the capacity build-up,it must not leak into the electrolyte.The loss of polysulfide causes capacity fade,a change in the local chemistry of the electrolyte,and anode poisoning.Constant efforts are in progress to find suitable polysulfide-absorbing materials;however,the magical polysulfide absorber is yet to be discovered or developed.Experimental methods alone often fall short in accelerating the investigations may be due to the complex Nature of the testing.This review focuses on the importance of computational methods,particularly density functional theory(DFT),in screening suitable polysulfide absorbers.It highlights the critical role of anchoring materials in improving Na-S battery performance,including pristine and doped graphene,metal–organic frameworks,carbon Nanofibers,vanadium disulfide,MXenes,and metal sulfides.By examining adsorption energies,charge transfer mechanisms,and catalytic properties,this review provides insights into the design of advanced materials that can effectively immobilize polysulfides and enhance battery stability.The review aims to guide future research efforts toward the development of high-performance RT Na-S batteries through a comprehensive understanding of the polysulfide-absorbing materials.
基金supported by the China Postdoctoral Science Foundation(2023M733712)the National Natural Science Foundation of China(31971491,32571862 and 32571830)the Strategic Priority Research Program of the Chinese Academy of Sciences(A)。
文摘Understanding the patterns and drivers of biomass allocation among organs at a broad scale is crucial for predicting the responses of plant growth and carbon sequestration to environmental change.However,the extent to which the general rules govern these patterns and the key factors affecting biomass allocation remain poorly understood.Using a global dataset of 239 tree species,we tested the two prevailing theories(i.e.,the allometric partitioning theory(APT)and the optimal partitioning theory(OPT))by investigating the scaling relationships between plant organs and how environmental factors and phylogeny shape the patterns of biomass allocation.Our results generally support APT at the global scale,with variations in biomass allocation patterns explained by OPT.As plant size increased,a significant shift in biomass allocation from leaves to roots and stems,as well as from roots to stems,was observed.Specific environmental factors(including temperature,precipitation variables,and soil properties)significantly influenced biomass allocation with distinct patterns in the angiosperms and gymnosperms,even when the allometric effects were taken into account.We conclude that tree biomass allocation among organs(i.e.,the ratios of leaf to stem,leaf to root,stem to root,and aboveground to belowground)is governed by allometry but modulated by optimization at the global scale.Our findings highlight the importance of considering both the ontogenetic and environmental effects in predicting the responses of biomass sequestration to phylogenetic and environmental factors.
基金supported by the National Key Research and Development Program of China (Grant No. 2024YFB4205101)the National Natural Science Foundation of China (No. 62274098 and No. 62074084)+2 种基金the Natural Science Foundation of Tianjin (No.22JCYBJC01300, No. 23JCYBJC01620 and No. 21JCYBJC00270)the Overseas Expertise Introduction Project for Discipline Innovation of Higher Edu cation of China (Grant No. B16027)the Fundamental Research Funds for the Central Universities,Nankai University (No. 63241568)
文摘Efficient surface passivation is critical for achieving high-performance perovskite solar cells(PSCs),yet the discovery of optimal passivators remains a time-consuming,trial-and-error process.Here,we report a synergistic machine learning(ML)and density functional theory(DFT)approach that enables predictive and rapid identification of effective passivation materials.By training an XGBoost model(91.3%accuracy)with DFT-derived molecular descriptors and activity calculations,we identify 2-(4-aminophenyl)-3H-benzimidazol-5-amine(APBIA)as a promising passivator.Experimental validation demonstrates that APBIA effectively removes surface impurities and passivates defects within perovskite films,leading to a significant increase in power conversion efficiency(PCE)from 22.48%to 25.55%(certified as 25.02%).This ML-DFT framework provides a generalizable pathway for accelerating the development of advanced functional materials for photovoltaic applications.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘In two-scale topology optimization,enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability.This paper proposes a two-scale concurrent topology optimization strategy aimed at improving the interface connection strength.This method employs a parametric approach to explicitly divide the micro-design domain into a“boundary connection region”and a“free design domain”at the initial stage of optimization.The boundary connection region is used to generate a connection layer that enhances the interface strength,while the free design domain is not constrained by this layer,thus fully exploiting the design potential of the material layout.During the optimization process,the solid isotropic material with penalization(SIMP)method is first used to optimize the material distribution in the free design domain,and filtering and projection techniques are employed to alleviate numerical instability and obtain a clear topological structure.Subsequently,the effective performance of the microstructure is calculated through homogenization and transferred to the macro-scale for global response analysis.Throughout the iterative process,the geometry of the connection layer remains unchanged,and only the free design domain is optimized,thereby achieving a balance between high performance and good manufacturability.The effectiveness of the proposed method is verified through numerical examples.
基金Supported by Program for New Century Excellent Talents in University (070003)the Natural Science Foundation of Anhui Province (070414154)~~
文摘A systematic and effective optimization is proposed for the design of a three-dimensional （3-D） vehicle suspension model with eight degrees of freedom （DOF）, including vertical seat motion, vehicle suspension, pitching and rolling motions, and vertical wheel motions using the evolutionary game theory. A new design of the passive suspension is aided by game theory to attain the best compromise between ride quality and suspension deflections. Extensive simulations are performed on three type road surface models A, B, C pavement grades based on the guidelines provided by ISO-2631 with the Matlab/Simulink environment. The preliminary results show that, when the passive suspension is optimized via the proposed approach, a substantial improvement in the vertical ride quality is obtained while keeping the suspension deflections within their allowable clearance when the vehicle moves at a constant velocity v=20 m/s, and the comfort performance of a suspension seat can be enhanced by 20%-30%.
基金supported by National Natural Science Foundation of China(61425008,61333004,61273054)Top-Notch Young Talents Program of China,and Aeronautical Foundation of China(2013585104)
基金supported by National Natural Science Foundation of China,grant numbers 72001214National Social Science Foundation of China,Young Talent Fund of University Association for Science and Technology in Shaanxi,China,No.20190108Natural Science Foundation of Shaanxi Province,grant number 2020JQ-484.
文摘Resilience of air&space defense system of systems(SoSs)is critical to national air defense security.However,the research on it is still scarce.In this study,the resilience of air&space defense SoSs is firstly defined and the kill network theory is established by combining super network and kill chain theory.Two cases of the SoSs are considered:(a)The kill chains are relatively homogenous;(b)The kill chains are relatively heterogenous.Meanwhile,two capability assessment methods,which are based on the number of kill chains and improved self-information quantity,respectively,are proposed.The improved self-information quantity modeled based on nodes and edges can achieve qualitative and quantitative assessment of the combat capability by using linguistic Pythagorean fuzzy sets.Then,a resilient evaluation index consisting of risk response,survivability,and quick recovery is proposed accordingly.Finally,network models for regional air defense and anti-missile SoSs are established respectively,and the resilience measurement results are verified and analyzed under different attack and recovery strategies,and the optimization strategies are also proposed.The proposed theory and method can meet different demands to evaluate combat capability and optimize resilience of various types of air&space defense and similar SoSs.
基金Under the auspices of Major Program of the National Natural Science Foundation of China ‘Coupled mechanisms and interactive coercing effects between urbanization and eco-environment in mega-urban agglomerations’(No.41590842)
文摘Urban agglomerations are spatial entities that promote the development of ‘new urbanization' processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces' encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission' linkage and inside-to-outside ‘negative transmission' movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores(i.e., ‘single, ring, axis, and pole core') progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security.
基金supported by the National Key Research&Development(R&D)Program of China(No.2017YFC0210500)the National Natural Science Foundation of China(No.51938014)
文摘Based on density functional theory(DFT)and basic structure models,the chemical reactions on the surface of vanadium-titanium based selective catalytic reduction(SCR)denitrification catalysts were summarized.Reasonable structural models(non-periodic and periodic structural models)are the basis of density functional calculations.A periodic structure model was more appropriate to represent the catalyst surface,and its theoretical calculation results were more comparable with the experimental results than a nonperiodic model.It is generally believed that the SCR mechanism where NH3 and NO react to produce N2 and H2 O follows an Eley-Rideal type mechanism.NH2 NO was found to be an important intermediate in the SCR reaction,with multiple production routes.Simultaneously,the effects of H2 O,SO2 and metal on SCR catalysts were also summarized.
基金co-supported by National Natural Science Foundation of China (No. 51275414)Aeronautical Science Foundation of China (No. 2011ZE53059)+1 种基金National Defense Basic Research Program (No. 51318040105)Graduate Starting Seed Fund of Northwestern Polytechnical University(No. Z2011006)
文摘The elliptical cross-section spiral equal-channel extrusion （ECSEE） process is simulated by using Deform-3D finite element software. The ratio m of major-axis to minor-axis length for ellipse-cross-section, the torsion angle u, the round-ellipse cross-section transitional channel L1, the elliptical rotation cross-section transitional channel L2 and the ellipse-round cross-section transitional channel L3 are destined for the extrusion process parameters. The average effective strain eave on cross-section of blank, the deformation uniformity coefficient a and the value of maximum damage dmax are chosen to be the optimize indexes, and the virtual orthogonal experiment of L16 （45） is designed. The correlation degree of the process factors affecting eave, a and dmax is analyzed by the numerical simulation results using the weights and grey association model. The process parameters are optimized by introducing the grey situation decision theory and the ECSEE optimal combination of process parameters is obtained： u of 120 , m of 1.55, L1 of 7 mm, L2 of 10 mm, and L3 of 10 mm. Simulation and experimental results show that the material can be refined with the optimized structural parameters of die. Therefore, the optimization results are satisfactory.
基金This work was supported by the National Natural Science Foundation of China(Grant No.42050104)the Science Foundation of SINOPEC Group(Grant No.P20030).
文摘A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.
基金supported by the Natural Science Foundation of China(Grant No.51705268)Shandong Provincial Natural Science Foundation,China(Grant No.ZR2016EEB20)China Postdoctoral Science Foundation Funded Project(Grant No.2017M612191)。
文摘It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.
