The demand for flexible electric heating devices has increased due to technology advancement and improved living standards.These devices have various applications including personal thermal management,hyperthermia,def...The demand for flexible electric heating devices has increased due to technology advancement and improved living standards.These devices have various applications including personal thermal management,hyperthermia,defrosting,agricultural heating film,and oil-water separation.Joule heat,generated by electric currents,is commonly used in electrical appliances.To incorporate Joule heating into flexible electronics,new materials with excellent mechanical properties are necessary.Traditional polymers,used as reinforcements,limit the continuity of conductive networks in composites.Therefore,there is a need to develop flexible Joule thermal composite materials with enhanced mechanical strength and conductivity.Cellulose,a widely available renewable resource,is attracting attention for its excellent mechanical properties.It can be used as a dispersant and reinforcing agent for conductive fillers in cellulose-based composites,creating highly conductive networks.Various forms of cellulose,such as wood,nanocellulose,pulp fiber,bacterial cellulose,cellulose paper,textile clothing,and aramid fiber,have been utilized to achieve high-performance Joule thermal composites.Researchers have achieved excellent mechanical properties and developed efficient electric heating devices by designing cellulose-based composites with different structures.The scalable production methods enable large-scale application of cellulose-based devices,each with unique advantages in 1D,2D,and 3D structures.This review summarizes recent advancements in cellulose-based Joule thermal composites,providing insights into different structural devices,and discussing prospects and challenges in the field.展开更多
Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometrie...Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometries.This paper proposes a programmable design methodology for 3D rotary braiding machines using circle-cutting and combination strategies.By introducing varying numbers of incisions on the circle,a diverse range of horn gears can be designed.Different combinations of these cut-circles allow the horn gears to be assembled into various 3D rotary braiders.The parametric equation for the braider plate is derived,showing that a combination strategy involving two cut-circles is feasible for braider design,whereas integrating three cut-circles simultaneously is impossible for a single machine.The construction of an automatic 6-3 type 3D braiding machine demonstrates the effectiveness of the proposed design strategy.This flexible braider design approach provides a practical solution for producing 3D braided composites with complex geometries.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
Covalent organic frameworks(COFs)are two-(2D)or threedimensional(3D)crystalline,porous networks generated by reversible polymerization of organic building blocks[1,2].The structures and functionalities of COFs are pre...Covalent organic frameworks(COFs)are two-(2D)or threedimensional(3D)crystalline,porous networks generated by reversible polymerization of organic building blocks[1,2].The structures and functionalities of COFs are precisely controlled via appropriately selected organic building blocks.This design imparts unique properties to COFs,including exceptional structural stability,tunable pore structure,and surface chemical activity,making them promising for gas separation,catalysis,optoelectronics,and sensing applications.Since Yaghi et al.'s seminal report on COFs in 2005[2],these frameworks have swiftly emerged as a hotspot in the field of materials.Originally,the focus was on fabricating rigid frameworks with static structures and optoelectronic properties.However,the inherently static nature of these frameworks hinders their responsiveness to external stimuli,potentially constraining their functionality in specific applications.Hence,an increasing number of researchers are now directing their attention toward the development of dynamic COFs capable of modifying their structures in response to external stimuli[3].Specifically,dynamic 2D COFs exhibiting enhanced structural responsiveness are of particular interest due to their capability to integrate switchable geometries and porosities with semiconductor building blocks,as well as electron conjugation across COF layers and π-stacked columns,which may enable stimuli-responsive electronic and spin properties[4].展开更多
In this manuscript,we consider a non-autonomous dynamical system.Using the Carathéodory structure,we define a BS dimension on an arbitrary subset and obtain a Bowen’s equation that illustrates the relation of th...In this manuscript,we consider a non-autonomous dynamical system.Using the Carathéodory structure,we define a BS dimension on an arbitrary subset and obtain a Bowen’s equation that illustrates the relation of the BS dimension to the Pesin-Pitskel topological pressure given by Nazarian[24].Moreover,we establish a variational principle and an inverse variational principle for the BS dimension of non-autonomous dynamical systems.Finally,we also get an analogue of Billingsley’s theorem for the BS dimension of non-autonomous dynamical systems.展开更多
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent...Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent,and metastatic malignancies.Mechanistically,ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death(ICD),eliciting damage-associated molecular patterns(DAMPs)release to activate partial antitumor immunity.However,standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations:low tumor immunogenicity,immunosuppressive microenvironment constraints,and tumor microenvironment(TME)-associated physiological barriers(e.g.,hypoxia,dense extracellular matrix).To address these challenges,synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance,encompassing(1)direct amplification of antitumor immunity,(2)disruption of immunosuppressive tumor niches,and(3)biophysical hallmark remodeling in TME.Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy.Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy,this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis-immunotherapy strategies.It advances multidimensional nanoplatform design principles for material selection,structural configuration,physicochemical modulation,multifunctional integration,and artificial intelligence-enabled design,providing a scientific basis for efficacy optimization.Moreover,it examines translational challenges of ferroptosis-immunotherapy nanoplatforms across preclinical and clinical stages,proposing actionable solutions while envisioning future onco-immunotherapy directions.Collectively,it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies,offering a roadmap for accelerating clinical translation in onco-immunotherapy research.展开更多
In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey...In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.展开更多
To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of ...To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.展开更多
Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI ...Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety...Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.展开更多
Based on the characteristics of landscape design,it is considered that three-dimensional rendering and landscape animation are important forms for the display of landscape effect,and has pointed out that there exist s...Based on the characteristics of landscape design,it is considered that three-dimensional rendering and landscape animation are important forms for the display of landscape effect,and has pointed out that there exist some deficiencies in the application of relevant software in China.By using VRML and 3DS MAX,a three-dimensional landscape design system has been developed.Then,its functions have been described which are CAD outline drawing,construction cost estimation,virtual reality,subsequent landscape observation,resources expansion and web files generation.Finally,it has discussed the modeling of virtual landscape data base and VRML interaction.展开更多
An optimal dimension-down iterative algorithm （DDIA） is proposed for solving a mixed （continuous/ discrete） transportation network design problem （MNDP）, which is generally expressed as a mathematical programmin...An optimal dimension-down iterative algorithm （DDIA） is proposed for solving a mixed （continuous/ discrete） transportation network design problem （MNDP）, which is generally expressed as a mathematical programming with equilibrium constraints （MPEC）. The upper level of the MNDP aims to optimize the network performance via both the expansion of existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium （UE） model. The idea of the proposed DDIA is to reduce the dimensions of the problem. A group of variables （discrete/continuous） are fixed to altemately optimize another group of variables （continuous/discrete）. Some continuous network design problems （CNDPs） and discrete network design problems （DNDPs） are solved repeatedly until the optimal solution is obtained. A numerical example is given to demonstrate the efficiency of the proposed algorithm.展开更多
Developing highly efficient microwave absorbing materials(MAMs)to ameliorate the electromagnetic(EM)response and facilitate energy absorption is crucial in both the civil and military industries.Metal-organic framewor...Developing highly efficient microwave absorbing materials(MAMs)to ameliorate the electromagnetic(EM)response and facilitate energy absorption is crucial in both the civil and military industries.Metal-organic framework(MOF)derived nanoporous carbon composites have emerged as advanced MAMs ow-ing to their rich porosity,tunable compositions,facile functionalization,and morphology diversity.To-gether with the flourishing development of composition-tuning strategy,the rational dimension design and elaborate control over the architectures have also evolved into an effective approach to regulating their EM properties.Herein,we provide a comprehensive review of the recent advances in using di-mension and morphology modulation to adjust the microwave attenuation capacities for MOF-derived carbon composites.The underlying design rules and unique advantages for the MAMs of various dimen-sions were discussed with the selection of representative work,providing general concepts and insight on how to efficiently tune the morphologies.Accordingly,the fundamental dimension-morphology-function relationship was also elucidated.Finally,the challenges and perspectives of dimension design and mor-phology control over MOF-derived MAMs were also presented.展开更多
In aerodynamic optimization, global optimization methods such as genetic algorithms are preferred in many cases because of their advantage on reaching global optimum. However,for complex problems in which large number...In aerodynamic optimization, global optimization methods such as genetic algorithms are preferred in many cases because of their advantage on reaching global optimum. However,for complex problems in which large number of design variables are needed, the computational cost becomes prohibitive, and thus original global optimization strategies are required. To address this need, data dimensionality reduction method is combined with global optimization methods, thus forming a new global optimization system, aiming to improve the efficiency of conventional global optimization. The new optimization system involves applying Proper Orthogonal Decomposition（POD） in dimensionality reduction of design space while maintaining the generality of original design space. Besides, an acceleration approach for samples calculation in surrogate modeling is applied to reduce the computational time while providing sufficient accuracy. The optimizations of a transonic airfoil RAE2822 and the transonic wing ONERA M6 are performed to demonstrate the effectiveness of the proposed new optimization system. In both cases, we manage to reduce the number of design variables from 20 to 10 and from 42 to 20 respectively. The new design optimization system converges faster and it takes 1/3 of the total time of traditional optimization to converge to a better design, thus significantly reducing the overall optimization time and improving the efficiency of conventional global design optimization method.展开更多
基金supported by the fund of the National Natural Science Foundation of China(Nos.22378249,22078184,and 22171170)the China Postdoctoral Science Foundation(No.2019M653853XB)the Natural Science Advance Research Foundation of Shaanxi University of Science and Technology(No.2018QNBJ-03).
文摘The demand for flexible electric heating devices has increased due to technology advancement and improved living standards.These devices have various applications including personal thermal management,hyperthermia,defrosting,agricultural heating film,and oil-water separation.Joule heat,generated by electric currents,is commonly used in electrical appliances.To incorporate Joule heating into flexible electronics,new materials with excellent mechanical properties are necessary.Traditional polymers,used as reinforcements,limit the continuity of conductive networks in composites.Therefore,there is a need to develop flexible Joule thermal composite materials with enhanced mechanical strength and conductivity.Cellulose,a widely available renewable resource,is attracting attention for its excellent mechanical properties.It can be used as a dispersant and reinforcing agent for conductive fillers in cellulose-based composites,creating highly conductive networks.Various forms of cellulose,such as wood,nanocellulose,pulp fiber,bacterial cellulose,cellulose paper,textile clothing,and aramid fiber,have been utilized to achieve high-performance Joule thermal composites.Researchers have achieved excellent mechanical properties and developed efficient electric heating devices by designing cellulose-based composites with different structures.The scalable production methods enable large-scale application of cellulose-based devices,each with unique advantages in 1D,2D,and 3D structures.This review summarizes recent advancements in cellulose-based Joule thermal composites,providing insights into different structural devices,and discussing prospects and challenges in the field.
基金funded by the Shanghai Natural Science Foundation of Shanghai Municipal Science and Technology Commission(20ZR1400600)the Fundamental Research Funds for the Central Universities(2232023G-06)through collaborative research with the Advanced Fibrous Materials Lab(AFML)at the University of British Columbia.
文摘Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometries.This paper proposes a programmable design methodology for 3D rotary braiding machines using circle-cutting and combination strategies.By introducing varying numbers of incisions on the circle,a diverse range of horn gears can be designed.Different combinations of these cut-circles allow the horn gears to be assembled into various 3D rotary braiders.The parametric equation for the braider plate is derived,showing that a combination strategy involving two cut-circles is feasible for braider design,whereas integrating three cut-circles simultaneously is impossible for a single machine.The construction of an automatic 6-3 type 3D braiding machine demonstrates the effectiveness of the proposed design strategy.This flexible braider design approach provides a practical solution for producing 3D braided composites with complex geometries.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
基金supported by the National Natural Science Foundation of China(Nos.51902121 and 22372067)。
文摘Covalent organic frameworks(COFs)are two-(2D)or threedimensional(3D)crystalline,porous networks generated by reversible polymerization of organic building blocks[1,2].The structures and functionalities of COFs are precisely controlled via appropriately selected organic building blocks.This design imparts unique properties to COFs,including exceptional structural stability,tunable pore structure,and surface chemical activity,making them promising for gas separation,catalysis,optoelectronics,and sensing applications.Since Yaghi et al.'s seminal report on COFs in 2005[2],these frameworks have swiftly emerged as a hotspot in the field of materials.Originally,the focus was on fabricating rigid frameworks with static structures and optoelectronic properties.However,the inherently static nature of these frameworks hinders their responsiveness to external stimuli,potentially constraining their functionality in specific applications.Hence,an increasing number of researchers are now directing their attention toward the development of dynamic COFs capable of modifying their structures in response to external stimuli[3].Specifically,dynamic 2D COFs exhibiting enhanced structural responsiveness are of particular interest due to their capability to integrate switchable geometries and porosities with semiconductor building blocks,as well as electron conjugation across COF layers and π-stacked columns,which may enable stimuli-responsive electronic and spin properties[4].
基金supported by the NSFC(12461012)and the NSF of Chongqing(CSTB2024NSCQ-MSX1246).
文摘In this manuscript,we consider a non-autonomous dynamical system.Using the Carathéodory structure,we define a BS dimension on an arbitrary subset and obtain a Bowen’s equation that illustrates the relation of the BS dimension to the Pesin-Pitskel topological pressure given by Nazarian[24].Moreover,we establish a variational principle and an inverse variational principle for the BS dimension of non-autonomous dynamical systems.Finally,we also get an analogue of Billingsley’s theorem for the BS dimension of non-autonomous dynamical systems.
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
文摘Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
基金supported by the National Natural Science Foundation of China(Nos.82302373,81903846)Natural Science Foundation of Sichuan Province(No.2022NSFSC1925)+1 种基金Chengdu Technology Innovation Research and Development Project(No.2022-YF05-01546-SN)the Introduction of Talents Research Project of Chengdu University(No.2081921049)。
文摘Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent,and metastatic malignancies.Mechanistically,ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death(ICD),eliciting damage-associated molecular patterns(DAMPs)release to activate partial antitumor immunity.However,standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations:low tumor immunogenicity,immunosuppressive microenvironment constraints,and tumor microenvironment(TME)-associated physiological barriers(e.g.,hypoxia,dense extracellular matrix).To address these challenges,synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance,encompassing(1)direct amplification of antitumor immunity,(2)disruption of immunosuppressive tumor niches,and(3)biophysical hallmark remodeling in TME.Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy.Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy,this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis-immunotherapy strategies.It advances multidimensional nanoplatform design principles for material selection,structural configuration,physicochemical modulation,multifunctional integration,and artificial intelligence-enabled design,providing a scientific basis for efficacy optimization.Moreover,it examines translational challenges of ferroptosis-immunotherapy nanoplatforms across preclinical and clinical stages,proposing actionable solutions while envisioning future onco-immunotherapy directions.Collectively,it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies,offering a roadmap for accelerating clinical translation in onco-immunotherapy research.
基金the financial supports from National Key R&D Program for Young Scientists of China(Grant No.2022YFC3080900)National Natural Science Foundation of China(Grant No.52374181)+1 种基金BIT Research and Innovation Promoting Project(Grant No.2024YCXZ017)supported by Science and Technology Innovation Program of Beijing institute of technology under Grant No.2022CX01025。
文摘In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.
基金supported by the Jilin Science and Technology Development Plan (20240101029JJ) for the following study:synchronized high-speed detection of surface shape and defects in the grinding stage of complex surfaces (KLMSZZ202305)for the high-precision wide dynamic large aperture optical inspection system for fine astronomical observation by the National Major Research Instrument Development Project (62127901)+2 种基金for ultrasmooth manufacturing technology of large diameter complex curved surface by the National Key R&D Program(2022YFB3403405)for research on the key technology of rapid synchronous detection of surface shape and subsurface defects in the grinding stage of large diameter complex surfaces by the International Cooperation Project(2025010157)The Key Laboratory of Optical System Advanced Manufacturing Technology,Chinese Academy of Sciences (2022KLOMT02-04) also supported this study
文摘To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.
基金supported by the Hong Kong Polytechnic University(1-WZ1Y,1-W34U,4-YWER).
文摘Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
文摘Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.
基金Supported by the Plan of " One College Student in One Village" of the Department of Education (2777)~~
文摘Based on the characteristics of landscape design,it is considered that three-dimensional rendering and landscape animation are important forms for the display of landscape effect,and has pointed out that there exist some deficiencies in the application of relevant software in China.By using VRML and 3DS MAX,a three-dimensional landscape design system has been developed.Then,its functions have been described which are CAD outline drawing,construction cost estimation,virtual reality,subsequent landscape observation,resources expansion and web files generation.Finally,it has discussed the modeling of virtual landscape data base and VRML interaction.
基金The National Natural Science Foundation of China(No. 50908235 )China Postdoctoral Science Foundation (No.201003520)
文摘An optimal dimension-down iterative algorithm （DDIA） is proposed for solving a mixed （continuous/ discrete） transportation network design problem （MNDP）, which is generally expressed as a mathematical programming with equilibrium constraints （MPEC）. The upper level of the MNDP aims to optimize the network performance via both the expansion of existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium （UE） model. The idea of the proposed DDIA is to reduce the dimensions of the problem. A group of variables （discrete/continuous） are fixed to altemately optimize another group of variables （continuous/discrete）. Some continuous network design problems （CNDPs） and discrete network design problems （DNDPs） are solved repeatedly until the optimal solution is obtained. A numerical example is given to demonstrate the efficiency of the proposed algorithm.
基金supported by t he Shanghai Science&Tech-nology Committee(No.22ZR1403300)the Fundamental Research Funds for the Central Universities(No.2232020A-02)the Na-tional Natural Science Foundation of China(Nos.51871053 and 91963204).
文摘Developing highly efficient microwave absorbing materials(MAMs)to ameliorate the electromagnetic(EM)response and facilitate energy absorption is crucial in both the civil and military industries.Metal-organic framework(MOF)derived nanoporous carbon composites have emerged as advanced MAMs ow-ing to their rich porosity,tunable compositions,facile functionalization,and morphology diversity.To-gether with the flourishing development of composition-tuning strategy,the rational dimension design and elaborate control over the architectures have also evolved into an effective approach to regulating their EM properties.Herein,we provide a comprehensive review of the recent advances in using di-mension and morphology modulation to adjust the microwave attenuation capacities for MOF-derived carbon composites.The underlying design rules and unique advantages for the MAMs of various dimen-sions were discussed with the selection of representative work,providing general concepts and insight on how to efficiently tune the morphologies.Accordingly,the fundamental dimension-morphology-function relationship was also elucidated.Finally,the challenges and perspectives of dimension design and mor-phology control over MOF-derived MAMs were also presented.
基金supported by the National Natural Science Foundation of China (No. 11502211)
文摘In aerodynamic optimization, global optimization methods such as genetic algorithms are preferred in many cases because of their advantage on reaching global optimum. However,for complex problems in which large number of design variables are needed, the computational cost becomes prohibitive, and thus original global optimization strategies are required. To address this need, data dimensionality reduction method is combined with global optimization methods, thus forming a new global optimization system, aiming to improve the efficiency of conventional global optimization. The new optimization system involves applying Proper Orthogonal Decomposition（POD） in dimensionality reduction of design space while maintaining the generality of original design space. Besides, an acceleration approach for samples calculation in surrogate modeling is applied to reduce the computational time while providing sufficient accuracy. The optimizations of a transonic airfoil RAE2822 and the transonic wing ONERA M6 are performed to demonstrate the effectiveness of the proposed new optimization system. In both cases, we manage to reduce the number of design variables from 20 to 10 and from 42 to 20 respectively. The new design optimization system converges faster and it takes 1/3 of the total time of traditional optimization to converge to a better design, thus significantly reducing the overall optimization time and improving the efficiency of conventional global design optimization method.
