According to the morphological structure characteristics of plants, the de- velopment mode for component-based virtual plants software was put forward, and the internal structure of plant organs component under this m...According to the morphological structure characteristics of plants, the de- velopment mode for component-based virtual plants software was put forward, and the internal structure of plant organs component under this mode were analyzed, thereby, the overall design mode for virtual plants software was given out, and its characteristics were estimated. Compared with traditional development modes of virtual plants software, component-based virtual plants software had significant advantages in code reusing, development efficiency and expansion of software functions.展开更多
A new method that designs and implements the component-based distributed & hierarchical flexible manufacturing control software is described with a component concept in this paper. The proposed method takes aim at...A new method that designs and implements the component-based distributed & hierarchical flexible manufacturing control software is described with a component concept in this paper. The proposed method takes aim at improving the flexibility and reliability of the control system. On the basis of describing the concepts of component-based software and the distributed object technology, the architecture of the component-based software of the control system is suggested with the Common Object Request Broker Architecture (CORBA). And then, we propose a design method for component-based distributed & hierarchical flexible manufacturing control system. Finally, to verify the software design method, a prototype flexible manufacturing control system software has been implemented in Orbix 2.3c, VC + + 6. 0 and has been tested in connection with the physical flexible manufacturing shop at the WuXi Professional Institute.展开更多
In a component-based software development life cycle, selection of preexisting components is an important task. Every component that has to be reused has an associated risk of failure of not meeting the functional and...In a component-based software development life cycle, selection of preexisting components is an important task. Every component that has to be reused has an associated risk of failure of not meeting the functional and non-functional requirements. A component's failure would lead a developer to look for some other alternative of combinations of COTS, in-house and engineered components among possible candidate combinations. This means design itself can readily change. The very process of design of a software system and component selection seems to be heavily dependent on testing results. Instability of design, further, becomes more severe due to requirements change requests. Therefore, this instability of design has to be essentially mitigated by using proper design and testing approaches, otherwise, it may lead to exorbitantly high testing cost due to the repeated testing of various alternatives. How these three activities: Component-based software design, component selection and component-based software testing are interrelated? What process model is most suited to address this concern? This work explores the above questions and their implication in terms of nature of a process model that can be convincing in case of component-based software development.展开更多
Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a cruc...Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.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
As unmanned underwater vehicles (UUVs) are increasingly designed to perform long-duration missions in highly complex and often extreme environments, traditional design methods face significant and growing challenges^(...As unmanned underwater vehicles (UUVs) are increasingly designed to perform long-duration missions in highly complex and often extreme environments, traditional design methods face significant and growing challenges^([1,2]).展开更多
Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution...Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.展开更多
In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep le...In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep learning has focused on single-layer grating couplers,and the accuracy of multi-layer grating couplers has not yet reached a high level.This paper proposes and demonstrates a novel deep learning network-assisted strategy for inverse design.The network model is based on a multi-layer perceptron(MLP)and incorporates convolutional neural networks(CNNs)and transformers.Through the stacking of multiple layers,it achieves a high-precision design for both multi-layer and single-layer raster couplers with various functionalities.The deep learning network exhibits exceptionally high predictive accuracy,with an average absolute error across the full wavelength range of 1300–1700 nm being only 0.17%,and an even lower predictive absolute error below 0.09%at the specific wavelength of 1550 nm.By combining the deep learning network with the genetic algorithm,we can efficiently design grating couplers that perform different functions.Simulation results indicate that the designed single-wavelength grating couplers achieve coupling efficiencies exceeding 80%at central wavelengths of 1550 nm and 1310 nm.The performance of designed dual-wavelength and broadband grating couplers also reaches high industry standards.Furthermore,the network structure and inverse design method are highly scalable and can be applied not only to multi-layer grating couplers but also directly to the prediction and design of single-layer grating couplers,providing a new perspective for the innovative development of photonic devices.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
This paper introduces CBFEM （component-based finite element model） which is a new method to analyze and design connections of steel structures. Design focused CM （component model） is compared to FEM （finite eleme...This paper introduces CBFEM （component-based finite element model） which is a new method to analyze and design connections of steel structures. Design focused CM （component model） is compared to FEM （finite elements models）. Procedure for composition of a model based on usual production process is used in CBFEM. Its results are compared to those obtained by component method for portal frame eaves moment connection with good agreement. Design of moment resistant column base is demonstrated by a case loaded by two directional bending moments and normal force. Interaction of several connections in one complex joint is explained in the last example. This paper aims to provide structural engineers with a new tool to effectively analyze and design various joints of steel structures.展开更多
In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites t...In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick^(6)LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm^(3).Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as ^(241)Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.展开更多
Lithium-sulfur batteries(LSBs)represent a next-generation energy storage technology,but widespread applications are restricted by the shuttle of lithium polysulfides(LiPSs).The rational design of separators has been d...Lithium-sulfur batteries(LSBs)represent a next-generation energy storage technology,but widespread applications are restricted by the shuttle of lithium polysulfides(LiPSs).The rational design of separators has been demonstrated to be one of the most efficient and cost-effective strategies to curb the shuttle effect,and tremendous research progress has been achieved.The efficiency of a separator depends on its interaction with LiPSs,which is governed by the surface energy and binding strength.Despite several review works that have been reported to advance the separators,most of them primarily focus on active material innovation and construction.The most crucial issues of surface binding energy have not been systematically reviewed,limiting the precise design of efficient separators.In this review,fundamentals related to surface energy and binding interactions with LiPSs are comprehensively analyzed and discussed.With surface binding and energy main lines,the advancements in separator engineering strategies are elaborately summarized and discussed.Moreover,techniques for evaluating affinity to LiPSs are thoroughly analyzed to avoid any ambiguities in measurement.Based on the research context,valuable research directions are suggested to construct efficient separators.This work provides guidelines to regulate the surface binding and energy of separators for high-performance LSBs.展开更多
Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a disti...Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.展开更多
From an engineering feasibility standpoint, what level of performance metrics can be ultimately achieved when designing a reactor using well-established nuclear fuels and structural materials that have already undergo...From an engineering feasibility standpoint, what level of performance metrics can be ultimately achieved when designing a reactor using well-established nuclear fuels and structural materials that have already undergone irradiation testing? The irradiation capability, which hinges on parameters like neutron flux level, irradiation channels' volume, and fuel cycle duration, is a core indicator for high-flux reactors. We propose a conceptual design of an ultra-high flux fast reactor(UFFR) with strong irradiation capability, which utilizes U-20Pu-10Zr alloy fuel and employs lead-bismuth as the coolant. The maximum neutron flux in the core reaches 1.32×10^(16) cm^(-2)s^(-1), while the average neutron flux in the irradiation channels attains 1.19×10^(16) cm^(-2)s^(-1). The volume of the central irradiation channel exceeds 10000 cm^(3), and the fuel cycle duration is 165 d, placing all its performance indicators among the top in the world. Based on the analyses of reactor physics and thermalhydraulics, it has been demonstrated that all reactivity coefficients are negative and all physical parameters meet the design criteria, ensuring the inherent safety of UFFR. An assessment of the irradiation capability has been carried out based on californium-252(^(252)Cf) production, indicating that the irradiation capability of UFFR surpasses that of the high flux isotope reactor(HFIR). The yield of ^(252)Cf from UFFR is 14.39 times that of HFIR, and its nuclei conversion rate is 3.21 times that of HFIR.展开更多
Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,...Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.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
Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls fo...Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.展开更多
基金Supported by the National Natural Science Foundation of China(61062007)the Principal Fund Project of Tarim University,China(TDZKSS201115)~~
文摘According to the morphological structure characteristics of plants, the de- velopment mode for component-based virtual plants software was put forward, and the internal structure of plant organs component under this mode were analyzed, thereby, the overall design mode for virtual plants software was given out, and its characteristics were estimated. Compared with traditional development modes of virtual plants software, component-based virtual plants software had significant advantages in code reusing, development efficiency and expansion of software functions.
基金Supported by National High Technology Development plan(Item No.:2001AA412250)and Shanghai Science & Technology Development Project(Item No.:02FK04)
文摘A new method that designs and implements the component-based distributed & hierarchical flexible manufacturing control software is described with a component concept in this paper. The proposed method takes aim at improving the flexibility and reliability of the control system. On the basis of describing the concepts of component-based software and the distributed object technology, the architecture of the component-based software of the control system is suggested with the Common Object Request Broker Architecture (CORBA). And then, we propose a design method for component-based distributed & hierarchical flexible manufacturing control system. Finally, to verify the software design method, a prototype flexible manufacturing control system software has been implemented in Orbix 2.3c, VC + + 6. 0 and has been tested in connection with the physical flexible manufacturing shop at the WuXi Professional Institute.
文摘In a component-based software development life cycle, selection of preexisting components is an important task. Every component that has to be reused has an associated risk of failure of not meeting the functional and non-functional requirements. A component's failure would lead a developer to look for some other alternative of combinations of COTS, in-house and engineered components among possible candidate combinations. This means design itself can readily change. The very process of design of a software system and component selection seems to be heavily dependent on testing results. Instability of design, further, becomes more severe due to requirements change requests. Therefore, this instability of design has to be essentially mitigated by using proper design and testing approaches, otherwise, it may lead to exorbitantly high testing cost due to the repeated testing of various alternatives. How these three activities: Component-based software design, component selection and component-based software testing are interrelated? What process model is most suited to address this concern? This work explores the above questions and their implication in terms of nature of a process model that can be convincing in case of component-based software development.
文摘Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.
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 (Grant No.52405033)。
文摘As unmanned underwater vehicles (UUVs) are increasingly designed to perform long-duration missions in highly complex and often extreme environments, traditional design methods face significant and growing challenges^([1,2]).
文摘Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.
基金sponsored by the National Key Scientific Instrument and Equipment Development Projects of China(Grant No.62027823)the National Natural Science Foun-dation of China(Grant No.61775048).
文摘In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep learning has focused on single-layer grating couplers,and the accuracy of multi-layer grating couplers has not yet reached a high level.This paper proposes and demonstrates a novel deep learning network-assisted strategy for inverse design.The network model is based on a multi-layer perceptron(MLP)and incorporates convolutional neural networks(CNNs)and transformers.Through the stacking of multiple layers,it achieves a high-precision design for both multi-layer and single-layer raster couplers with various functionalities.The deep learning network exhibits exceptionally high predictive accuracy,with an average absolute error across the full wavelength range of 1300–1700 nm being only 0.17%,and an even lower predictive absolute error below 0.09%at the specific wavelength of 1550 nm.By combining the deep learning network with the genetic algorithm,we can efficiently design grating couplers that perform different functions.Simulation results indicate that the designed single-wavelength grating couplers achieve coupling efficiencies exceeding 80%at central wavelengths of 1550 nm and 1310 nm.The performance of designed dual-wavelength and broadband grating couplers also reaches high industry standards.Furthermore,the network structure and inverse design method are highly scalable and can be applied not only to multi-layer grating couplers but also directly to the prediction and design of single-layer grating couplers,providing a new perspective for the innovative development of photonic devices.
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.
文摘This paper introduces CBFEM （component-based finite element model） which is a new method to analyze and design connections of steel structures. Design focused CM （component model） is compared to FEM （finite elements models）. Procedure for composition of a model based on usual production process is used in CBFEM. Its results are compared to those obtained by component method for portal frame eaves moment connection with good agreement. Design of moment resistant column base is demonstrated by a case loaded by two directional bending moments and normal force. Interaction of several connections in one complex joint is explained in the last example. This paper aims to provide structural engineers with a new tool to effectively analyze and design various joints of steel structures.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.42225405 and U2106202)。
文摘In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick^(6)LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm^(3).Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as ^(241)Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.
基金supported by the National Natural Science Foundation of China (52172228)the Natural Science Foundation of Fujian Province (2024J01475 and 2023J05127)
文摘Lithium-sulfur batteries(LSBs)represent a next-generation energy storage technology,but widespread applications are restricted by the shuttle of lithium polysulfides(LiPSs).The rational design of separators has been demonstrated to be one of the most efficient and cost-effective strategies to curb the shuttle effect,and tremendous research progress has been achieved.The efficiency of a separator depends on its interaction with LiPSs,which is governed by the surface energy and binding strength.Despite several review works that have been reported to advance the separators,most of them primarily focus on active material innovation and construction.The most crucial issues of surface binding energy have not been systematically reviewed,limiting the precise design of efficient separators.In this review,fundamentals related to surface energy and binding interactions with LiPSs are comprehensively analyzed and discussed.With surface binding and energy main lines,the advancements in separator engineering strategies are elaborately summarized and discussed.Moreover,techniques for evaluating affinity to LiPSs are thoroughly analyzed to avoid any ambiguities in measurement.Based on the research context,valuable research directions are suggested to construct efficient separators.This work provides guidelines to regulate the surface binding and energy of separators for high-performance LSBs.
基金supported by Project of National and Local Joint Engineering Research Center for Biomass Energy Development and Utilization(Harbin Institute of Technology,No.2021A004).
文摘Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.
基金supported by the National Natural Science Foundation of China (Grant No.12575180)the Lingchuang Research Project of China National Nuclear Corporation (CNNC)。
文摘From an engineering feasibility standpoint, what level of performance metrics can be ultimately achieved when designing a reactor using well-established nuclear fuels and structural materials that have already undergone irradiation testing? The irradiation capability, which hinges on parameters like neutron flux level, irradiation channels' volume, and fuel cycle duration, is a core indicator for high-flux reactors. We propose a conceptual design of an ultra-high flux fast reactor(UFFR) with strong irradiation capability, which utilizes U-20Pu-10Zr alloy fuel and employs lead-bismuth as the coolant. The maximum neutron flux in the core reaches 1.32×10^(16) cm^(-2)s^(-1), while the average neutron flux in the irradiation channels attains 1.19×10^(16) cm^(-2)s^(-1). The volume of the central irradiation channel exceeds 10000 cm^(3), and the fuel cycle duration is 165 d, placing all its performance indicators among the top in the world. Based on the analyses of reactor physics and thermalhydraulics, it has been demonstrated that all reactivity coefficients are negative and all physical parameters meet the design criteria, ensuring the inherent safety of UFFR. An assessment of the irradiation capability has been carried out based on californium-252(^(252)Cf) production, indicating that the irradiation capability of UFFR surpasses that of the high flux isotope reactor(HFIR). The yield of ^(252)Cf from UFFR is 14.39 times that of HFIR, and its nuclei conversion rate is 3.21 times that of HFIR.
基金partially supported by the National Natural Science Foundation of China(Nos.32471474 and 82102574)the Precision Medicine Project of People’s Hospital of Xinjiang Uygur Autonomous Region(No.20220305)+4 种基金Chengdu Advanced Metal Materials Industry Technology Research Institute Co.,Ltd.Support Project(No.24H0802)Sichuan Science and Technology Program(Nos.2025YFHZ0086,2023YFS0053,2024YFHZ0125,and 2025ZNSFSC0381)Project of Tianfu Jincheng Laboratory(No.2025ZH009)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515220102)Xinjiang Autonomous Region Science and Technology Support Project Plan(Directive)Project(No.2024E02049)。
文摘Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.
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.
文摘Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.
