Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop spec...Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.展开更多
Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalyst...Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.展开更多
Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 waveba...Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 wavebands needs to be designed and prepared,while simultaneously satisfying high reflection in 2 wave-bands and high transmittance in 3 wavebands.Therefore,we have conducted a systematic study on the film design,thin film preparation process,and control accuracy of film layer thickness.In this work,the short-wave pass film system is superimposed with the long-wave pass film system,and the number of cycles and matching coefficient of the film system are tuned to meet the requirements of cut-off band.Additionally,Smith method was used to match bandpass film system to optimize the transmission band and complete the visible/near infrared multiband laser filter film design.In the preparation process,combined with the sensitiv-ity of the film layer,inverse analysis is used to invert the film layer monitored by each optical monitoring chip.The optical control scheme with weak optical signal in the monitoring process is simulated and correc-ted,and the monitoring wavelength with stronger optical signal is matched,resulting in an improvement of the control accuracy for the film thickness and the transmittance in the specified wavelength range.Ulti-mately,the actual physical thickness is 9.66μm,and the error with the theoretical design thickness is less than 0.4%,and the transmittance of the specified 3 wavebands exceeds 99%.The average transmittance of the cut-off bands at the 455−500 nm and 910−1000 nm is 0.45% and 0.16%,respectively.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
The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,effic...The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.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
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
This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post...This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post-assessment,summary)instructional model.The reform addresses the gap between syntax-based programming instruction and the need for higher-level skills in abstraction,modularity,and software architecture.The course is anchored in a semester-long,project-based learning platform centered on a Java-based Aircraft Battle Game,progressing through six iterative experiments.Each experiment targets specific competencies within the structured BOPPPS teaching cycle and is aligned with specific OBE learning outcomes.A case study on the Factory Pattern illustrates how the BOPPPS model fosters conceptual understanding and practical application.Evaluation results from the 2023 and 2024 spring semesters show improved outcomes:Project completion rose from 87%to 95%,37%of students implemented innovative features,and average final grades increased by 7%.The results affirm that the OBE+BOPPPS integration strengthens engagement,deepens understanding,and equips students with real-world software development competencies.展开更多
Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for ...Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for renewable energy and constructing self-powered electronics.In this review,we begin by outlining the fundamental mechanisms—ion diffusion,electric double layer formation,and streaming potential—that govern charge transport for MEG in moist environments.A comprehensive survey of material innovations follows,highlighting breakthroughs in carbon-based materials,conductive polymers,hydrogels,and bio-inspired systems that enhance MEG performance,scalability,and biocompatibility.We then explore a range of device architectures,from planar and layered systems to flexible,miniaturized,and textile-integrated designs,engineered for both energy conversion and sensor integration.Key challenges are analyzed,along with strategies for overcoming them.We conclude with a forward-looking perspective on future directions,including hybrid energy systems,AI-assisted material design,and real-world deployment.This review presents a timely and comprehensive overview of MEG technologies and their trajectory toward practical and sustainable energy solutions.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
Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant pr...Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.展开更多
High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by t...High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by the alloy interface structures.Despite substantial efforts,a comprehensive overview of interface engineering of high-performance alloys has not been presented so far.In this study,the interfaces in high-performance alloys,particularly grain and phase boundaries,were systematically examined,with emphasis on their crystallographic characteristics and chemical element segregations.The effects of the interfaces on the electrical conductivity,mechanical strength,toughness,hydrogen embrittlement resistance,and thermal stability of the alloys were elucidated.Moreover,correlations among various types of interfaces and advanced experimental and computational techniques were examined using big data analytics,enabling robust design strategies.Challenges currently faced in the field of interface engineering and emerging opportunities in the field are also discussed.The study results would guide the development of next-generation high-performance alloys.展开更多
The Circular Electron Positron Collider(CEPC)proposed in China is a dual-ring collider with electron and positron beams in the energy range of 45.5–180 GeV.The main dipole in the CEPC collider is a dual-aperture dipo...The Circular Electron Positron Collider(CEPC)proposed in China is a dual-ring collider with electron and positron beams in the energy range of 45.5–180 GeV.The main dipole in the CEPC collider is a dual-aperture dipole with a shared coil between the two apertures,forming an I-shaped structure that can reduce power consumption by 50%.Because of its long length and low field strength,the development of this dual-aperture magnet faces challenges regarding its mechanical design,field measurement accuracy,and field performance.Numerical simulations were performed to better understand the Earth's field and the effect of different BH curves on field performance.The field results of the prototype are presented herein,and the field quality satisfies the requirements.The remanent field accounts for 2%of the integral field at 140 Gs,and the hysteresis effect caused an increase in field strength of approximately 0.075%after a standardization cycle of the trim coils.Research on this prototype can provide useful insights for understanding low-field dipole magnets.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
Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuatio...Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuation across the human auditory range.This study presents a double-phase fidget-spinner-shaped acoustic metamaterial(DFAM),specifically designed to achieve an ultra-broad,low-frequency continuous bandgap by means of synergistic structural optimization,enabling effective and robust control of audible noise.Based on Bloch's theorem and the finite element method,the dispersion relation of the DFAM structure is calculated and verified by the transmission loss curves.The propagation characteristics of sound waves within the structure are further analyzed for noise frequencies that fall within the passband.The influence of the geometric and physical parameters on the bandgap is investigated,and the corresponding transmission loss in the propagation direction is further calculated.A hybrid collaborative design strategy,leveraging multi-parameter optimization and bandgap complementarity,is developed to construct a metastructure with continuous bandgap coverage from 20 Hz to 1000 Hz.The resulting metastructure demonstrates exceptional broadband noise attenuation,achieving a total bandgap width of 876.3 Hz(87.63% of the target range)with the transmission loss up to-762.78 d B in a three-periodic arrangement.The simulation and experimental results for the transmission loss of the DFAM metastructure show strong agreement in the low-frequency range.This work provides a novel framework for designing ultra-wide low-frequency continuous bandgap metastructures,offering significant potential for noise mitigation in complex environments.展开更多
Previous solar probes have relied on solar energy for power,but in the near-solar environment,traditional solar panels are prone to overheating and radiation damage,increasing system complexity and reducing power reli...Previous solar probes have relied on solar energy for power,but in the near-solar environment,traditional solar panels are prone to overheating and radiation damage,increasing system complexity and reducing power reliability.This study introduces a dual-power system integrating solar-thermal thermoelectric generation with photovoltaic technology.First,suitable thermoelectric materials are screened,the geometric structure of the thermoelectric devices is simulated,and then the fabricated thermoelectric devices are subjected to cyclic heatingcooling power generation tests and long-duration high-temperature power generation tests.The results demonstrate that a single thermoelectric device can stably provide 3.5 W of power with excellent cycling stability.Additionally,this study discusses design concepts for energy storage and intelligent energy management systems required by the dualpower system.Designed for the Solar Close Observations and Proximity Experiments(SCOPE)mission,this dualpower supply system integrates the benefits of both to address demands under varying environmental conditions.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
基金funded High-Level Talents project of Henan Agricultural University(111-30501301)Project of the National key R&D Program of China(2021YFA0909600)+3 种基金Natural Science Foundation of Henan Province(242300420141)the China Postdoctoral Science Foundation(2020M672308)Cultivation Program for Young Backbone Teachers at Henan University of Technology(DC 11)Science Project 110202101042(JY 19)/2022530000241007,110202102033,110202202038.
文摘Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.
基金supported by the funds of the Ministry of Science and Technology of China(2019YFA0904700)the National Natural Science Foundation of China(32471477)to Cheng Qi.
文摘Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.
文摘Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 wavebands needs to be designed and prepared,while simultaneously satisfying high reflection in 2 wave-bands and high transmittance in 3 wavebands.Therefore,we have conducted a systematic study on the film design,thin film preparation process,and control accuracy of film layer thickness.In this work,the short-wave pass film system is superimposed with the long-wave pass film system,and the number of cycles and matching coefficient of the film system are tuned to meet the requirements of cut-off band.Additionally,Smith method was used to match bandpass film system to optimize the transmission band and complete the visible/near infrared multiband laser filter film design.In the preparation process,combined with the sensitiv-ity of the film layer,inverse analysis is used to invert the film layer monitored by each optical monitoring chip.The optical control scheme with weak optical signal in the monitoring process is simulated and correc-ted,and the monitoring wavelength with stronger optical signal is matched,resulting in an improvement of the control accuracy for the film thickness and the transmittance in the specified wavelength range.Ulti-mately,the actual physical thickness is 9.66μm,and the error with the theoretical design thickness is less than 0.4%,and the transmittance of the specified 3 wavebands exceeds 99%.The average transmittance of the cut-off bands at the 455−500 nm and 910−1000 nm is 0.45% and 0.16%,respectively.
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 Key R&D Program of China(2023YFA1507400)the National Natural Science Foundation of China(Grant No.22325805,22441010,22408203)+2 种基金Beijing Natural Science Foundation(Grant No.JQ22003)the Haihe Laboratory of Sustainable Chemical Transformations(24HHWCSS00007)Tsinghua University Dushi Program,and Sinopec Group(PR20232572).
文摘The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.
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 in part by the Guangdong Province Education Science Planning Project(Higher Education Project,Project No.2024GXJK410)Shenzhen Education Science“14th Five-Year Plan”2023 Annual Project on Artificial Intelligence Special Project under Grant No.rgzn23001,the Guangdong Province Higher Education Research and Reform Project under Grant No.YueJiaoGaoHan(2024)No.9+1 种基金the Guangdong Province General Colleges and Universities Innovation Team Project under No.2022KCXTD038the Guangdong Provincial Hardware and System Teaching&Research Office Quality Engineering Project under No.HITSZERP22002.
文摘This study presents a teaching reform for the Object-oriented Software Construction(OOSC)course by integrating outcome-based education(OBE)and the BOPPPS(bridge-In,objectives,pre-assessment,participatory learning,post-assessment,summary)instructional model.The reform addresses the gap between syntax-based programming instruction and the need for higher-level skills in abstraction,modularity,and software architecture.The course is anchored in a semester-long,project-based learning platform centered on a Java-based Aircraft Battle Game,progressing through six iterative experiments.Each experiment targets specific competencies within the structured BOPPPS teaching cycle and is aligned with specific OBE learning outcomes.A case study on the Factory Pattern illustrates how the BOPPPS model fosters conceptual understanding and practical application.Evaluation results from the 2023 and 2024 spring semesters show improved outcomes:Project completion rose from 87%to 95%,37%of students implemented innovative features,and average final grades increased by 7%.The results affirm that the OBE+BOPPPS integration strengthens engagement,deepens understanding,and equips students with real-world software development competencies.
基金supported by the National Natural Science Foundation of China(52305388,BE0200030)Shanghai Pujiang Program(22PJ1407600)+1 种基金SJTU Explore X programShanghai Jiao Tong University Initiative Scientific Research Program(WH220402021)。
文摘Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for renewable energy and constructing self-powered electronics.In this review,we begin by outlining the fundamental mechanisms—ion diffusion,electric double layer formation,and streaming potential—that govern charge transport for MEG in moist environments.A comprehensive survey of material innovations follows,highlighting breakthroughs in carbon-based materials,conductive polymers,hydrogels,and bio-inspired systems that enhance MEG performance,scalability,and biocompatibility.We then explore a range of device architectures,from planar and layered systems to flexible,miniaturized,and textile-integrated designs,engineered for both energy conversion and sensor integration.Key challenges are analyzed,along with strategies for overcoming them.We conclude with a forward-looking perspective on future directions,including hybrid energy systems,AI-assisted material design,and real-world deployment.This review presents a timely and comprehensive overview of MEG technologies and their trajectory toward practical and sustainable energy solutions.
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the National Natural Science Foundation of China(Grant No.32371823)the Liaoning Province Xingliao Talents Leading Talent Program(Grant No.XLYC2402043)the Open Foundation of State Key Laboratory of Woody Oil Resources Utilization(Grant No.SKLN EFU202517).
文摘Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.
基金supported by the National Natural Science Foundation of China(Nos.52122408 and 52474397)the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences(No.242017127)+1 种基金the financial support from the Fundamental Research Funds for the Central Universities(University of Science and Technology Beijing(USTB),Nos.FRF-TP-2021-04C1 and 06500135)supported by USTB MatCom of Beijing Advanced Innovation Center for Materials Genome Engineering。
文摘High-performance alloys are indispensable in modern engineering because of their exceptional strength,ductility,corrosion resistance,fatigue resistance,and thermal stability,which are all significantly influenced by the alloy interface structures.Despite substantial efforts,a comprehensive overview of interface engineering of high-performance alloys has not been presented so far.In this study,the interfaces in high-performance alloys,particularly grain and phase boundaries,were systematically examined,with emphasis on their crystallographic characteristics and chemical element segregations.The effects of the interfaces on the electrical conductivity,mechanical strength,toughness,hydrogen embrittlement resistance,and thermal stability of the alloys were elucidated.Moreover,correlations among various types of interfaces and advanced experimental and computational techniques were examined using big data analytics,enabling robust design strategies.Challenges currently faced in the field of interface engineering and emerging opportunities in the field are also discussed.The study results would guide the development of next-generation high-performance alloys.
文摘The Circular Electron Positron Collider(CEPC)proposed in China is a dual-ring collider with electron and positron beams in the energy range of 45.5–180 GeV.The main dipole in the CEPC collider is a dual-aperture dipole with a shared coil between the two apertures,forming an I-shaped structure that can reduce power consumption by 50%.Because of its long length and low field strength,the development of this dual-aperture magnet faces challenges regarding its mechanical design,field measurement accuracy,and field performance.Numerical simulations were performed to better understand the Earth's field and the effect of different BH curves on field performance.The field results of the prototype are presented herein,and the field quality satisfies the requirements.The remanent field accounts for 2%of the integral field at 140 Gs,and the hysteresis effect caused an increase in field strength of approximately 0.075%after a standardization cycle of the trim coils.Research on this prototype can provide useful insights for understanding low-field dipole magnets.
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Project supported by the National Natural Science Foundation of China(No.12572020)the Key Project of Natural Science Foundation of Hebei Province of China(No.A2023210064)。
文摘Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuation across the human auditory range.This study presents a double-phase fidget-spinner-shaped acoustic metamaterial(DFAM),specifically designed to achieve an ultra-broad,low-frequency continuous bandgap by means of synergistic structural optimization,enabling effective and robust control of audible noise.Based on Bloch's theorem and the finite element method,the dispersion relation of the DFAM structure is calculated and verified by the transmission loss curves.The propagation characteristics of sound waves within the structure are further analyzed for noise frequencies that fall within the passband.The influence of the geometric and physical parameters on the bandgap is investigated,and the corresponding transmission loss in the propagation direction is further calculated.A hybrid collaborative design strategy,leveraging multi-parameter optimization and bandgap complementarity,is developed to construct a metastructure with continuous bandgap coverage from 20 Hz to 1000 Hz.The resulting metastructure demonstrates exceptional broadband noise attenuation,achieving a total bandgap width of 876.3 Hz(87.63% of the target range)with the transmission loss up to-762.78 d B in a three-periodic arrangement.The simulation and experimental results for the transmission loss of the DFAM metastructure show strong agreement in the low-frequency range.This work provides a novel framework for designing ultra-wide low-frequency continuous bandgap metastructures,offering significant potential for noise mitigation in complex environments.
基金supported by National Key R&D Program of China(2022YFF0503804).
文摘Previous solar probes have relied on solar energy for power,but in the near-solar environment,traditional solar panels are prone to overheating and radiation damage,increasing system complexity and reducing power reliability.This study introduces a dual-power system integrating solar-thermal thermoelectric generation with photovoltaic technology.First,suitable thermoelectric materials are screened,the geometric structure of the thermoelectric devices is simulated,and then the fabricated thermoelectric devices are subjected to cyclic heatingcooling power generation tests and long-duration high-temperature power generation tests.The results demonstrate that a single thermoelectric device can stably provide 3.5 W of power with excellent cycling stability.Additionally,this study discusses design concepts for energy storage and intelligent energy management systems required by the dualpower system.Designed for the Solar Close Observations and Proximity Experiments(SCOPE)mission,this dualpower supply system integrates the benefits of both to address demands under varying environmental conditions.
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.
