Three-way control combiner valves(TCCVs)are critical components used in nuclear power plants to regulate the concentration of boron acid for neutron absorption and reactor safety.However,current TCCV designs often suf...Three-way control combiner valves(TCCVs)are critical components used in nuclear power plants to regulate the concentration of boron acid for neutron absorption and reactor safety.However,current TCCV designs often suffer from suboptimal control performance and high flow resistance,leading to control deviations and reduced operational efficiency.In this paper,a numerical model based on the standard K–ωturbulence model is established and validated against experimental data to analyze the flow characteristics and local flow resistance of a TCCV.A parametric design method for the throttling windows is proposed,establishing relationships between shape parameters and performance indexes,including control performance and flow resistance.The adaptive non-dominated sorting genetic algorithm(ANSGA-II)is used to optimize the shape parameters of the throttling windows.The optimization results show an improvement in the performance indexes of the TCCV,with the adjustable operating range increasing by 31.0%and the maximum local resistance decreasing by 18.3%.We also introduce the concepts of effective and controllable domains to characterize the inlet backflow phenomena and regulation dead zones,which are crucial for ensuring the reliability and effectiveness of control valves.These findings provide insights for enhancing the design and performance of TCCVs in nuclear power plants.展开更多
In modern urban environments,limited space and the drive for building efficiency have led to the increasing prevalence of windowless offices.Because lighting is essential for mood,alertness,cognitive performance,healt...In modern urban environments,limited space and the drive for building efficiency have led to the increasing prevalence of windowless offices.Because lighting is essential for mood,alertness,cognitive performance,health,and productivity,the lack of natural daylight and outdoor views can adversely affect well-being and work out-comes.Consequently,artificial windows(AW),designed to replicate natural light and external views,have been proposed.This study compared real windows(RW),AW,and no windows(NW)to investigate their effects on cog-nitive performance and productivity among office workers during working phases.A controlled experiment was conducted,combining heart rate variability(HRV)data and cognitive tests.In addition,questionnaires were used to evaluate participants′subjective perceptions of the thermal and lighting environments.The results showed that AW led to better attention,short-term memory,and creativity.In particular,the time for attention tests was about 14.4%shorter than under NW,and the time for short-term memory tests was reduced by 6.7%.Focus,measured by the HRV(nLFHF)ratio,increased by approximately 22.2%,while subjective work efficiency demonstrated an even more substantial increase.Moreover,AW provided superior thermal and lighting perceptions compared to NW and even outperformed RW in lighting comfort and acceptability.Overall,these findings indicate that AW holds considerable potential for improving attention,productivity,and environmental comfort during working phases,offering an effective alternative for windowless offices.展开更多
Bionic anti-reflection windows are critical for enhancing the performance of aerospace infrared detection systems.The manufacturing of anti-reflective microstructures(ARMs),however,faces a significant challenge that t...Bionic anti-reflection windows are critical for enhancing the performance of aerospace infrared detection systems.The manufacturing of anti-reflective microstructures(ARMs),however,faces a significant challenge that the transmittance spectrum is difficult to predict both accurately and swiftly,leading to long-term reliance on blind and inefficient trial-and-error for process optimization.Here,we report a method that integrates machine learning(ML)with femtosecond laser for the rapid customization of high-performance anti-reflection windows.Embedding of the material’s absorption characteristics as a physical constraint into the ML model enables highly accurate prediction across an ultra-broad transmittance spectrum,overcoming the failure of conventional simulations in these intrinsic absorption bands.The trained ML model serves as an intelligent agent to guide the precise control over multiple femtosecond laser parameters,thus converting the costly process of physical trial-and-error into one of efficient virtual screening and iteration.As a proof of concept,an anti-reflective sapphire window was produced that demonstrates broadband(3.3–6.0μm)and high transmittance(~96.8%peak at 4.2μm),along with excellent wide-angle characteristics,mechanical wear resistance,and high-quality imaging capability.This work provides a novel paradigm for rapidly manufacturing high-performance anti-reflective windows,laying the foundation for next-generation optical components.展开更多
Towards the development of highly efficient electrochromic coatings,the crystallinity,morphology(e.g.size and shape)of electrochromic nanomaterials,and their charge insertion capacities play a significant role.Herein,...Towards the development of highly efficient electrochromic coatings,the crystallinity,morphology(e.g.size and shape)of electrochromic nanomaterials,and their charge insertion capacities play a significant role.Herein,we report the structure-dependent colouration effciency in electrochromic coatings based on the use of 0D,1D and 2D tungsten trioxide(WO3)nanostructures.A series of WO3with different nanostructures were prepared and used as working electrodes to fabricate electrochromic devices for smart windows applications.Facile spray coating was applied on fluorine-doped tin oxide(FTO)substrate to make~70%transparent working electrodes to investigate their charge insertion capacities,electrochromic active surface area,and colouration efficiency.Results showed that the 2D WO3nanoflakes displayed the highest diffusion coefficient for the intercalation of 1.52×10-10cm2/s with an increased electrochemical active surface area of 25.10 mF/cm2,a large modulation of optical reflectance(42.63%)with 3.79 s shorter response time for bleaching and a greater colouration efficiency(CE)value(89.29 cm2/C)at 700 nm compared to the CE value for 1D WO3(of 22 cm2/C)and 0D WO3(8 cm2/C).The outcome of this study provides a new insight and valuable contribution to design an efficient electrochromic coating by controlling and optimising the nanostructures of selective electrochromic materials.展开更多
Dual-band antireflection(DBAR)windows based on surface microstructures offer a promising solution for mid-wave infrared(MWIR)and long-wave infrared(LWIR)co-aperture composite imaging.However,micro-nano manufacturing t...Dual-band antireflection(DBAR)windows based on surface microstructures offer a promising solution for mid-wave infrared(MWIR)and long-wave infrared(LWIR)co-aperture composite imaging.However,micro-nano manufacturing technology faces significant challenges in efficiently producing highly uniform microstructures with characteristic dimensions of∼1μm across hundreds of millimeters.Here,we report a laser optical field modulation(LOFM)technology for the rapid manufacture of ultra-large-scale arrays of antireflection microholes(ARMHs)on large-aperture and non-perfectly planar windows.LOFM technology,which modulates laser pulses in both temporal and spatial domains,enhances ARMH aspect ratios from 0.1 to 0.8 without reducing manufacturing time,and maintains processing accuracy even with laser focus shifts,thereby addressing inconsistencies in large-area processing.As a proof of concept,approximately 7 billion ARMHs are fabricated on a 100-mm-diameter zinc sulfide(ZnS)window at a rate of 20000 holes per second using LOFM technology assisted by machine learning.The fabricated DBAR ZnS window exhibits ultra-broadband(3.5−14μm),high transmittance(91.1%),wide-angle transmission,wear-resistant,and self-cleaning,making it suitable for environments with multiple interference factors.Dual-band imaging applications demonstrate the significant advantages of DBAR windows in target recognition,multi-scenario robustness,and information acquisition.展开更多
Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining...Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.展开更多
Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable devel...Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(Tsol=83.8%,transparent state)and solar modulating ability(ΔTsol=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO2 passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.展开更多
The efficient regulation of sunlight to minimize unnecessary energy exchange through windows plays a vital role in advancing building energy efficiency.However,the inferior stability of cerium-doped tungsten trioxide(...The efficient regulation of sunlight to minimize unnecessary energy exchange through windows plays a vital role in advancing building energy efficiency.However,the inferior stability of cerium-doped tungsten trioxide(CWO)as a near-infrared(NIR)shielding material,combined with the poor mechanical properties of its coatings,poses significant challenges for long-term thermal insulation performance.Here,a hierarchical thermal insulation coating with multifunctional integration has been developed.The inner layer’s excellent NIR shielding performance(94.4%)results in a temperature reduction of 13.6°C,demonstrating outstanding thermal insulation.Meanwhile,the external layer composed of polysilsesquioxane grafted by carboxylated hexafluoropropylene trimer offers exceptional weather resistance due to the low surface energy.The fluorosilicone coating effectively mitigates oxidation of CWO,as evidenced by the retention of NIR shielding performance even after 30 days of exposure to 60°C and 90%relative humidity.Furthermore,the coating demonstrates superior anti-graffiti properties and achieves an ultra-high mechanical strength of 0.49 GPa through precise fluorine content modulation.This hierarchical design integrates high hardness,excellent abrasion resistance,anti-graffiti functionality,transparency,and long-term operational durability into a single smart window system,offering a promising solution for reducing building energy consumption.展开更多
With the diversification of electricity trading forms driven by distributed energy technologies,the continuous growth of blockchain’s chained data structure poses dual challenges to traditional B+tree indexes in term...With the diversification of electricity trading forms driven by distributed energy technologies,the continuous growth of blockchain’s chained data structure poses dual challenges to traditional B+tree indexes in terms of query efficiency and storage costs.This paper proposes a sliding window-based learned index construction method(SW-LI).The method consists of two key components.First,block timestamp-height samples are selected using a sliding window and used to train a linear regression model that captures the timestamp-to-height mapping.Second,an adaptive window adjustment mechanism is introduced:when the prediction error within a window exceeds a threshold,the window is contracted to improve local fitting accuracy;otherwise,it is expanded to accelerate global index construction.Together,these components dynamically balance model accuracy and training efficiency.Experimental results demonstrate that when the block count increases from 5000 to 25,000,SW-LI improves index construction efficiency by 69.22%-88.22%compared to Anole.Under a 10,000-block scale,its prediction error is reduced by an average of 80%compared to Sliding Window Search-enhanced Online Gradient Descent(SWS-OGD),with a storage overhead of only 60 KB(25,000 blocks),validating the method’s ability to maintain query accuracy while significantly enhancing indexing efficiency.When the block contains 4000 transactions,the average total query latency of SW-LI is 46.15%lower than that of Anole,which is only 2.7%of the average query latency of SWS-OGD(i.e.,approximately 37 times faster).展开更多
Although there is an increasing demand for subseasonal prediction,the skill of subseasonal forecasting is currently limited.Under specific oceanic and atmospheric conditions,the subseasonal forecast skill can reach a ...Although there is an increasing demand for subseasonal prediction,the skill of subseasonal forecasting is currently limited.Under specific oceanic and atmospheric conditions,the subseasonal forecast skill can reach a high level intermittently during a long period.Based on the S2S(subseasonal-to-seasonal)database,the forecast skill windows for surface air temperature(SAT)over East Asia are identified using the PCC(pattern correlation coefficient).Two longlasting windows stand out over the past 30 years—namely,the cold summer of 1993 and the hot summer of 1994 in central and northeastern East Asia.The two windows lasted about two months with high forecast skill in week-3 SAT,and even in week-4 and week-5 SAT.The persistent large-scale oceanic and atmospheric climate anomalies were generally reinforcing in these two summers,providing windows of opportunity for high forecast skill.The combination of the tropical western Pacific sea surface temperature anomaly(SSTA),the Japan Sea-Kuroshio-Kuroshio Extension(K-KE)SSTA,and the North Atlantic SSTA,favored the atmospheric teleconnection,resulting in the cold event in 1993 and the hot event in 1994.The NAO(North Atlantic Oscillation)stayed in its negative or positive phase persistently,contributing to the climate anomalies over East Asia.Climate model experiments with prescribed SST variations demonstrated that the SSTA in the three regions influences East Asian SAT.An index based on the preceding SSTA in the three regions can be used to help identify whether the current forecast case is within the real-time forecast window.This enhances the practical application of the study and has a positive impact on real-time operational forecasting.展开更多
VO2is a promising thermochromic material,but it is still limited by low transparency,weak solar modulation,and poor stability.Here,we develop a coordination‐compound‐derived strategy to construct a hierarchical B...VO2is a promising thermochromic material,but it is still limited by low transparency,weak solar modulation,and poor stability.Here,we develop a coordination‐compound‐derived strategy to construct a hierarchical BiVO4/VO2@BiVO4film with a core-shell@nanosheet structure.VO2@BiVO4nanoparticles form the inner layer,whereas porous BiVO4nanosheets assemble on the surface.This architecture provides synergistic benefits:The BiVO4shell protects VO2from oxidation and enhances plasmon‐induced solar modulation,and the nanosheets improve visible transparency via antireflection.The composite also exhibits photocatalytic self‐cleaning and antibacterial activity.It delivers 63.0%visible transmittance and 15.6%solar modulation,retaining 80%performance after 27 days at 100°C and 50%humidity.This work integrates optical performance,durability,and multifunctionality,offering a practical pathway for VO2‐based smart windows.展开更多
This work presents a cracked template and vacuum metal evaporation strategy for fabricating structurally randomized copper(Cu)mesh films.Regulating the internal stress distribution within the coating during template c...This work presents a cracked template and vacuum metal evaporation strategy for fabricating structurally randomized copper(Cu)mesh films.Regulating the internal stress distribution within the coating during template cracking enables the controlled fabrication of Cu mesh films with varying discrete degrees of mesh aperture area and distinct probability distributions of metal line inclination.The influence of structural parameter randomization within the Cu mesh films on properties has been systematically investigated,encompassing higher-order diffraction energy homogenization,optoelectronic performance,and electromagnetic interference shielding effectiveness(EMI SE).Results demonstrate that increasing structural randomization effectively suppresses higher-order diffraction energy,achieving a reduction to-3.93 dB in normalized higher-order diffraction energy.Furthermore,the Cu mesh film exhibited minimal degradation on imaging system performance,with resolution decreasing only marginally from 80.6 to 71.8 lp/mm.Simultaneously,the most randomized Cu mesh film demonstrates an ultra-low sheet resistance(3.31Ω/sq),high visible light transmittance(88.7%at 550 nm),an exceptional figure of merit(FoM=913.69),and robust EMI SE within the X-band(average SE of 33.18 dB).These findings underscore that metal mesh films incorporating structural randomization offer an effective strategy for enhancing EMI shielding in high-performance optoelectronic imaging systems.展开更多
Electrochromic smart windows(ESWs)can significantly reduce building energy consumption,but the high cost hinders large-scale production.The in situ growth of tungsten oxide(WO3)films is only by a simple immersion p...Electrochromic smart windows(ESWs)can significantly reduce building energy consumption,but the high cost hinders large-scale production.The in situ growth of tungsten oxide(WO3)films is only by a simple immersion process,the silver nanowires(AgNWs)undergo oxidation to Ag+ions through electron loss,and the liberated electrons provide driving force for the deposition of WO42-.Enabled the fabrication of large-area WO3films and ESWs were fabricated under minimal laboratory conditions,demonstrating the economic feasibility,efficient and reliable nature of industrial production.Structural characterization and density functional theory calculations were combined to confirm that AgNWs effectively regulate oxygen vacancies of WO3films and promote the in situ growth process.The optimized WO3exhibits a maximum transmittance modulation of 90.8%and excellent cycling stability of 20,000 cycles.The largescale WO3-based ESWs can save building energy up to 140.0 MJ m-2compared to traditional windows in tropical regions,as verified by simulations more than40 global cities.This research provides a new approach for improving the performance and industrial production of ESW,providing the full understanding and development direction to short the distance of the ESW commercial production.展开更多
Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories...Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.展开更多
The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the tradit...The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.展开更多
Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally...Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O3 pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.展开更多
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ...The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.展开更多
基金supported by the National Natural Science Foundation of China(No.52422506).
摘要Three-way control combiner valves(TCCVs)are critical components used in nuclear power plants to regulate the concentration of boron acid for neutron absorption and reactor safety.However,current TCCV designs often suffer from suboptimal control performance and high flow resistance,leading to control deviations and reduced operational efficiency.In this paper,a numerical model based on the standard K–ωturbulence model is established and validated against experimental data to analyze the flow characteristics and local flow resistance of a TCCV.A parametric design method for the throttling windows is proposed,establishing relationships between shape parameters and performance indexes,including control performance and flow resistance.The adaptive non-dominated sorting genetic algorithm(ANSGA-II)is used to optimize the shape parameters of the throttling windows.The optimization results show an improvement in the performance indexes of the TCCV,with the adjustable operating range increasing by 31.0%and the maximum local resistance decreasing by 18.3%.We also introduce the concepts of effective and controllable domains to characterize the inlet backflow phenomena and regulation dead zones,which are crucial for ensuring the reliability and effectiveness of control valves.These findings provide insights for enhancing the design and performance of TCCVs in nuclear power plants.
摘要In modern urban environments,limited space and the drive for building efficiency have led to the increasing prevalence of windowless offices.Because lighting is essential for mood,alertness,cognitive performance,health,and productivity,the lack of natural daylight and outdoor views can adversely affect well-being and work out-comes.Consequently,artificial windows(AW),designed to replicate natural light and external views,have been proposed.This study compared real windows(RW),AW,and no windows(NW)to investigate their effects on cog-nitive performance and productivity among office workers during working phases.A controlled experiment was conducted,combining heart rate variability(HRV)data and cognitive tests.In addition,questionnaires were used to evaluate participants′subjective perceptions of the thermal and lighting environments.The results showed that AW led to better attention,short-term memory,and creativity.In particular,the time for attention tests was about 14.4%shorter than under NW,and the time for short-term memory tests was reduced by 6.7%.Focus,measured by the HRV(nLFHF)ratio,increased by approximately 22.2%,while subjective work efficiency demonstrated an even more substantial increase.Moreover,AW provided superior thermal and lighting perceptions compared to NW and even outperformed RW in lighting comfort and acceptability.Overall,these findings indicate that AW holds considerable potential for improving attention,productivity,and environmental comfort during working phases,offering an effective alternative for windowless offices.
基金financial supports from National Key R&D Program of China(Grant No.2023YFB4605500)Key Program for Basic Research(Grant No.JCKY2024210A001)+3 种基金National Natural Science Foundation of China(Grant No.52105498)Natural Science Foundation of Hunan Province(Grant No.2023JJ40736,Grant No.2026JJ50177)State Key Laboratory of Ultrafast Optical Science and Technology(Grant No.2025SKL-uFAST-KF22)State Key Laboratory of Precision Manufacturing for Extreme Service Performance(Grant No.ZZYJKT2023-08).
摘要Bionic anti-reflection windows are critical for enhancing the performance of aerospace infrared detection systems.The manufacturing of anti-reflective microstructures(ARMs),however,faces a significant challenge that the transmittance spectrum is difficult to predict both accurately and swiftly,leading to long-term reliance on blind and inefficient trial-and-error for process optimization.Here,we report a method that integrates machine learning(ML)with femtosecond laser for the rapid customization of high-performance anti-reflection windows.Embedding of the material’s absorption characteristics as a physical constraint into the ML model enables highly accurate prediction across an ultra-broad transmittance spectrum,overcoming the failure of conventional simulations in these intrinsic absorption bands.The trained ML model serves as an intelligent agent to guide the precise control over multiple femtosecond laser parameters,thus converting the costly process of physical trial-and-error into one of efficient virtual screening and iteration.As a proof of concept,an anti-reflective sapphire window was produced that demonstrates broadband(3.3–6.0μm)and high transmittance(~96.8%peak at 4.2μm),along with excellent wide-angle characteristics,mechanical wear resistance,and high-quality imaging capability.This work provides a novel paradigm for rapidly manufacturing high-performance anti-reflective windows,laying the foundation for next-generation optical components.
基金the funding by the ARC Research Hub for Advanced Manufacturing with 2D Materials(ARC IH210100025)。
摘要Towards the development of highly efficient electrochromic coatings,the crystallinity,morphology(e.g.size and shape)of electrochromic nanomaterials,and their charge insertion capacities play a significant role.Herein,we report the structure-dependent colouration effciency in electrochromic coatings based on the use of 0D,1D and 2D tungsten trioxide(WO3)nanostructures.A series of WO3with different nanostructures were prepared and used as working electrodes to fabricate electrochromic devices for smart windows applications.Facile spray coating was applied on fluorine-doped tin oxide(FTO)substrate to make~70%transparent working electrodes to investigate their charge insertion capacities,electrochromic active surface area,and colouration efficiency.Results showed that the 2D WO3nanoflakes displayed the highest diffusion coefficient for the intercalation of 1.52×10-10cm2/s with an increased electrochemical active surface area of 25.10 mF/cm2,a large modulation of optical reflectance(42.63%)with 3.79 s shorter response time for bleaching and a greater colouration efficiency(CE)value(89.29 cm2/C)at 700 nm compared to the CE value for 1D WO3(of 22 cm2/C)and 0D WO3(8 cm2/C).The outcome of this study provides a new insight and valuable contribution to design an efficient electrochromic coating by controlling and optimising the nanostructures of selective electrochromic materials.
基金supported by the National Key R&D Program of China(Grant No.2023YFB4605500)Excellent Young Scientists Program of Hunan Provincial Department of Education(Grant No.23B0017)+2 种基金National Natural Science Foundation of China(Grant No.52105498)Natural Science Foundation of Hunan Province(Grant No.2023JJ40736)National Postdoctoral Program for Innovative Talents(BX20220353).
摘要Dual-band antireflection(DBAR)windows based on surface microstructures offer a promising solution for mid-wave infrared(MWIR)and long-wave infrared(LWIR)co-aperture composite imaging.However,micro-nano manufacturing technology faces significant challenges in efficiently producing highly uniform microstructures with characteristic dimensions of∼1μm across hundreds of millimeters.Here,we report a laser optical field modulation(LOFM)technology for the rapid manufacture of ultra-large-scale arrays of antireflection microholes(ARMHs)on large-aperture and non-perfectly planar windows.LOFM technology,which modulates laser pulses in both temporal and spatial domains,enhances ARMH aspect ratios from 0.1 to 0.8 without reducing manufacturing time,and maintains processing accuracy even with laser focus shifts,thereby addressing inconsistencies in large-area processing.As a proof of concept,approximately 7 billion ARMHs are fabricated on a 100-mm-diameter zinc sulfide(ZnS)window at a rate of 20000 holes per second using LOFM technology assisted by machine learning.The fabricated DBAR ZnS window exhibits ultra-broadband(3.5−14μm),high transmittance(91.1%),wide-angle transmission,wear-resistant,and self-cleaning,making it suitable for environments with multiple interference factors.Dual-band imaging applications demonstrate the significant advantages of DBAR windows in target recognition,multi-scenario robustness,and information acquisition.
基金funded on the one hand by Agence de l'Innovation de Défense(AID)grant reference number 2021650044on the other hand by Ecole Centrale de Nantes。
摘要Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.
基金supported by Natural Science Foundation of China(Grant No.52372076,52073081,52203322,5252200843)Ministry of Science and Technology of the People’s Republic of China(2023YFB3812800)Fundamental Research Funds for the Central Universities(FRF-TP-25-073)。
摘要Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(Tsol=83.8%,transparent state)and solar modulating ability(ΔTsol=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO2 passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.
基金financially supported by Shandong Province Postdoctoral Innovation Project(No.SDCX-ZG-202302017)Natural Science Foundation of Shandong Province(Nos.ZR2022QB045,ZR2024QB019 and ZR2025QC564).
摘要The efficient regulation of sunlight to minimize unnecessary energy exchange through windows plays a vital role in advancing building energy efficiency.However,the inferior stability of cerium-doped tungsten trioxide(CWO)as a near-infrared(NIR)shielding material,combined with the poor mechanical properties of its coatings,poses significant challenges for long-term thermal insulation performance.Here,a hierarchical thermal insulation coating with multifunctional integration has been developed.The inner layer’s excellent NIR shielding performance(94.4%)results in a temperature reduction of 13.6°C,demonstrating outstanding thermal insulation.Meanwhile,the external layer composed of polysilsesquioxane grafted by carboxylated hexafluoropropylene trimer offers exceptional weather resistance due to the low surface energy.The fluorosilicone coating effectively mitigates oxidation of CWO,as evidenced by the retention of NIR shielding performance even after 30 days of exposure to 60°C and 90%relative humidity.Furthermore,the coating demonstrates superior anti-graffiti properties and achieves an ultra-high mechanical strength of 0.49 GPa through precise fluorine content modulation.This hierarchical design integrates high hardness,excellent abrasion resistance,anti-graffiti functionality,transparency,and long-term operational durability into a single smart window system,offering a promising solution for reducing building energy consumption.
基金supported by the National Key Research and Development Program of China(No.2022YFB3105100).
摘要With the diversification of electricity trading forms driven by distributed energy technologies,the continuous growth of blockchain’s chained data structure poses dual challenges to traditional B+tree indexes in terms of query efficiency and storage costs.This paper proposes a sliding window-based learned index construction method(SW-LI).The method consists of two key components.First,block timestamp-height samples are selected using a sliding window and used to train a linear regression model that captures the timestamp-to-height mapping.Second,an adaptive window adjustment mechanism is introduced:when the prediction error within a window exceeds a threshold,the window is contracted to improve local fitting accuracy;otherwise,it is expanded to accelerate global index construction.Together,these components dynamically balance model accuracy and training efficiency.Experimental results demonstrate that when the block count increases from 5000 to 25,000,SW-LI improves index construction efficiency by 69.22%-88.22%compared to Anole.Under a 10,000-block scale,its prediction error is reduced by an average of 80%compared to Sliding Window Search-enhanced Online Gradient Descent(SWS-OGD),with a storage overhead of only 60 KB(25,000 blocks),validating the method’s ability to maintain query accuracy while significantly enhancing indexing efficiency.When the block contains 4000 transactions,the average total query latency of SW-LI is 46.15%lower than that of Anole,which is only 2.7%of the average query latency of SWS-OGD(i.e.,approximately 37 times faster).
基金supported by the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2024QZKK0301)the S&T Development Fund of CAMS(Grant Nos.2023KJ040 and 2024KJ013)。
摘要Although there is an increasing demand for subseasonal prediction,the skill of subseasonal forecasting is currently limited.Under specific oceanic and atmospheric conditions,the subseasonal forecast skill can reach a high level intermittently during a long period.Based on the S2S(subseasonal-to-seasonal)database,the forecast skill windows for surface air temperature(SAT)over East Asia are identified using the PCC(pattern correlation coefficient).Two longlasting windows stand out over the past 30 years—namely,the cold summer of 1993 and the hot summer of 1994 in central and northeastern East Asia.The two windows lasted about two months with high forecast skill in week-3 SAT,and even in week-4 and week-5 SAT.The persistent large-scale oceanic and atmospheric climate anomalies were generally reinforcing in these two summers,providing windows of opportunity for high forecast skill.The combination of the tropical western Pacific sea surface temperature anomaly(SSTA),the Japan Sea-Kuroshio-Kuroshio Extension(K-KE)SSTA,and the North Atlantic SSTA,favored the atmospheric teleconnection,resulting in the cold event in 1993 and the hot event in 1994.The NAO(North Atlantic Oscillation)stayed in its negative or positive phase persistently,contributing to the climate anomalies over East Asia.Climate model experiments with prescribed SST variations demonstrated that the SSTA in the three regions influences East Asian SAT.An index based on the preceding SSTA in the three regions can be used to help identify whether the current forecast case is within the real-time forecast window.This enhances the practical application of the study and has a positive impact on real-time operational forecasting.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52422213 and 52272212)the Natural Science Foundation of Shandong Province(Grant Nos.ZR2022JQ20 and ZR2025QC589)the Taishan Scholar Project of Shandong Province(Grant No.tsqn202211168).
摘要VO2is a promising thermochromic material,but it is still limited by low transparency,weak solar modulation,and poor stability.Here,we develop a coordination‐compound‐derived strategy to construct a hierarchical BiVO4/VO2@BiVO4film with a core-shell@nanosheet structure.VO2@BiVO4nanoparticles form the inner layer,whereas porous BiVO4nanosheets assemble on the surface.This architecture provides synergistic benefits:The BiVO4shell protects VO2from oxidation and enhances plasmon‐induced solar modulation,and the nanosheets improve visible transparency via antireflection.The composite also exhibits photocatalytic self‐cleaning and antibacterial activity.It delivers 63.0%visible transmittance and 15.6%solar modulation,retaining 80%performance after 27 days at 100°C and 50%humidity.This work integrates optical performance,durability,and multifunctionality,offering a practical pathway for VO2‐based smart windows.
基金supported by the Aeronautical Science Foundation of China(202400080M9001)the Natural Science Basic Research Program of Shaanxi(2024JC-YBQN-0518)。
摘要This work presents a cracked template and vacuum metal evaporation strategy for fabricating structurally randomized copper(Cu)mesh films.Regulating the internal stress distribution within the coating during template cracking enables the controlled fabrication of Cu mesh films with varying discrete degrees of mesh aperture area and distinct probability distributions of metal line inclination.The influence of structural parameter randomization within the Cu mesh films on properties has been systematically investigated,encompassing higher-order diffraction energy homogenization,optoelectronic performance,and electromagnetic interference shielding effectiveness(EMI SE).Results demonstrate that increasing structural randomization effectively suppresses higher-order diffraction energy,achieving a reduction to-3.93 dB in normalized higher-order diffraction energy.Furthermore,the Cu mesh film exhibited minimal degradation on imaging system performance,with resolution decreasing only marginally from 80.6 to 71.8 lp/mm.Simultaneously,the most randomized Cu mesh film demonstrates an ultra-low sheet resistance(3.31Ω/sq),high visible light transmittance(88.7%at 550 nm),an exceptional figure of merit(FoM=913.69),and robust EMI SE within the X-band(average SE of 33.18 dB).These findings underscore that metal mesh films incorporating structural randomization offer an effective strategy for enhancing EMI shielding in high-performance optoelectronic imaging systems.
基金the National Natural Science Foundation of China(grant No.52163022,62305076)Sichuan Science and Technology Program(2024ZYD0196)+1 种基金China Postdoctoral Science Foundation(2023M740505)Sichuan Postdoctoral Science Special Foundation(No.TB2023010)。
摘要Electrochromic smart windows(ESWs)can significantly reduce building energy consumption,but the high cost hinders large-scale production.The in situ growth of tungsten oxide(WO3)films is only by a simple immersion process,the silver nanowires(AgNWs)undergo oxidation to Ag+ions through electron loss,and the liberated electrons provide driving force for the deposition of WO42-.Enabled the fabrication of large-area WO3films and ESWs were fabricated under minimal laboratory conditions,demonstrating the economic feasibility,efficient and reliable nature of industrial production.Structural characterization and density functional theory calculations were combined to confirm that AgNWs effectively regulate oxygen vacancies of WO3films and promote the in situ growth process.The optimized WO3exhibits a maximum transmittance modulation of 90.8%and excellent cycling stability of 20,000 cycles.The largescale WO3-based ESWs can save building energy up to 140.0 MJ m-2compared to traditional windows in tropical regions,as verified by simulations more than40 global cities.This research provides a new approach for improving the performance and industrial production of ESW,providing the full understanding and development direction to short the distance of the ESW commercial production.
基金supported by the National Natural Science Foundation of China(32371028,32300822,U24A20373,and 82071177)the Shanghai Rising-Star Program(24QA2704800)+2 种基金the Shanghai Jiao Tong University 2030 InitiativeShanghai Municipal Health Commission(202340046)the Fund for Excellent Young Scholars of Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine.
摘要Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.
基金supported by National Natural Science Foundation of China(42364008,41804110)in part by Guizhou Provincial Basic Research Program(Natural Science)(ZK[2022]060)+1 种基金in part by China Postdoctoral Science Foundation(2022M723127)in part by Youth Innovation Team Project of Shandong Provincial Education Department(2022KJ141).
摘要The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.
基金supported by the Natural Science Foundation of Henan Province[grant number:242300420115]Key Scientific Research Projects in Universities of Henan Province[grant number:23A330006].
摘要Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O3 pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.
摘要The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.