In this paper,we construct a power type functional which is the approximation functional of the Singular Trudinger-Moser functional.Moreover,we obtain the concentration level of the functional and show it converges to...In this paper,we construct a power type functional which is the approximation functional of the Singular Trudinger-Moser functional.Moreover,we obtain the concentration level of the functional and show it converges to the concentration level of singular Trudinger-Moser functional on the unit ball.展开更多
As an essential candidate for environment-friendly luminescent quantum dots(QDs),CuInS-based QDs have attracted more attention in recent years.However,several drawbacks still hamper their industrial applications,such ...As an essential candidate for environment-friendly luminescent quantum dots(QDs),CuInS-based QDs have attracted more attention in recent years.However,several drawbacks still hamper their industrial applications,such as lower photoluminescence quantum yield(PLQY),complex synthetic pathways,uncontrollable emission spectra,and insufficient photostability.In this study,CuInZnS@ZnS core/shell QDs was prepared via a one-pot/three-step synthetic scheme with accurate and tunable control of PL spectra.Then their ensemble spectroscopic properties during nucleation formation,alloying,and ZnS shell growth processes were systematically investigated.PL peaks of these QDs can be precisely manipulated from 530 to 850 nm by controlling the stoichiometric ratio of Cu/In,Zn^(2+)doping and ZnS shell growth.In particular,CuInZnS@ZnS QDs possess a significantly long emission lifetime(up to 750 ns),high PLQY(up to 85%),and excellent crystallinity.Their spectroscopic evolution is well validated by Cu-deficient related intragap emission model.By controlling the stoichiometric ratio of Cu/In,two distinct Cu-deficient related emission pathways are established based on the differing oxidation states of Cu defects.Therefore,this work provides deeper insights for fabricating high luminescent ternary or quaternary-alloyed QDs.展开更多
Smart batteries play a key role in upgrading energy storage systems.However,they require a well-balanced integration of material structure,functional properties,and electrochemical performance,and their development is...Smart batteries play a key role in upgrading energy storage systems.However,they require a well-balanced integration of material structure,functional properties,and electrochemical performance,and their development is limited by conventional material systems in terms of energy density,response time,and functional integration.Carbon materials have emerged as a key solution for overcoming these problems due to their structural adjustability and multifunctional compatibility.Strategies for improving their electrochemical performance by changing the pore structure and interlayer spacing,as well as chemical functionalization,and composite design are analyzed,and their impact on improving the specific capacity and cycling stability of batteries is demonstrated.The unique advantages of carbon materials in realizing smart functions such as power supply,real-time monitoring and energy management in smart batteries are also discussed.Based on current progress in related fields,the prospects for the use of carbon materials in smart batteries are evaluated.展开更多
To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the...To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the glass-metal hetero-bonding process.This study focuses on the analysis and experimental re-search of the bonding layer in the integrated structure.By optimizing the structural configuration and select-ing suitable bonding processes,the reliability of the telescope system is enhanced.The research indicates that using J-133 adhesive achieves the best performance,with a bonding layer thickness of 0.30 mm and a metal substrate surface roughness of Ra 0.8.These findings significantly enhance the reliability of the optical sys-tem while minimizing potential risks.展开更多
To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stabil...To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.展开更多
In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
文摘In this paper,we construct a power type functional which is the approximation functional of the Singular Trudinger-Moser functional.Moreover,we obtain the concentration level of the functional and show it converges to the concentration level of singular Trudinger-Moser functional on the unit ball.
基金Fund Project for Transformation of Scientific and Technological Achievements of Jiangsu Province of China(BA2023020)。
文摘As an essential candidate for environment-friendly luminescent quantum dots(QDs),CuInS-based QDs have attracted more attention in recent years.However,several drawbacks still hamper their industrial applications,such as lower photoluminescence quantum yield(PLQY),complex synthetic pathways,uncontrollable emission spectra,and insufficient photostability.In this study,CuInZnS@ZnS core/shell QDs was prepared via a one-pot/three-step synthetic scheme with accurate and tunable control of PL spectra.Then their ensemble spectroscopic properties during nucleation formation,alloying,and ZnS shell growth processes were systematically investigated.PL peaks of these QDs can be precisely manipulated from 530 to 850 nm by controlling the stoichiometric ratio of Cu/In,Zn^(2+)doping and ZnS shell growth.In particular,CuInZnS@ZnS QDs possess a significantly long emission lifetime(up to 750 ns),high PLQY(up to 85%),and excellent crystallinity.Their spectroscopic evolution is well validated by Cu-deficient related intragap emission model.By controlling the stoichiometric ratio of Cu/In,two distinct Cu-deficient related emission pathways are established based on the differing oxidation states of Cu defects.Therefore,this work provides deeper insights for fabricating high luminescent ternary or quaternary-alloyed QDs.
文摘Smart batteries play a key role in upgrading energy storage systems.However,they require a well-balanced integration of material structure,functional properties,and electrochemical performance,and their development is limited by conventional material systems in terms of energy density,response time,and functional integration.Carbon materials have emerged as a key solution for overcoming these problems due to their structural adjustability and multifunctional compatibility.Strategies for improving their electrochemical performance by changing the pore structure and interlayer spacing,as well as chemical functionalization,and composite design are analyzed,and their impact on improving the specific capacity and cycling stability of batteries is demonstrated.The unique advantages of carbon materials in realizing smart functions such as power supply,real-time monitoring and energy management in smart batteries are also discussed.Based on current progress in related fields,the prospects for the use of carbon materials in smart batteries are evaluated.
文摘To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the glass-metal hetero-bonding process.This study focuses on the analysis and experimental re-search of the bonding layer in the integrated structure.By optimizing the structural configuration and select-ing suitable bonding processes,the reliability of the telescope system is enhanced.The research indicates that using J-133 adhesive achieves the best performance,with a bonding layer thickness of 0.30 mm and a metal substrate surface roughness of Ra 0.8.These findings significantly enhance the reliability of the optical sys-tem while minimizing potential risks.
文摘To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
