The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversari...The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.展开更多
In this paper,we give improved error estimates for linearized and nonlinear CrankNicolson type finite difference schemes of Ginzburg-Landau equation in two dimensions.For linearized Crank-Nicolson scheme,we use mathem...In this paper,we give improved error estimates for linearized and nonlinear CrankNicolson type finite difference schemes of Ginzburg-Landau equation in two dimensions.For linearized Crank-Nicolson scheme,we use mathematical induction to get unconditional error estimates in discrete L^(2)and H^(1)norm.However,it is not applicable for the nonlinear scheme.Thus,based on a‘cut-off’function and energy analysis method,we get unconditional L^(2)and H^(1)error estimates for the nonlinear scheme,as well as boundedness of numerical solutions.In addition,if the assumption for exact solutions is improved compared to before,unconditional and optimal pointwise error estimates can be obtained by energy analysis method and several Sobolev inequalities.Finally,some numerical examples are given to verify our theoretical analysis.展开更多
The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an over...The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.展开更多
A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface...A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface area of 427 m^(2)·g^(-1)and rich surface active sites,which help restrain polysulfides(LiPSs)through good physi-cal and chemical adsorption,while simultaneously accelerating the nucleation and dissolution kinetics of Li_(2)S,effec-tively suppressing the shuttle effect.The assembled lithium-sulfur batteries(LSBs)employing the PVS-based inter-layer delivered a high initial discharge capacity of 1386 mAh·g^(-1)at 0.1C(167.5 mAh·g^(-1)),long-term cycling stabil-ity,and good rate property.展开更多
In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures.MRI is particularly effective for detecting soft tissue...In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures.MRI is particularly effective for detecting soft tissue anomalies.Traditionally,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of data.To address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI scans.This manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning methods.There are three stages for learning;in the first stage,the whole dataset is used to learn the features.In the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented dataset.This method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for analysis.Various hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning process.HWBA-dataset registers maximum classification performance.We evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major ch...Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major challenge for their practical application.The design of battery separators has become a key aspect in addressing the challenge.MXenes,a promising two-dimensional(2D)material,offer exceptional conductivity,large surface area,high mechanical strength,and active sites for surface reactions.When assembled into layered films,MXenes form highly tunable two-dimensional channels ranging from a few angstroms to over 1 nm.These nanoconfined channels are instrumental in facilitating lithium-ion transport while effectively impeding the shuttle effect of LiPSs,which are essential for improving the specific capacity and cyclic stability of Li-S batteries.Substantial progress has been made in developing MXenes-based separators for Li-S batteries,yet there remains a research gap in summarizing advancements from the perspective of interlayer engineering.This entails maintaining the 2D nanochannels of layered MXenes-based separators while modulating the physicochemical environment within the MXenes interlayers through targeted modifications.This review highlights advancements in in situ modification of MXenes and their integration with 0D,1D,and 2D materials to construct laminated nanocomposite separators for Li-S batteries.The future development directions of MXenes-based materials in Li-S energy storage devices are also outlined,to drive further advancements in MXenes for Li-S battery separators.展开更多
Assessing the impact of anthropogenic volatile organic compounds(VOCs)on ozone(O_(3))formation is vital for themanagement of emission reduction and pollution control.Continuousmeasurement of O_(3)and the major precurs...Assessing the impact of anthropogenic volatile organic compounds(VOCs)on ozone(O_(3))formation is vital for themanagement of emission reduction and pollution control.Continuousmeasurement of O_(3)and the major precursorswas conducted in a typical light industrial city in the YRD region from 1 May to 25 July in 2021.Alkanes were the most abundant VOC group,contributing to 55.0%of TVOCs concentration(56.43±21.10 ppb).OVOCs,aromatics,halides,alkenes,and alkynes contributed 18.7%,9.6%,9.3%,5.2%and 1.9%,respectively.The observational site shifted from a typical VOC control regime to a mixed regime from May to July,which can be explained by the significant increase of RO_(x)production,resulting in the transition of environment from NOx saturation to radical saturation with respect to O_(3)production.The optimal O_(3)control strategy should be dynamically changed depending on the transition of control regime.Under NOx saturation condition,minimizing the proportion of NOx in reduction could lead to better achievement of O_(3)alleviation.Under mixed control regime,the cut percentage gets the top priority for the effectiveness of O_(3)control.Five VOCs sources were identified:temperature dependent source(28.1%),vehicular exhausts(19.9%),petrochemical industries(7.2%),solvent&gasoline usage(32.3%)and manufacturing industries(12.6%).The increase of temperature and radiation would enhance the evaporation related VOC emissions,resulting in the increase of VOC concentration and the change of RO_(x)circulation.Our results highlight determination of the optimal control strategies for O_(3)pollution in a typical YRD industrial city.展开更多
The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the rel...The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.展开更多
In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy sys...In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.展开更多
In this paper,we study the optimal investment problem of an insurer whose surplus process follows the diffusion approximation of the classical Cramer-Lundberg model.Investment in the foreign markets is allowed,and the...In this paper,we study the optimal investment problem of an insurer whose surplus process follows the diffusion approximation of the classical Cramer-Lundberg model.Investment in the foreign markets is allowed,and therefore,the foreign exchange rate model is incorporated.Under the allowing of selling and borrowing,the problem of maximizing the expected exponential utility of terminal wealth is studied.By solving the corresponding Hamilton-Jacobi-Bellman equations,the optimal investment strategies and value functions are obtained.Finally,numerical analysis is presented.展开更多
Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades ...Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades and continue to face persistent challenges related to light transmission,biosafety,and visual appearance.Here,we report the discovery of two-dimensional(2D)TiO_(2),characterized by a micro-sized lateral dimension(~1.6μm)and atomic-scale thickness,which fundamentally resolves these long-standing issues.The 2D structure enables exceptional light management,achieving 80%visible light transparency—rendering it nearly invisible on the skin—while maintaining UV-blocking performance comparable to unmodified rutile TiO_(2)nanoparticles.Its larger lateral size results in a two-orders-of-magnitude reduction in skin penetration(0.96 w/w%),significantly enhancing biosafety.Moreover,the unique layered architecture inherently suppresses the generation of reactive oxygen species(ROS)under sunlight exposure,reducing the ROS generation rate by 50-fold compared to traditional TiO_(2)nanoparticles.Through precise metal element modulation,we further developed the first customizable sunscreen material capable of tuning UV protection ranges and automatically matching diverse skin tones.The 2D TiO_(2)offers a potentially transformative approach to modern sunscreen formulation,combining superior UV protection,enhanced safety and a natural appearance.展开更多
Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high ef...Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high efficiency and reliability.However,the ambiguity surrounding the output flow characteristics of individual two-dimensional pumps poses a significant challenge in achieving precise closed-loop control of the EHA positions.To address this issue,this study established a comprehensive numerical model that included gap leakage to analyze the impact of leakage on the output flow characteristics of a two-dimensional piston pump.The validity of the numerical analysis was indirectly confirmed through meticulous measurements of the leakage and volumetric efficiency,ensuring robust results.The research findings indicated that,at lower pump speeds,leakage significantly affected the output flow rate,leading to potential inefficiencies in the system.Conversely,at higher rotational speeds,the impact of leakage was less pronounced,implying that the influence of leakage on the pump outlet flow must be carefully considered and managed for EHAs to perform position servo control.Additionally,the research demonstrates that two-dimensional motion does not have a unique or additional effect on pump leakage,thus simplifying the design considerations.Finally,the study concluded that maintaining an oil-filled leakage environment is beneficial because it helps reduce the impact of leakage and enhances the overall volumetric efficiency of the pump system.展开更多
Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of...Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of catalytical materials.In 2019,we discussed the development trend of this field,and wrote a roadmap on this topic in Chinese Chemical Letters(30(2019)2065-2088).Nowadays,we discuss it again from a new viewpoint along this road.In this paper,several subtopics are discussed,e.g.,photocatalysis based on titanium dioxide,violet phosphorus,graphitic carbon and covalent organic frameworks,electrocatalysts based on carbon,metal-and covalent-organic framework.Finally,we hope that this roadmap can enrich the development of two-dimensional materials in environmental catalysis with novel understanding,and give useful inspiration to explore new catalysts for practical applications.展开更多
It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament ch...It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.展开更多
Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus o...Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus on one unique quantum phase induced by the electron-hole interaction in two-dimensional systems,known as“exciton insulators”(EIs).Although this phase of matter has been studied for more than half a century,suitable platforms for its stable realization remain scarce.We provide an overview of the strategies to realize EIs in accessible materials and structures,along with a discussion on some unique properties of EIs stemming from the band structures of these materials.Additionally,signatures in experiments to distinguish EIs are discussed.展开更多
Restructuring of power market not only introduces competition but also brings complexity which increases overloading of Transmission Lines(TL).To obviate this complexity,this paper aims to mitigate the overloading and...Restructuring of power market not only introduces competition but also brings complexity which increases overloading of Transmission Lines(TL).To obviate this complexity,this paper aims to mitigate the overloading and estimate the optimal location of Static Synchronous Compensator(STATCOM) by reducing congestion for a deregulated power system.The proposed method is based on the use of Locational Marginal Price(LMP) difference technique and congestion cost.LMPs are obtained as a by-product of Optimal Power Flow(OPF),whereas Congestion Cost(CC) is a function of difference in LMP and power flows.The effiectiveness of this approach is demonstrated by reducing the CC and solution space which can identify the TLs more suitable for placement of STATCOM.Importantly,total real power loss,reactive power loss and total CC are the three main objective functions in this optimization process.The process is implemented by developing an IEEE-69 bus test system which verifies and validates the effectiveness of proposed optimization technique.Additionally,a comparative analysis is enumerated by implementing two optimization techniques:Flower Pollination Algorithm(FPA) and Particle Swarm Optimization(PSO).The comparative analysis is sufficient to demonstrate the superiority of FPA technique over PSO technique in estimating an optimal placement of a STATCOM.The results from the load-flow analysis illustrate the reduction in CC,total real and reactive power loss using FPA technique compared to PSO technique.Overall,satisfactory results are obtained without using complex calculations which verify the effectiveness of optimization techniques.展开更多
Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly effi...Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.展开更多
The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges h...The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges hinder its widespread deployment.Ultrathin two-dimensional(2D)materials,with their atomically exposed surfaces,tunable electronic structures,and defect-engineering capabilities,present unique opportunities for next-generation electrocatalysts.This review provides an integrated overview of ultrathin 2D electrocatalysts,discussing their structural diversity,synthetic routes,structure-activity relationships,and mechanistic understanding in water electrolysis processes.Special focus is placed on the translation of 2D materials from laboratory research to practical device implementation,emphasizing challenges such as scalable fabrication,interfacial engineering,and operational durability in realistic electrolyzer environments.The role of advanced characterization techniques in capturing dynamic structural changes and active site evolution is discussed.Finally,we outline future research directions,emphasizing the synergy of machine learning-driven materials discovery,advanced operando characterization,and scalable system integration to accelerate the industrial translation of 2D electrocatalysts for green hydrogen production.展开更多
The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACT...The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.展开更多
基金supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2020MA092)the Innovation Project for Graduate Students of Ludong University(Grant No.IPGS2024-048).
文摘The diffusion trajectory of a Brownian particle passing over the saddle point of a two-dimensional quadratic potential energy surface is tracked in detail according to the deep learning strategies.Generative adversarial networks(GANs)emanating in the category of machine learning(ML)frameworks are used to generate and assess the rationality of the data.While their optimization is based on the long short-term memory(LSTM)strategies.In addition to drawing a heat map,the optimal path of two-dimensional(2D)diffusion is simultaneously demonstrated in a stereoscopic space.The results of our simulation are completely consistent with the previous theoretical predictions.
基金Supported by the National Natural Science Foundation of China(Grant No.11571181)the Research Start-Up Foundation of Nantong University(Grant No.135423602051).
文摘In this paper,we give improved error estimates for linearized and nonlinear CrankNicolson type finite difference schemes of Ginzburg-Landau equation in two dimensions.For linearized Crank-Nicolson scheme,we use mathematical induction to get unconditional error estimates in discrete L^(2)and H^(1)norm.However,it is not applicable for the nonlinear scheme.Thus,based on a‘cut-off’function and energy analysis method,we get unconditional L^(2)and H^(1)error estimates for the nonlinear scheme,as well as boundedness of numerical solutions.In addition,if the assumption for exact solutions is improved compared to before,unconditional and optimal pointwise error estimates can be obtained by energy analysis method and several Sobolev inequalities.Finally,some numerical examples are given to verify our theoretical analysis.
基金the support from the National Natural Science Foundation of China(22272004,62272041)the Fundamental Research Funds for the Central Universities(YWF-22-L-1256)+1 种基金the National Key R&D Program of China(2023YFC3402600)the Beijing Institute of Technology Research Fund Program for Young Scholars(No.1870011182126)。
文摘The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.
文摘A functional interlayer based on two-dimensional(2D)porous modified vermiculite nanosheets(PVS)was obtained by acid-etching vermiculite nanosheets.The as-obtained 2D porous nanosheets exhibited a high specific surface area of 427 m^(2)·g^(-1)and rich surface active sites,which help restrain polysulfides(LiPSs)through good physi-cal and chemical adsorption,while simultaneously accelerating the nucleation and dissolution kinetics of Li_(2)S,effec-tively suppressing the shuttle effect.The assembled lithium-sulfur batteries(LSBs)employing the PVS-based inter-layer delivered a high initial discharge capacity of 1386 mAh·g^(-1)at 0.1C(167.5 mAh·g^(-1)),long-term cycling stabil-ity,and good rate property.
文摘In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures.MRI is particularly effective for detecting soft tissue anomalies.Traditionally,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of data.To address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI scans.This manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning methods.There are three stages for learning;in the first stage,the whole dataset is used to learn the features.In the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented dataset.This method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for analysis.Various hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning process.HWBA-dataset registers maximum classification performance.We evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
基金supported by Beijing Natural Science Foundation(Nos.2232037 and 2242035)the National Natural Science Foundation of China(Nos.22005012,22105012 and 51803183)+1 种基金Chunhui Plan Cooperative Project of Ministry of Education(No.202201298)the China Postdoctoral Science Foundation Funded Project(No.2023M733520).
文摘Lithium-sulfur(Li-S)batteries with high energy density and capacity have garnered significant research attention among various energy storage devices.However,the shuttle effect of polysulfides(LiPSs)remains a major challenge for their practical application.The design of battery separators has become a key aspect in addressing the challenge.MXenes,a promising two-dimensional(2D)material,offer exceptional conductivity,large surface area,high mechanical strength,and active sites for surface reactions.When assembled into layered films,MXenes form highly tunable two-dimensional channels ranging from a few angstroms to over 1 nm.These nanoconfined channels are instrumental in facilitating lithium-ion transport while effectively impeding the shuttle effect of LiPSs,which are essential for improving the specific capacity and cyclic stability of Li-S batteries.Substantial progress has been made in developing MXenes-based separators for Li-S batteries,yet there remains a research gap in summarizing advancements from the perspective of interlayer engineering.This entails maintaining the 2D nanochannels of layered MXenes-based separators while modulating the physicochemical environment within the MXenes interlayers through targeted modifications.This review highlights advancements in in situ modification of MXenes and their integration with 0D,1D,and 2D materials to construct laminated nanocomposite separators for Li-S batteries.The future development directions of MXenes-based materials in Li-S energy storage devices are also outlined,to drive further advancements in MXenes for Li-S battery separators.
基金supported by the National Natural Science Foundation of China(Nos.42005086,91844301,and 41805100)the National Key Research and Development Programof China(No.2022YFC3703500)+2 种基金China Postdoctoral Science Foundation(No.2023M733028)the Key Research and Development Program of Zhejiang Province(Nos.2021C03165 and 2022C03084)the Ecological and Environmental Scientific Research and Achievement Promotion Project of Zhejiang Province(No.2020HT0048).
文摘Assessing the impact of anthropogenic volatile organic compounds(VOCs)on ozone(O_(3))formation is vital for themanagement of emission reduction and pollution control.Continuousmeasurement of O_(3)and the major precursorswas conducted in a typical light industrial city in the YRD region from 1 May to 25 July in 2021.Alkanes were the most abundant VOC group,contributing to 55.0%of TVOCs concentration(56.43±21.10 ppb).OVOCs,aromatics,halides,alkenes,and alkynes contributed 18.7%,9.6%,9.3%,5.2%and 1.9%,respectively.The observational site shifted from a typical VOC control regime to a mixed regime from May to July,which can be explained by the significant increase of RO_(x)production,resulting in the transition of environment from NOx saturation to radical saturation with respect to O_(3)production.The optimal O_(3)control strategy should be dynamically changed depending on the transition of control regime.Under NOx saturation condition,minimizing the proportion of NOx in reduction could lead to better achievement of O_(3)alleviation.Under mixed control regime,the cut percentage gets the top priority for the effectiveness of O_(3)control.Five VOCs sources were identified:temperature dependent source(28.1%),vehicular exhausts(19.9%),petrochemical industries(7.2%),solvent&gasoline usage(32.3%)and manufacturing industries(12.6%).The increase of temperature and radiation would enhance the evaporation related VOC emissions,resulting in the increase of VOC concentration and the change of RO_(x)circulation.Our results highlight determination of the optimal control strategies for O_(3)pollution in a typical YRD industrial city.
基金supported by the Education and Teaching Research Project of Universities in Fujian Province(FBJY20230167).
文摘The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.
基金supported by the Central Government Guides Local Science and Technology Development Fund Project(2023ZY0020)Key R&D and Achievement Transformation Project in InnerMongolia Autonomous Region(2022YFHH0019)+3 种基金the Fundamental Research Funds for Inner Mongolia University of Science&Technology(2022053)Natural Science Foundation of Inner Mongolia(2022LHQN05002)National Natural Science Foundation of China(52067018)Metallurgical Engineering First-Class Discipline Construction Project in Inner Mongolia University of Science and Technology,Control Science and Engineering Quality Improvement and Cultivation Discipline Project in Inner Mongolia University of Science and Technology。
文摘In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.
基金supported by the National Natural Science Foundation of China(Grant No.12301603).
文摘In this paper,we study the optimal investment problem of an insurer whose surplus process follows the diffusion approximation of the classical Cramer-Lundberg model.Investment in the foreign markets is allowed,and therefore,the foreign exchange rate model is incorporated.Under the allowing of selling and borrowing,the problem of maximizing the expected exponential utility of terminal wealth is studied.By solving the corresponding Hamilton-Jacobi-Bellman equations,the optimal investment strategies and value functions are obtained.Finally,numerical analysis is presented.
基金supported by the National Key Research and Development Project(No.2019YFA0705403)the National Natural Science Foundation of China(No.T2293693,52273311)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2020B0301030002)and the Shenzhen Basic Research Project(Nos.WDZC20200824091903001,JSGG20220831105402004,JCYJ20220818100806014)Shenzhen Major Science and Technology Projects(Nos.KCXFZ20240903094013018,KCXFZ20240903094203005)。
文摘Titanium dioxide(TiO_(2))has been an important protective ingredient in mineral-based sunscreens since the 1990s.However,traditional TiO_(2)nanoparticle formulations have seen little improvement over the past decades and continue to face persistent challenges related to light transmission,biosafety,and visual appearance.Here,we report the discovery of two-dimensional(2D)TiO_(2),characterized by a micro-sized lateral dimension(~1.6μm)and atomic-scale thickness,which fundamentally resolves these long-standing issues.The 2D structure enables exceptional light management,achieving 80%visible light transparency—rendering it nearly invisible on the skin—while maintaining UV-blocking performance comparable to unmodified rutile TiO_(2)nanoparticles.Its larger lateral size results in a two-orders-of-magnitude reduction in skin penetration(0.96 w/w%),significantly enhancing biosafety.Moreover,the unique layered architecture inherently suppresses the generation of reactive oxygen species(ROS)under sunlight exposure,reducing the ROS generation rate by 50-fold compared to traditional TiO_(2)nanoparticles.Through precise metal element modulation,we further developed the first customizable sunscreen material capable of tuning UV protection ranges and automatically matching diverse skin tones.The 2D TiO_(2)offers a potentially transformative approach to modern sunscreen formulation,combining superior UV protection,enhanced safety and a natural appearance.
基金Supported by National Natural Science Foundation of China(Grant No.52205072).
文摘Owing to their rolling friction,two-dimensional piston pumps are highly suitable as power components for electro-hydrostatic actuators(EHAs).These pumps are particularly advantageous for applications requiring high efficiency and reliability.However,the ambiguity surrounding the output flow characteristics of individual two-dimensional pumps poses a significant challenge in achieving precise closed-loop control of the EHA positions.To address this issue,this study established a comprehensive numerical model that included gap leakage to analyze the impact of leakage on the output flow characteristics of a two-dimensional piston pump.The validity of the numerical analysis was indirectly confirmed through meticulous measurements of the leakage and volumetric efficiency,ensuring robust results.The research findings indicated that,at lower pump speeds,leakage significantly affected the output flow rate,leading to potential inefficiencies in the system.Conversely,at higher rotational speeds,the impact of leakage was less pronounced,implying that the influence of leakage on the pump outlet flow must be carefully considered and managed for EHAs to perform position servo control.Additionally,the research demonstrates that two-dimensional motion does not have a unique or additional effect on pump leakage,thus simplifying the design considerations.Finally,the study concluded that maintaining an oil-filled leakage environment is beneficial because it helps reduce the impact of leakage and enhances the overall volumetric efficiency of the pump system.
基金supported by the National Natural Science Foundation of China(Nos.52272290,21972030,52073119,and 52373210)the Natural Science Foundation of Jilin Province(No.20230101029JC)+1 种基金the Fundamental Research Program of Shanxi Province(No.202303021212159)the Monash University Malaysia–ASEAN grant(No.ASE-000010)。
文摘Environmental catalysis has been considered one of the important research topics.Some technologies(e.g.,photocatalysis and electrocatalysis)have been intensively developed with the advance of synthetic technologies of catalytical materials.In 2019,we discussed the development trend of this field,and wrote a roadmap on this topic in Chinese Chemical Letters(30(2019)2065-2088).Nowadays,we discuss it again from a new viewpoint along this road.In this paper,several subtopics are discussed,e.g.,photocatalysis based on titanium dioxide,violet phosphorus,graphitic carbon and covalent organic frameworks,electrocatalysts based on carbon,metal-and covalent-organic framework.Finally,we hope that this roadmap can enrich the development of two-dimensional materials in environmental catalysis with novel understanding,and give useful inspiration to explore new catalysts for practical applications.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.U1809210)the International Science Technology Cooperation Program of China(Grant No.2014DFR51160)+3 种基金the One Belt and One Road International Cooperation Project from the Key Research and Development Program of Zhejiang Province,China(Grant No.2018C04021)the National Natural Science Foundation of China(Grant Nos.50972129,50602039,and 52102052)the Fund from Institute of Wenzhou,Zhejiang University(Grant Nos.XMGL-CX-202305 and XMGLKJZX-202307)the Project from Tanghe Scientific&Technology Company(Grant No.KYY-HX-20230024).
文摘It is a key challenge to prepare two-dimensional diamond(2D-diamond).Herein,we develop a method for synthesizing 2D-diamond by depositing monodisperse tantalum(Ta)atoms onto graphene substrates using a hot-filament chemical vapor deposition setup,followed by annealing treatment under different temperatures at ambient pressure.The results indicate that when the annealing temperature increases from 700℃ to 1000℃,the size of the 2D-diamond found in the samples gradually increases from close to 20 nm to around 30 nm.Meanwhile,the size and number of amorphous carbon spheres and Ta-containing compounds between the graphene layers gradually increase.As the annealing temperature continues to rise to 1100℃,a significant aggregation of Ta-containing compounds is observed in the samples,with no diamond structure detected.This further confirms that monodisperse Ta atoms play a key role in graphene phase transition into 2D-diamond.This study provides a novel method for the ambient-pressure phase transition of graphene into 2D-diamond.
基金supported by the National Key Research&Development Program of China(Grant Nos.2022YFA1403500 and 2021YFA1400500)the National Science Foundation of China(Grant Nos.62321004,12234001,and 12474215)+1 种基金supported by New Cornerstone Science Foundationa fellowship and a CRF award from the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant Nos.HKUST SRFS2324-6S01 and C7037-22GF)。
文摘Electron-hole interactions play a crucial role in determining the optoelectronic properties of materials,and in lowdimensional systems this is especially true due to the decrease of screening.In this review,we focus on one unique quantum phase induced by the electron-hole interaction in two-dimensional systems,known as“exciton insulators”(EIs).Although this phase of matter has been studied for more than half a century,suitable platforms for its stable realization remain scarce.We provide an overview of the strategies to realize EIs in accessible materials and structures,along with a discussion on some unique properties of EIs stemming from the band structures of these materials.Additionally,signatures in experiments to distinguish EIs are discussed.
文摘Restructuring of power market not only introduces competition but also brings complexity which increases overloading of Transmission Lines(TL).To obviate this complexity,this paper aims to mitigate the overloading and estimate the optimal location of Static Synchronous Compensator(STATCOM) by reducing congestion for a deregulated power system.The proposed method is based on the use of Locational Marginal Price(LMP) difference technique and congestion cost.LMPs are obtained as a by-product of Optimal Power Flow(OPF),whereas Congestion Cost(CC) is a function of difference in LMP and power flows.The effiectiveness of this approach is demonstrated by reducing the CC and solution space which can identify the TLs more suitable for placement of STATCOM.Importantly,total real power loss,reactive power loss and total CC are the three main objective functions in this optimization process.The process is implemented by developing an IEEE-69 bus test system which verifies and validates the effectiveness of proposed optimization technique.Additionally,a comparative analysis is enumerated by implementing two optimization techniques:Flower Pollination Algorithm(FPA) and Particle Swarm Optimization(PSO).The comparative analysis is sufficient to demonstrate the superiority of FPA technique over PSO technique in estimating an optimal placement of a STATCOM.The results from the load-flow analysis illustrate the reduction in CC,total real and reactive power loss using FPA technique compared to PSO technique.Overall,satisfactory results are obtained without using complex calculations which verify the effectiveness of optimization techniques.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.41930971,42330111,and 42405061)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(Earth Lab).
文摘Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.
文摘The pursuit of sustainable hydrogen production has positioned water electrolysis as a cornerstone technology for global carbon neutrality.However,sluggish kinetics,catalyst scarcity,and system integration challenges hinder its widespread deployment.Ultrathin two-dimensional(2D)materials,with their atomically exposed surfaces,tunable electronic structures,and defect-engineering capabilities,present unique opportunities for next-generation electrocatalysts.This review provides an integrated overview of ultrathin 2D electrocatalysts,discussing their structural diversity,synthetic routes,structure-activity relationships,and mechanistic understanding in water electrolysis processes.Special focus is placed on the translation of 2D materials from laboratory research to practical device implementation,emphasizing challenges such as scalable fabrication,interfacial engineering,and operational durability in realistic electrolyzer environments.The role of advanced characterization techniques in capturing dynamic structural changes and active site evolution is discussed.Finally,we outline future research directions,emphasizing the synergy of machine learning-driven materials discovery,advanced operando characterization,and scalable system integration to accelerate the industrial translation of 2D electrocatalysts for green hydrogen production.
文摘The Sine and Wormhole Energy Whale Optimization Algorithm(SWEWOA)represents an advanced solution method for resolving Optimal Power Flow(OPF)problems in power systems equipped with Flexible AC Transmission System(FACTS)devices which include Thyristor-Controlled Series Compensator(TCSC),Thyristor-Controlled Phase Shifter(TCPS),and Static Var Compensator(SVC).SWEWOA expands Whale Optimization Algorithm(WOA)through the integration of sine and wormhole energy features thus improving exploration and exploitation capabilities for efficient convergence in complex non-linear OPF problems.A performance evaluation of SWEWOA takes place on the IEEE-30 bus test system through static and dynamic loading scenarios where it demonstrates better results than five contemporary algorithms:Adaptive Chaotic WOA(ACWOA),WOA,Chaotic WOA(CWOA),Sine Cosine Algorithm Differential Evolution(SCADE),and Hybrid Grey Wolf Optimization(HGWO).The research shows that SWEWOA delivers superior generation cost reduction than other algorithms by reaching a minimum of 0.9%better performance.SWEWOA demonstrates superior power loss performance by achieving(P_(loss,min))at the lowest level compared to all other tested algorithms which leads to better system energy efficiency.The dynamic loading performance of SWEWOA leads to a 4.38%reduction in gross costs which proves its capability to handle different operating conditions.The algorithm achieves top performance in Friedman Rank Test(FRT)assessments through multiple performance metrics which verifies its consistent reliability and strong stability during changing power demands.The repeated simulations show that SWEWOA generates mean costs(C_(gen,min))and mean power loss values(P_(loss,min))with small deviations which indicate its capability to maintain cost-effective solutions in each simulation run.SWEWOA demonstrates great potential as an advanced optimization solution for power system operations through the results presented in this study.
