As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.A...The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.展开更多
The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The e...The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.展开更多
This paper discusses the signal decomposition method using the extreme-lifting scheme and two two-dimensional decomposition schemes: separable one-dimensional scheme and two-dimensional scheme with quincunx sampling. ...This paper discusses the signal decomposition method using the extreme-lifting scheme and two two-dimensional decomposition schemes: separable one-dimensional scheme and two-dimensional scheme with quincunx sampling. The structure of the relation "～" between Ex and Ey of these two schemes is symmetrical and both these two schemes have shortcomings)An unsymmetrical scheme of the extreme-lifting scheme is proposed in this paper, which canbe directly used to decompose two-dimensional image and can get better decomposition result than the two schemes with little computation cost.展开更多
This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this...This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this purpose, a semi discrete variational format relative time and a fully discrete FVE format for the 2D hyperbolic equations are built, and a set of snapshots from the very few FVE solutions are extracted on the first very short time interval. Then, the POD basis from the snapshots is formulated, and the reduced-order POD extrapolating FVE format containing very few degrees of freedom but holding sufficiently high accuracy is built. Next, the error estimates of the reduced-order solutions and the algorithm procedure for solving the reduced-order for- mat are furnished. Finally, a numerical example is shown to confirm the correctness of theoretical conclusions. This means that the format is efficient and feasible to solve the 2D hyperbolic equations.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
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition wi...Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.展开更多
Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the origin...Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.展开更多
Fluoride-based electrolyte exhibits extraordinarily high oxidative stability in high-voltage lithium metal batteries(h-LMBs) due to the inherent low highest occupied molecular orbital(HOMO) of fiuorinated solvents. Ho...Fluoride-based electrolyte exhibits extraordinarily high oxidative stability in high-voltage lithium metal batteries(h-LMBs) due to the inherent low highest occupied molecular orbital(HOMO) of fiuorinated solvents. However, such fascinating properties do not bring long-term cyclability of h-LMBs. One of critical challenges is the interface instability in contacting with the Li metal anode, as fiuorinated solvents are highly susceptible to exceptionally reductive metallic Li attributed to its low lowest unoccupied molecular orbital(LUMO), which leads to significant consumption of the fiuorinated components upon cycling.Herein, attenuating reductive decomposition of fiuorinated electrolytes is proposed to circumvent rapid electrolyte consumption. Specifically, the vinylene carbonate(VC) is selected to tame the reduction decomposition by preferentially forming protective layer on the Li anode. This work, experimentally and computationally, demonstrates the importance of pre-passivation of Li metal anodes at high voltage to attenuate the decomposition of fiuoroethylene carbonate(FEC). It is expected to enrich the understanding of how VC attenuate the reactivity of FEC, thereby extending the cycle life of fiuorinated electrolytes in high-voltage Li-metal batteries.展开更多
The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.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
This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This m...This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.展开更多
In this paper,we prove that L(K_(x,y))(λ),theλ-fold line graph of the complete bipartite graph Ka,y,has a C_(6)-decomposition if and only if ry≥6,λxy(c+y-2)=0(mod 12)and(x+y)=0(mod 2),where x,y are nonnegative int...In this paper,we prove that L(K_(x,y))(λ),theλ-fold line graph of the complete bipartite graph Ka,y,has a C_(6)-decomposition if and only if ry≥6,λxy(c+y-2)=0(mod 12)and(x+y)=0(mod 2),where x,y are nonnegative integers and(x,y)≠(2,4)or(2,5).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
To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explo...To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.展开更多
In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to ...In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to evaluate the effectiveness of exteriorwall coat-ings with ozone decomposition catalysts for ozone removal in practical applications.ANSYS 2020R1 software was first used for simulation and analysis of ozone concentration and flow fields to investigate the decomposition boundary of these wall coatings.The results show that the exterior wall coatings with manganese-based catalysts can effectively reduce the ozone concentration near the wall coating.The ozone decomposition efficiency is nega-tively correlated with the distance fromthe coating and the decomposition boundary range is around 18 m.The decomposition boundary will increase with the increase of tempera-ture,and decrease with the increase of the wind speed and the relative humidity.These results underscore the viability of using exterior wall coatings with catalysts for controlling ozone pollution in atmospheric environments.This approach presents a promising avenue for addressing ozone pollution through self-purifying materials on building external wall.展开更多
In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrabilit...In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.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
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
基金financially supported by the National Natural Science Foundation of China(Nos.52034002 and U2202254)the Fundamental Research Funds for the Central Universities,China(No.FRF-TT-19-001)。
文摘The sulfation and decomposition process has proven effective in selectively extracting lithium from lepidolite.It is essential to clarify the thermochemical behavior and kinetic parameters of decomposition reactions.Accordingly,comprehensive kinetic study by employing thermalgravimetric analysis at various heating rates was presented in this paper.Two main weight loss regions were observed during heating.The initial region corresponded to the dehydration of crystal water,whereas the subsequent region with overlapping peaks involved complex decomposition reactions.The overlapping peaks were separated into two individual reaction peaks and the activation energy of each peak was calculated using isoconversional kinetics methods.The activation energy of peak 1 exhibited a continual increase as the reaction conversion progressed,while that of peak 2 steadily decreased.The optimal kinetic models,identified as belonging to the random nucleation and subsequent growth category,provided valuable insights into the mechanism of the decomposition reactions.Furthermore,the adjustment factor was introduced to reconstruct the kinetic mechanism models,and the reconstructed models described the kinetic mechanism model more accurately for the decomposition reactions.This study enhanced the understanding of the thermochemical behavior and kinetic parameters of the lepidolite sulfation product decomposition reactions,further providing theoretical basis for promoting the selective extraction of lithium.
基金supported by National Natural Science Foundation of China under Grant No.60872065Open Foundation of State Key Laboratory for Novel Software Technology at Nanjing University under Grant No.KFKT2010B17
文摘The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.
文摘This paper discusses the signal decomposition method using the extreme-lifting scheme and two two-dimensional decomposition schemes: separable one-dimensional scheme and two-dimensional scheme with quincunx sampling. The structure of the relation "～" between Ex and Ey of these two schemes is symmetrical and both these two schemes have shortcomings)An unsymmetrical scheme of the extreme-lifting scheme is proposed in this paper, which canbe directly used to decompose two-dimensional image and can get better decomposition result than the two schemes with little computation cost.
基金Project supported by the National Natural Science Foundation of China(Nos.11271127 and11671106)
文摘This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this purpose, a semi discrete variational format relative time and a fully discrete FVE format for the 2D hyperbolic equations are built, and a set of snapshots from the very few FVE solutions are extracted on the first very short time interval. Then, the POD basis from the snapshots is formulated, and the reduced-order POD extrapolating FVE format containing very few degrees of freedom but holding sufficiently high accuracy is built. Next, the error estimates of the reduced-order solutions and the algorithm procedure for solving the reduced-order for- mat are furnished. Finally, a numerical example is shown to confirm the correctness of theoretical conclusions. This means that the format is efficient and feasible to solve the 2D hyperbolic equations.
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.
基金supported by Ningbo Natural Science Foundation(No.2023J059)Ningbo Commonweal Programme Key Project(No.2023S038)Guangxi Key Research and Development Programme(No.GuikeAB21220063).
文摘Machine-learning is a robust technique for understanding pollution characteristics of surface ozone,which are at high levels in urban China.This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to investigate ozone dynamics and formation regimes in a coastal area of China.During the period of 2017–2022,significant inter-annual fluctuations emerged,with peaks in mid-2017 attributed to volatile organic compounds(VOCs),and in late-2019 influenced by air temperature.Multifaceted periodicities(daily,weekly,holiday,and yearly)in ozone were revealed,elucidating substantial influences of daily and yearly components on ozone periodicity.A VOC-sensitive ozone formation regime was identified,characterized by lower VOCs/NO_(x) ratios(average=0.88)and significant positive correlations between ozone and VOCs.This interplay manifested in elevated ozone duringweekends,holidays,and pandemic lockdowns.Key variables influencing ozone across diverse timescaleswere uncovered,with solar radiation and temperature driving daily and yearly ozone variations,respectively.Precursor substances,particularly VOCs,significantly shaped weekly/holiday patterns and long-term trends of ozone.Specifically,acetone,ethane,hexanal,and toluene had a notable impact on the multi-year ozone trend,emphasizing the urgency of VOC regulation.Furthermore,our observations indicated that NO_(x) primarily drived the stochastic variations in ozone,a distinguishing characteristic of regions with heavy traffic.This research provides novel insights into ozone dynamics in coastal urban areas and highlights the importance of integrating statistical and machinelearning methods in atmospheric pollution studies,with implications for targeted mitigation strategies beyond this specific region and pollutant.
基金supported in part by the Interdisciplinary Project of Dalian University(DLUXK-2023-ZD-001).
文摘Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy consumption.Series decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time series.However,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between components.These problems make it difficult to analyze the intricate temporal variations of real-world time series.In this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between variables.Two backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend components.Mamba with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.
基金supported by the National Natural Science Foundation of China (Nos. 22379121, 62005216)Basic Public Welfare Research Program of Zhejiang (No. LQ22F050013)+1 种基金Zhejiang Province Key Laboratory of Flexible Electronics Open Fund (2023FE005)Shenzhen Foundation Research Program (No. JCYJ20220530112812028)。
文摘Fluoride-based electrolyte exhibits extraordinarily high oxidative stability in high-voltage lithium metal batteries(h-LMBs) due to the inherent low highest occupied molecular orbital(HOMO) of fiuorinated solvents. However, such fascinating properties do not bring long-term cyclability of h-LMBs. One of critical challenges is the interface instability in contacting with the Li metal anode, as fiuorinated solvents are highly susceptible to exceptionally reductive metallic Li attributed to its low lowest unoccupied molecular orbital(LUMO), which leads to significant consumption of the fiuorinated components upon cycling.Herein, attenuating reductive decomposition of fiuorinated electrolytes is proposed to circumvent rapid electrolyte consumption. Specifically, the vinylene carbonate(VC) is selected to tame the reduction decomposition by preferentially forming protective layer on the Li anode. This work, experimentally and computationally, demonstrates the importance of pre-passivation of Li metal anodes at high voltage to attenuate the decomposition of fiuoroethylene carbonate(FEC). It is expected to enrich the understanding of how VC attenuate the reactivity of FEC, thereby extending the cycle life of fiuorinated electrolytes in high-voltage Li-metal batteries.
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
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.
基金supported by the Shihezi University High-Level Talents Research Startup Project(Project No.RCZK202521)the National Natural Science Foundation of China(Grant Nos.12271066,11871121,12171405)+1 种基金the Chongqing Natural Science Foundation Joint Fund for Innovation and Development Project(Project No.CSTB2024NSCQLZX0085)the Chongqing Normal University Foundation(Grant No.23XLB018).
文摘This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.
文摘In this paper,we prove that L(K_(x,y))(λ),theλ-fold line graph of the complete bipartite graph Ka,y,has a C_(6)-decomposition if and only if ry≥6,λxy(c+y-2)=0(mod 12)and(x+y)=0(mod 2),where x,y are nonnegative integers and(x,y)≠(2,4)or(2,5).
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 Key R&D Program of China(2023YFD2101001)National Natural Science Foundation of China(32202144,61807001)。
文摘To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.
基金supported by the National Natural Science Foundation of China(Nos.52470114 and 52022104)the National Key R&D Program of China(No.2022YFC3702802)the Youth Innovation Promotion Association,CAS(No.Y2021020).
文摘In recent years,ozone has become one of the key pollutants affecting the urban air qual-ity.Direct catalytic decomposition of ozone emerges as an effective method for ozone re-moval.Field experimentswere conducted to evaluate the effectiveness of exteriorwall coat-ings with ozone decomposition catalysts for ozone removal in practical applications.ANSYS 2020R1 software was first used for simulation and analysis of ozone concentration and flow fields to investigate the decomposition boundary of these wall coatings.The results show that the exterior wall coatings with manganese-based catalysts can effectively reduce the ozone concentration near the wall coating.The ozone decomposition efficiency is nega-tively correlated with the distance fromthe coating and the decomposition boundary range is around 18 m.The decomposition boundary will increase with the increase of tempera-ture,and decrease with the increase of the wind speed and the relative humidity.These results underscore the viability of using exterior wall coatings with catalysts for controlling ozone pollution in atmospheric environments.This approach presents a promising avenue for addressing ozone pollution through self-purifying materials on building external wall.
基金sponsored by the National Natural Science Foundations of China under Grant Nos.12301315,12235007,11975131the Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ20A010009。
文摘In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.
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.
