As battery technology evolves and demand for efficient energy storage solutions,aqueous zinc ion batteries(AZIBs)have garnered significant attention due to their safety and environmental ***,the stability of cathode m...
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As battery technology evolves and demand for efficient energy storage solutions,aqueous zinc ion batteries(AZIBs)have garnered significant attention due to their safety and environmental ***,the stability of cathode materials under high-voltage conditions remains a critical challenge in improving its energy *** review systematically explores the failure mechanisms of high-voltage cathode materials in AZIBs,including hydrogen evolution reaction,phase transformation and dissolution *** address these challenges,we propose a range of advanced strategies aimed at improving the stability of cathode *** strategies include surface coating and doping techniques designed to fortify the surface properties and structure integrity of the cathode materials under high-voltage ***,we emphasize the importance of designing antioxidant electrolytes,with a focus on understanding and optimizing electrolyte decomposition *** review also highlights the significance of modifying conductive agents and employing innovative separators to further enhance the stability of *** integrating these cutting-edge approaches,this review anticipates substantial advancements in the stability of high-voltage cathode materials,paving the way for the broader application and development of AZIBs in energy storage.
Human values capture what people and societies perceive as desirable, transcend specific situations and serve as guiding principles for action. People’s value systems motivate their positions on issues concerning the...
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Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is g...
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Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is greatly hindered by the trap-induced non-radiative recombination losses and poor long-term work stability. In the past decade, the huge advancements have been obtained on suppressing nonradiative recombination and enhancing device durability. Among them, the multisite ligands(MSLs) engineering plays a crucial role in precise control and directional modification of functional layers and interfaces,which contributes to markedly increased PCE and lifetimes of PSCs. In view of this, this review summarizes the advances of MSLs in PSCs. From the perspective of functional groups and chemical interaction,the modulation mechanisms of properties of different functional layers and interfaces and device performance via various MSLs are deeply investigated and revealed. Finally, the prospects for the application and development direction of MSLs in PSCs are legitimately proposed.
With the widespread deployment of indoor positioning systems, an unprecedented scale of indoor trajectories is being produced. By considering the inherent uncertainties and the text information contained in such an in...
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With the widespread deployment of indoor positioning systems, an unprecedented scale of indoor trajectories is being produced. By considering the inherent uncertainties and the text information contained in such an indoor trajectory, a new definition named Indoor Uncertain Semantic Trajectory is defined in this paper. In this paper, we focus on a new primitive, yet quite essential query named Indoor Uncertain Semantic Trajectory Similarity Join (IUST-Join for short), which is to match all similar pairs of indoor uncertain semantic trajectories from two sets. IUST-Join targets a number of essential indoor applications. With these applications in mind, we provide a purposeful definition of an indoor uncertain semantic trajectory similarity metric named IUS. To process IUST-Join more efficiently, both an inverted index on indoor uncertain semantic trajectories named 3IST and the first acceleration strategy are proposed to form a filtering-and-verification framework, where most invalid pairs of indoor uncertain semantic trajectories are pruned at quite low computation cost. And based on this filtering-and-verification framework, we present a highly-efficient algorithm named Indoor Uncertain Semantic Trajectory Similarity Join Processing (USP for short). In addition, lots of novel and effective acceleration strategies are proposed and embedded in the USP algorithm. Thanks to these techniques, both the time complexity and the time overhead of the USP algorithm are further reduced. The results of extensive experiments demonstrate the superior performance of the proposed work.
Forecasting river flow is crucial for optimal planning,management,and sustainability using freshwater *** machine learning(ML)approaches have been enhanced to improve streamflow *** techniques have been viewed as a vi...
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Forecasting river flow is crucial for optimal planning,management,and sustainability using freshwater *** machine learning(ML)approaches have been enhanced to improve streamflow *** techniques have been viewed as a viable method for enhancing the accuracy of univariate streamflow estimation when compared to standalone *** researchers have also emphasised using hybrid models to improve forecast ***,this paper conducts an updated literature review of applications of hybrid models in estimating streamflow over the last five years,summarising data preprocessing,univariate machine learning modelling strategy,advantages and disadvantages of standalone ML techniques,hybrid models,and performance *** study focuses on two types of hybrid models:parameter optimisation-based hybrid models(OBH)and hybridisation of parameter optimisation-based and preprocessing-based hybridmodels(HOPH).Overall,this research supports the idea thatmeta-heuristic approaches precisely improveML ***’s also one of the first efforts to comprehensively examine the efficiency of various meta-heuristic approaches(classified into four primary classes)hybridised with ML *** study revealed that previous research applied swarm,evolutionary,physics,and hybrid metaheuristics with 77%,61%,12%,and 12%,***,there is still room for improving OBH and HOPH models by examining different data pre-processing techniques and metaheuristic algorithms.
Nowadays, electronic waste is no longer considered ordinary waste;instead, it is recognized as valuable and hazardous waste containing significant amounts of precious metals. Therefore, it should not be disposed of il...
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An enormous amount of applications that are available for download permits users to enhance the functionality of the devices with brand-new features, which is a significant factor in the growing popularity of smartpho...
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A steady-state thermal hybrid element model is proposed to calculate particle-reinforced composites divided by an improved quadtree *** functional of hybrid flux finite element method(HF-FEM)is constructed using the w...
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A steady-state thermal hybrid element model is proposed to calculate particle-reinforced composites divided by an improved quadtree *** functional of hybrid flux finite element method(HF-FEM)is constructed using the weighted residual *** functional independently assumes a heat flux field in the cell domain and a temperature field along cell *** construction of a universal heat flux function is put forward,which is approximated by a complete polynomial,and the temperature at the cell boundary is obtained by linear ***,the hybrid stress finite element method(HS-FEM)is constructed to solve the thermal *** this paper,an improved quadtree grid that can accurately describe the shape of elliptical inclusions is *** comparing several numerical examples with the traditional FEM,it is demonstrated that the hybrid element of the thermal analysis proposed in this paper is practical.
This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was ...
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This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was introduced in this paper, which took the gross domestic product(GDP) of each region as one of the factors that affect the spread speed of COVID-19 and studied the relationship between the GDP and the infection density of each region(China's Mainland, the United States, and EU countries). In addition, the geographic distance between regions was also considered in this method and the effect of geographic distance on the spread speed of COVID-19 was studied. Studies have shown that the probability of mutual infection of these two regions decreases with increasing geographic distance. Therefore, this paper proposed an epidemic disease spread index based on GDP and geographic distance to quantify the spread speed of COVID-19 in a region. The analysis results showed a strong correlation between the epidemic disease spread index in a region and the number of confirmed cases. This finding provides reasonable suggestions for the control of epidemics. Strengthening the control measures in regions with higher epidemic disease spread index can effectively control the spread of epidemics.
Forecasting the price of bitcoins is significant in contemporary research, given the fact that the digital currency is relatively unpredictable and highly integrated in global securities markets. This paper compares t...
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