As the requirements and expectation for displays in society are growing, higher standards of the display technology are proposed, including wider color gamut, higher color purity, and higher ...resolution. The recent emergence of light‐emitting halide perovskites has come with numerous advantages, such as high charge‐carrier mobility, tunable emission wavelength, narrow emission linewidth, and intrinsically high photoluminescence quantum yield. Recent advancement of perovskite‐based light‐emitting diodes (PeLEDs) as a promising technology for next‐generation displays is reviewed. Here, how the attractive optical and electrical properties of perovskite materials can be translated into high PeLED performance are discussed, and working mechanisms and optimization approaches of both perovskite materials and the respective devices are analyzed. On the material side this includes the control of size and composition of perovskites grains and nanocrystals, surface and interface passivation, doping and alloying, while on the device side this includes the interfacial engineering and energy level adjustments, and photon emission enhancement. Several challenges such as performance of blue PeLEDs, the environmental and operational stability of PeLEDs, and the toxicity issues of lead halide perovskites are discussed, and perspectives on future developments of perovskite materials and PeLEDs for the display technology are offered.
Here, how attractive optical and electrical properties of perovskite materials are translated into the high performance of perovskite‐based light‐emitting diodes (PeLEDs) is discussed, and working mechanisms and optimization approaches of both perovskite materials and the respective devices are analyzed. Several challenges such as performance of blue PeLEDs, the environmental and operational stability of PeLEDs, and the toxicity issues of lead halide perovskites are considered.
Aqueous Zn-I flow batteries utilizing low-cost porous membranes are promising candidates for high-power-density large-scale energy storage. However, capacity loss and low Coulombic efficiency ...resulting from polyiodide cross-over hinder the grid-level battery performance. Here, we develop colloidal chemistry for iodine-starch catholytes, endowing enlarged-sized active materials by strong chemisorption-induced colloidal aggregation. The size-sieving effect effectively suppresses polyiodide cross-over, enabling the utilization of porous membranes with high ionic conductivity. The developed flow battery achieves a high-power density of 42 mW cm
at 37.5 mA cm
with a Coulombic efficiency of over 98% and prolonged cycling for 200 cycles at 32.4 Ah L
(50% state of charge), even at 50 °C. Furthermore, the scaled-up flow battery module integrating with photovoltaic packs demonstrates practical renewable energy storage capabilities. Cost analysis reveals a 14.3 times reduction in the installed cost due to the applicability of cheap porous membranes, indicating its potential competitiveness for grid energy storage.
Boosting of the ensemble learning model has made great progress, but most of the methods are Boosting the single mode. For this reason, based on the simple multiclass enhancement framework that uses ...local similarity as a weak learner, it is extended to multimodal multiclass enhancement Boosting. First, based on the local similarity as a weak learner, the loss function is used to find the basic loss, and the logarithmic data points are binarized. Then, we find the optimal local similarity and find the corresponding loss. Compared with the basic loss, the smaller one is the best so far. Second, the local similarity of the two points is calculated, and then the loss is calculated by the local similarity of the two points. Finally, the text and image are retrieved from each other, and the correct rate of text and image retrieval is obtained, respectively. The experimental results show that the multimodal multi-class enhancement framework with local similarity as the weak learner is evaluated on the standard data set and compared with other most advanced methods, showing the experience proficiency of this method.
Accurate and efficient evaluation of singular integrals is of crucial importance for the successful implementation of the boundary element method (BEM). In most traditional methods, complex ...mathematical operations or expensive computation cost is required to achieve high accuracy of singular integral. To solve this problem, a new machine learning-based prediction framework is proposed in this paper from the perspective of data analysis. Using the framework, an effective prediction model can be constructed by various supervised machine learning algorithms. The prediction model is fed into the BEM program to predict the results of singular integrals directly according to the given coordinates of the elements. In this process, a transformation method is proposed to bridge the gap between the training space in which the prediction model is constructed and the application space in which the prediction model is applied. We take the singular integrals in 3D elastostatics as an example to evaluate the performance of the proposed framework with 5 typical machine learning algorithms. The results demonstrate that, the prediction method has less cost time while getting identical computational accuracy with the traditional method. More importantly, the prediction accuracy is numerically stable and not sensitive to the position of source points.
Colloidal all‐inorganic perovskite nanocrystals have gained significant attention as a promising material for both fundamental and applied research due to their excellent emission properties. ...However, reported photoluminescence quantum yields (PL QYs) of blue‐emitting perovskite nanocrystals are rather low, mostly due to the fact that the high energy excitons for such wide bandgap materials are easily captured by interband traps, and then decay nonradiatively. In this work, it is demonstrated how to tackle this issue, performing self‐assembly of 2D perovskite nanoplatelets into larger size (≈50 nm × 50 nm × 20 nm) cuboid crystals. In these structures, 2D nanoplatelets being isolated from each other within the cuboidal scaffold by organic ligands constitute multiple quantum wells, where exciton localization on potential disorder sites helps them to bypass nonradiative channels present in other platelets. As a result, the cuboid crystals show an extremely high PL QY of 91% of the emission band centered at 480 nm. Moreover, using the same synthetic method, mixed‐anion CsPb(Br/Cl)3 cuboid crystals with blue emission peaks ranging from 452 to 470 nm, and still high PL QYs in the range of 72–83% are produced.
2D cesium lead halide (CsPbX3, X = Br, Br/Cl) perovskite nanoplatelets self‐assemble into large size (≈50 nm × 50 nm × 20 nm) cuboid nanocrystals, which show strong blue emission with high photoluminescence quantum yields of 72–91% in the wavelength range of 452–480 nm due to improved radiative channels.
The presented work investigates structural and functional fatigue behaviors of Ni49.8Ti50.2 (at. %) SMA wires under various maximum heating temperatures. Firstly, a thermo-mechanical fatigue ...experimental setup is established to test 24 SMA wires under various maximum heating temperatures (Tmax) of 92 °C, 115 °C, 147 °C, 165 °C, 211 °C, 291 °C. Then, the influence of Tmax on the fatigue life, strain evolution and failure type is discussed and a model is developed to simulate the plastic evolution behavior. Several experimental results are summarized. 1) The fatigue life decreases significantly from 26,559 to 35 cycles as Tmax increases from 92 °C to 291 °C. 2) The final plastic strain increases with Tmax rising and the fracture characteristic transfers from brittle mode to ductile mode. 3) Plastic strain in martensite phase becomes saturated in stage I of plastic strain curves and plastic strain in austenite phase contributes most of plasticity after that. 4) A higher Tmax increases the stable recovery strain and the degradation rate of recovery strain. Finally, based on experimental results, the plastic strain evolution behavior in stage I and stage II is simulated through a Tmax based model. This model shows a good quality of simplicity and precision.
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•Fatigue life, final plastic strain and fracture mode change regularly when maximum heating temperature increases.•The plasticity is caused by residual stress in martensite and dislocation motion in austenite in two stages.•A higher maximum heating temperature increases the stable recovery strain and the degradation rate of recovery strain.•A maximum heating temperature based model is developed to preciously simulate the plastic strain evolution behavior.
Decorating single atoms of transition metals on MXenes to enhance the electrocatalytic properties of the resulting composites is a useful strategy for developing efficient electrocatalysts, and the ...mechanisms behind this enhancement are under intense scrutiny. Herein, we anchored Co single atoms onto several commonly used MXene substrates (V2CTx, Nb2CTx and Ti3C2Tx) and systematically studied the electrocatalytic behavior and the mechanisms of oxygen and hydrogen evolution reactions (OER and HER, respectively) of the resulting composites. Co@V2CTx composite displays an OER overpotential of 242 mV and an HER overpotential of 35 mV at 10 mA cm−2 in 1.0 M KOH electrolyte, which is much lower than for Co@Nb2CTx and Co@Ti3C2Tx, making it comparable to the commercial noble metal Pt/C and RuO2/C electrocatalysts. The experimental and theoretical results point out that the enhanced bifunctional catalytic performance of Co@V2CTx benefits from the stronger hybridization between Co 3d and surface terminated O 2p orbitals which optimized the electronic structure of Co single atoms in the composite. This, in turn, results in lowering the OER and HER energy barriers and acceleration of the catalytic kinetics in case of the Co@V2CTx composite. The advantage of Co@V2CTx was further validated by its high overall water splitting performance (1.60 V to deliver 10 mA cm−2). Our study sheds light on the origins of the catalytic activity of single transition metals atoms on MXene substrates, and provides guidelines for designing efficient bifunctional MXene‐based electrocatalysts.
Co single atoms were anchored on three different MXenes substrates, namely Co@V2CTx, Co@Nb2CTx and Co@Ti3C22Tx, which were tested as electrocatalysts of oxygen and hydrogen evolution reactions (OER and HER). Combinations of experimental and theoretical studies point out that the enhanced bifunctional catalytic performance of Co@V2CTx benefits from the higher electron transfer, which results in lowering the energy barriers and accelerating the catalytic kinetics for both OER and HER.
•Innovation alliances and partnerships have become widespread, especially in high-tech industries, characterized by limited network structure varieties.•We provide a network game to analyze the ...network structure by incorporating endogenous R&D spillovers and diffusion effects.•We characterize the network structure of enterprises' strategic R&D decisions in different types of spatial equilibrium.•The theoretical framework generates policy implications under cooperative R&D, location choice, spatial agglomeration, and social capital allocation in innovation networks.
We provide a network game to analyze the innovation network structure by incorporating endogenous R&D spillovers and diffusion effects, reconciling the limited types of innovation alliance in practice. In our network model, enterprises can actively choose to invest in R&D or establish links with others to absorb R&D spillovers. We characterize the network structure of enterprises' strategic R&D decisions in different types of spatial equilibrium. We further extend the theoretical framework to generate industry-specific implications under cooperative R&D, location choice, spatial agglomeration, and social capital allocation in innovation networks.
The rise of fintech in the past decade has received growing scholarly attention. Does the application of fintech promote innovation efficiency at the regional level? Will fintech heterogeneously ...affect a different stage of innovation? Motivated by these questions, this paper studies the impact of fintech on innovation efficiency and the spatial spillover effects of fintech by using regional-level data on China. We employ a two-stage DEA method to evaluate the innovation efficiency, namely, the R&D efficiency and launching efficiency, of different innovation processes. We conduct an empirical test by using the spatial Durbin model in combination with the fintech development index. The results suggest that fintech promotes overall innovation efficiency and launching efficiency but less affects R&D efficiency. Fintech also exhibits adverse spatial spillover effects on the surrounding regions in the launching stage. We further studied the effects of the breadth and depth of fintech on innovation and the impacts on different types of patents. The results show a heterogeneous impact of fintech, which generates regional development policy implications in the digital era.
•Fintech innovations have developed rapidly in recent years and increasingly transform financial services.•We employ a two-stage DEA method to evaluate the R&D efficiency and launching efficiency of different innovation processes.•Fintech promotes overall innovation efficiency and launching efficiency but less affects R&D efficiency.•Fintech also exhibits adverse spatial spillover effects on the surrounding regions in the launching stage.
Objectives:
This study aims to explore the associations of personality traits and extra-family social relationship with depressive symptoms among Chinese adults.
Methods:
A nationally representative ...sample of 29,810 adults aged 16 and above were selected from 2018 CFPS. Personality and depressive symptoms were measured using CBF-PI-15 and the CES-D8 scale. Extra-family social relationship was assessed through the self-rated evaluation. The multiple regression analysis and the PROCESS macro were used for the mediation analysis.
Results:
Extraversion (OR = 0.807, 95% CI = 0.773, 0.842), agreeableness (OR = 0.795, 95% CI = 0.756, 0.835) and extra-family social relationship (OR = 0.927, 95% CI = 0.913, 0.941) had negative associations with depressive symptoms. Extra-family social relationship could mediate between extraversion and depressive symptoms (Indirect effect = −0.049,95% CI = −0.060, −0.039) as well as agreeableness (Indirect effect = −0.056, 95% CI = −0.068, −0.046) and depressive symptoms. Comparing to females, the indirect effect accounts for a higher proportion of total effect in males.
Conclusion:
Extra-family social relationship might mediate the association between extraversion and depressive symptoms as well as agreeableness and depressive symptoms.
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