Search

Biomacromolecular networks, crucial components of biological systems, are of great importance in biological and nanomedical science, in which the interfaces between nanoparticle and macromolecular networks are intriguing and drawing great attention. Herein, this review seeks to present the state‐of‐art progress and perspective of the dynamic behaviors, confinement and entropy at the nanoparticle‐biomacromolecular network interfaces. The basic biomacromolecular networks in living systems, recent research on networks with dynamic bonds and various diffusion behaviors of nanoparticles within biomacromolecular networks are summarized. In particular, entropic effects in the confined environments of biological networks are discussed, along with how they impact the mechanical properties and dynamical behaviors. The interesting research and findings included in this review might offer the scientific community a better understanding of how this field has developed thus far, and are anticipated to trigger more systematic and fundamental research to elucidate the underlying physics and broaden the potential applications of macromolecular networks, biological and artificial. [ABSTRACT FROM AUTHOR]

Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution. However, obtained information of these convolutional neural networks cannot completely express predicted high‐quality images for complex scenes. A dynamic network for image super‐resolution (DSRNet) is presented, which contains a residual enhancement block, wide enhancement block, feature refinement block and construction block. The residual enhancement block is composed of a residual enhanced architecture to facilitate hierarchical features for image super‐resolution. To enhance robustness of obtained super‐resolution model for complex scenes, a wide enhancement block achieves a dynamic architecture to learn more robust information to enhance applicability of an obtained super‐resolution model for varying scenes. To prevent interference of components in a wide enhancement block, a refinement block utilises a stacked architecture to accurately learn obtained features. Also, a residual learning operation is embedded in the refinement block to prevent long‐term dependency problem. Finally, a construction block is responsible for reconstructing high‐quality images. Designed heterogeneous architecture can not only facilitate richer structural information, but also be lightweight, which is suitable for mobile digital devices. Experimental results show that our method is more competitive in terms of performance, recovering time of image super‐resolution and complexity. The code of DSRNet can be obtained at https://github.com/hellloxiaotian/DSRNet. [ABSTRACT FROM AUTHOR]

Increased aggression due to gaming addiction is a widespread and highly publicized problem. The underlying processes by which verbal aggression, a more harmful and persistent subcategory of aggression, is affected by gaming addiction may differ from other types of aggression. In this study, data came from 252 randomly recruited current university students (50.79% male, mean age 19.60 years, SD: 1.44 years, range 17 to 29 years). Participants reported gaming addiction and different types of aggression through questionnaires. In addition, two important explanatory processes, inhibitory control, and risk preference, were measured through behavioral experiments. A Bayesian hierarchical drift-diffusion model was employed to interpret the data from the risk preference task. In contrast to previous work, the study found that inhibitory control did not significantly correlate with either gaming addiction or any form of aggression However, the drift rate, a measure of decision-making inclination under risk, partially mediates the relationship between gaming addiction and verbal aggression (but not other forms of aggression). The findings illuminate risk preference under adverse conditions as a key predictor of verbal aggression, offering avenues for early intervention and suggesting game design modifications to mitigate verbal aggression by adjusting reward mechanisms. [ABSTRACT FROM AUTHOR]

Even though lead halide perovskite has been demonstrated as a promising optoelectronic material for next-generation display applications, achieving high-efficiency and stable pure-red (620~635 nm) emission to cover the full visible wavelength is still challenging. Here, we report perovskite light-emitting diodes emitting pure-red light at 628 nm achieving high external quantum efficiencies of 26.04%. The performance is attributed to successful synthesizing strongly confined CsPbI3 quantum dots with good stability. The strong binding 2-naphthalene sulfonic acid ligands are introduced after nucleation to suppress Ostwald ripening, meanwhile, ammonium hexafluorophosphate exchanges long chain ligands and avoids regrowth by strong binding during the purification process. Both ligands enhance the charge transport ability of CsPbI3 quantum dots. The state-of-the-art synthesis of pure red CsPbI3 quantum dots achieves 94% high quantum efficiency, which can maintain over 80% after 50 days, providing a method for synthesizing stable strong confined perovskite quantum dots. Li et al. report the regulation of perovskite quantum dot growth after nucleation by designing ligand exchange utilising proton transfer. The Ostwald ripening and regrowth are prohibited with an external quantum efficiency of 26.04% achieved in the pure-red perovskite light-emitting diodes. [ABSTRACT FROM AUTHOR]

Traffic network design problems (NDPs) play an important role in urban planning. Since there exist uncertainties in the real urban traffic network, neglecting the uncertainty factors may lead to unreasonable decisions. This paper considers the transportation network signal design problem under stochastic origin-destination (OD) demand. In general, solving this stochastic problem requires a large amount of computational budget to calculate the equilibrium flow corresponding to a certain demand distribution, which limits its real applications. To reduce the computational time in calculating the equilibrium flow under stochastic demand, this paper proposes a metamodel-based optimization method. First, a combined metamodel that integrates a physical modeling part and a model bias generic part is developed. The metamodel is used to approximate the time-consuming average equilibrium flow solution process, hence to improve the computational efficiency. To further improve the convergence and the solution optimality performance of the metamodel-based optimization, the gradient information of traffic flow with respect to the signal plan is incorporated in the optimization model. A gradient-based metamodel algorithm is then proposed. In the numerical example, a six-node test network is used to examine the proposed metamodel-based optimization method. The proposed combined metamodel is compared with the benchmark method to investigate the importance of incorporating a model bias generic part and the traffic flow gradient information in the combined metamodel. Although there is a reduction in solution optimality since the metamodel is an approximation of the original model, the metamodel methods greatly improve the computational efficiency (the computational time is reduced by 4.84 to 13.47 times in the cases of different initial points). By incorporating the model bias, the combined metamodel can better approximate the original optimal solution. Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. Numerical results show that the gradient-based metamodel method can effectively improve the computation efficiency while slightly reducing the solution optimality (with an increase of 0.09% in the expected total travel cost)., Author(s): Wei Huang [1]; Xuanyu Zhang [1]; Haofan Cheng [1]; Jiemin Xie (corresponding author) [2] 1. Introduction Traffic network design is a basic means to improve traffic flow distribution and [...]

Inorganic perovskite quantum dots (QDs) have garnered significant attention due to their outstanding optical properties. However, perovskite quantum dot light‐emitting diodes (Pe‐QLEDs) still face challenges related to their fluorescence efficiency and electron injection. First, the electron transport layer (ETL) leads to severe non‐radiative recombination due to fluorescence quenching in CsPbI3 QDs. Second, there is an electron injection imbalance resulting from low electron injection efficiency, leading to reduced non‐radiative recombination and external quantum efficiency. To address these issues, this study introduces two interface layer materials with different electron affinities, 1,3,5‐Tris(3‐pyridyl‐3‐phenyl)benzene (TmPyPB) and 2,4,6‐Tris(3′‐(pyridine‐3‐yl)biphenyl‐3‐yl)‐1,3,5‐triazine (TmPPPyTz). These materials not only passivated defects on the surface of CsPbI3 QDs films but also effectively prevented the fluorescence quenching of CsPbI3 QDs by the PO‐T2T (ETL). TmPPPyTz, with a relatively lower LUMO energy level, further improved energy level matching, significantly enhancing electron injection efficiency. Ultimately, using interface engineering with the TmPPPyTz interface layer, the devices achieved an outstanding 25.80% champion‐level external quantum efficiency (EQE) for Pe‐QLEDs with only a sub‐bandgap voltage of 1.7 V and half‐life (T50) is 17.99 h at 100 nits. This research provided an effective method to enhance the performance of CsPbI3 Pe‐QLEDs, addressing long‐standing issues inhibiting their efficiency. [ABSTRACT FROM AUTHOR]

Lead sulfide (PbS) colloidal quantum dot (CQD) materials are extensively utilized in the fabrication of near-infrared detectors. Advanced PbS quantum dot infrared detectors often employ ligand exchange processes to enhance the performance of the active layer. This process involves the replacement of long-chain ligands, which exhibit poor conductivity, with short-chain ligands, such as 1,2-ethanedithiol (EDT) in the treatment of PbS. However, conventional solid-state ligand exchange techniques are prone to cause inherent cracking, resulting in significant leakage currents that limit detector sensitivity. To address this challenge, we introduce a copper indium selenium sulfur (CuInSeS) quantum dot interfacial layer, resulting in the creation of a smooth and crack-free film. This method effectively optimizes the interfacial contact between PbS and ZnO. Additionally, this layer concurrently establishes a gradient energy level, facilitating the transport of charge carriers. This results in a decrease in the dark current to 4.6 × 10−8 mA under a −1 V bias, achieving a detectivity of 1.87 × 1012 Jones. The results demonstrate that the quantum dot interfacial layer effectively suppresses the dark current of the detector, addressing the deficiencies associated with the solid-state ligand exchange technique. This work provides a direction for further research on detectors. [ABSTRACT FROM AUTHOR]

Hybrid lead halide perovskites have generated increasing attention for their high performance in optoelectronic applications. One main drawback of these materials is the sensitivity to moisture, which contributes heavily to the ultimate decomposition. Here, this study takes advantage of the reported representative white‐light emitting lead bromide perovskite and three‐dimensional (3D) perovskite as the subject of water‐stability study. It is reported here that other than observed phase transformation in one case, the majority of these perovskites break down in water rapidly, precipitating out as an inorganic salt compound Pb3Br6[H2O]·H2O. As these materials are studied in detail, it is discovered that better coverage of the hydrophobic organic cation enhances the water stability. Taking this idea further, it is demonstrated here that five new one‐dimensional (1D) lead bromide compounds have superior water stability, where the longest stability when completely immersed in water is more than one year and counting. This work provides a new mechanism regarding the degradation process when encountering moisture and general guidelines to increase the water stability for the lead bromide hybrids. [ABSTRACT FROM AUTHOR]

Core–shell perovskite nanocrystals (NCs) have emerged as a promising class of materials for optoelectronic applications due to their unique properties and stability. Although much research has been conducted on the shell growth mechanism and properties of the core–shell NCs, little is known about the role of shell thickness in determining their optical properties. Herein, a heteroepitaxial method is employed to prepare a series of core–shell FAPbBr3/CsPbBr3 NCs with different shell thicknesses. Through temperature‐dependent photoluminescence measurement, it is found that the electronic structure of core–shell FAPbBr3/CsPbBr3 NCs evolves from quasi‐type‐II to type‐I with the increase in shell thickness. This abnormal transition can be attributed to the thickened gradient alloy layer FA1‐xCsxPbBr3, which effectively relieves the lattice mismatch and releases strain in the NCs, resulting in variations in the bandgap between the core and the shell. Furthermore, the biexciton Auger lifetimes in these samples exhibit a non‐monotonic dependence on shell thickness, indicating the electronic structure transition. These results provide valuable insights into the relationship between shell thickness, electronic structure, and optical properties in core–shell perovskite NCs, which may offer guidance for the design of high‐performance optoelectronic devices. [ABSTRACT FROM AUTHOR]

Highlights: A new proton-promoted in situ ligand exchange strategy based on CsPbI3 quantum dots. The ligand exchange strategy maintains the quantum confinement effect of quantum dots and significantly improves the stability and photophysical properties of CsPbI3 quantum dots. The performance of light-emitting diodes based on CsPbI3 quantum dots is significantly improved, the external quantum efficiency is increased from 18.63% to 24.45%, and the half-operational lifetime is increased by 70 times. CsPbI3 perovskite quantum dots (QDs) are ideal materials for the next generation of red light-emitting diodes. However, the low phase stability of CsPbI3 QDs and long-chain insulating capping ligands hinder the improvement of device performance. Traditional in-situ ligand replacement and ligand exchange after synthesis were often difficult to control. Here, we proposed a new ligand exchange strategy using a proton-prompted in-situ exchange of short 5-aminopentanoic acid ligands with long-chain oleic acid and oleylamine ligands to obtain stable small-size CsPbI3 QDs. This exchange strategy maintained the size and morphology of CsPbI3 QDs and improved the optical properties and the conductivity of CsPbI3 QDs films. As a result, high-efficiency red QD-based light-emitting diodes with an emission wavelength of 645 nm demonstrated a record maximum external quantum efficiency of 24.45% and an operational half-life of 10.79 h. [ABSTRACT FROM AUTHOR]

In order to solve the problems of low efficiency, multiple blind spots, and high risks in traditional debris flow exploration, two technical means were adopted: small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) and unmanned aerial vehicle (UAV) low altitude remote sensing (the former obtains highly reliable deformation of vegetation coverage areas through dense images, while the latter obtains high-resolution realistic 3D models through regional network adjustment and other processing) . Integrating deformation and image texture, a survey and analysis of debris flow valleys along a railway in a certain mountainous area was conducted to obtain the spatial and temporal distribution of geological hazards in the watershed. The results show that, through SBAS-InSAR technology, it was found that there were multiple seasonal active hazards in the debris flow valley, with a maximum deformation variable of 28.5 mm/a. Based on the 3D model of UAV, a detailed investigation was conducted on the spatial form, volume, occurrence, and development of the deformation hazard. The largest scale landslide had a volume of 165 000 to 180 000 cubic meters. On site investigations show that the comprehensive remote sensing technology can effectively overcome the challenges of complex mountainous terrain and difficult access for humans, providing a multidimensional perspective for disaster screening. It has the advantages of low personnel investment, wide monitoring area, fast disaster positioning, and high screening accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a closed-loop simulation of vehicle dynamics in CarSim is utilized as surrogate measures to study the effect of pavement roughness and differential settlement on risk of vehicle rollover and skidding. It is found that the influence of pavement roughness on vehicle rollover is significant and the influence of pavement roughness on vehicle skidding is insignificant. The influence of pavement roughness of grade A and B on safety margin of vehicle rollover can be negligible. Pavement roughness of grade C and D significantly reduces the safety margin of vehicle rollover. A 5cm settlement difference on pavement reduces the safety margin of vehicle skidding on a good road. When the settlement difference is 5cm, the vehicle rollover and skidding are greatly affected by the lane-changing speed. It provides an effective and general method based on vehicle dynamics for studying transportation safety as well as for setting up criteria for pavement maintenance., Author(s): Lu Sun [1]; Luchuan Chen [2]; Yanna Yin (corresponding author) [3]; Yao Tian [2]; Xuanyu Zhang [4] 1. Introduction Despite the decline in highway fatalities from 2001 to 2014 [...]

Perovskite nanocrystals for light‐emitting diodes are often synthesized by uncontrollable metathesis reactions, suffering from low product yield, nonuniform growth, and poor stability. Herein, by controlling the nucleation kinetics with high dissociation constant (Ka or Kb) acids or bases, homogenous one‐route nucleation of perovskite nanocrystals is achieved as the cluster intermediates are eliminated. The stable, shape uniform, and narrow size distribution green nanocrystals are synthesized. The perovskite nanocrystal film exhibites excellent stability in 80% humidity air with only a 10% photoluminescence intensity drop after 16 h. Efficient and stable electroluminescence is demonstrated with an FWHM of 16 nm at 517 nm. The green devices shows a peak EQE of 24.13% with a lifetime T50 of 54 min at 10 000 cd m−2. [ABSTRACT FROM AUTHOR]