Nanchang Hangkong University

In this study, the Ti600/TC18 dissimilar alloy parts were joined by inertia friction welding, which is mainly used in aerospace industry as structural components. Then the investigation of the residual stress distribution in the inertial friction welded joint of Ti600/TC18, both pre-and post-weld heat treatment, was carried out using ABAQUS software and XRD. The results show that the highest temperature during the welding is up to 1200 °C; it is subjected to tensile stress. As the welding goes on, the range of tensile stress is expanded gradually, and it is up to 8.92 MPa. During the welding, dynamic recrystallization is occurred in the weld zone, so the refined dynamic recrystallization grains are formed. After heat treatment, the martensitic transformation is occurred within the β phase, so the α p , acicular α, α s and residual β phase are existed in the weld zone. Moreover, the heat treatment has an obvious effect on the distribution of longitudinal residual stress, which can promote the residual stress field to be distributed more uniform and gradual. In addition, the peak tensile stress on the weld surface can be reduced effectively by stress relief annealing, which is attributed to the obvious growth of grain and the coarsening of lath-like α phase in the joint. Finally, comparing the test values with the simulation values, the later exhibits better accuracy and stability.

In this paper, we propose an axial strain sensitivity enhancement method based on what we believe to be a novel fusion-spliced microbubble resonator filled with F3O4 nanoparticles. The fusion-spliced microbubble resonator is formed by splicing a hollow-core bubble and a single-mode fiber at both ends. The temperature inside the resonator is elevated by passing control light into one end of the resonator. The temperature increase can change the material properties of the silicon oxide resonator to increase the strain sensitivity. The effect of temperature on the strain sensitivity of the resonator was investigated theoretically and experimentally. A maximum sensitivity of 16.4 pm/µε was measured by adjusting the control light, and the strain sensitivity increase was achieved without realizing ultra-thin wall thickness. This novel microbubble resonator structure is expected to be used in applications such as high-precision sensing or tunable lasers.

Hexavalent chromium (Cr(VI)) is a highly toxic environmental pollutant posing a serious threat to ecosystems and human health. In recent years, adsorption and photocatalytic reduction technologies have become effective solutions for removing Cr(VI) due to their high efficiency and low cost.This review provides a critical overview of Cr(VI) removal by adsorption and photocatalysis, with particular emphasis on their synergistic effects. The efficiency of Cr(VI) removal by adsorption and photocatalytic reduction methods is often influenced by factors such as pH, interfering ions, and the initial concentration of Cr(VI), which impacts their application in complex environments. Therefore, overcoming the challenges in practical operations remains an issue. This review discusses the application of different materials in Cr(VI) removal with a focus on their adsorption and photocatalytic reduction mechanisms. It also analyzes the effects of material properties and external environments on Cr(VI) removal and suggests directions for optimizing material performance. By further improving the selectivity, stability, and synergistic effects of adsorption and photoreduction of materials, future research is expected to design more efficient and economical Cr(VI) removal materials and facilitate their wide applications in practical environments.

Real-time semantic segmentation is one of the most researched areas in the field of computer vision, and research on dual-branch networks has gradually become a popular direction in network architecture research. In this paper, a dual-branch automatic driving image segmentation network integrating spatial and channel attention mechanisms is proposed with named as “BiAttentionNet”. The network aims to balance network accuracy and real-time performance by processing high-level semantic information and low-level detail information separately. BiAttentionNet consists of three main parts: the detail branch, the semantic branch, and the proposed attention-guided fusion layer. The detail branch extracts local and surrounding context features using the designed PCSD convolution module to process wide-channel low-level feature information. The semantic branch utilizes an improved lightweight Unet network to extract semantic information from deep narrow channels. Finally, the proposed attention-guided fusion layer fuses the features of the dual branches using detail attention and channel attention mechanisms to achieve image segmentation tasks in road scenes. Comparative experiments with recent mainstream networks such as BiseNet v2, Fast-SCNN, ConvNeXt, SegNeXt, Segformer, CGNet, etc., on the Cityscapes dataset show that BiAttentionNet achieves a highest accuracy of 65.89% in the mIoU metric for the backbone network. This validates the effectiveness of the proposed BiAttentionNet.

Electrochromic-supercapacitors (EC-SCs) based on conducting polymers hold broad application prospects in fields such as smart electronic devices, wearable devices, and the Internet of Things. However, complex structures generated by their...

Photothermocatalytic oxidation technology stands out as one of the most environmentally friendly and effective approaches for VOC degradation, and the catalyst plays a pivotal role in this process. In this study, carbon-doped Co3O4 nanocomposites (C-Co3O4) were synthesized via the sol-gel method and employed for the photothermal degradation of toluene. The results reveal that the calcination temperature profoundly influences the photothermal catalytic performance of the materials. C-Co3O4-250, obtained by calcination at 250 °C, exhibits the largest specific surface area, superior low-temperature reduction capability, and enhanced oxygen species activity, leading to its optimal catalytic performance in the photothermal oxidation of toluene. Under a light intensity of 400 mW/cm², toluene conversion reaches 95%, and the CO2 yield attains 80% on C-Co3O4-250 during continuous flow reactions, much higher than that of 18% and 10% on pure Co3O4. Graphical Abstract

To solve the problems of thickening and wrinkling on the inside of aluminum alloy small bend radius tube bends, insufficient length of output section, and cracking of output section ports, this paper takes a 5A02 aluminum alloy thin-walled tube with a relative bending radius of 0.9, an outer diameter of 32 mm, and a wall thickness of 1 mm as the research object. This is the first study to propose a new process and a new device for push–pull-rotate–integrated (P-P-RI) bending forming. A finite element model was established, and the P-P-RI bending forming experiment was carried out. The study shows that the intervention of the tension load can effectively reduce the gap between the polyurethane blocks, so that the bending tube in the forming process has more uniform force. When the tension load is 360 MPa, under the premise of ensuring that the length of the output section is sufficient, it can also effectively improve the degree of bending tube cross-sectional distortion. The rotational speed of the rotating wheel has an important impact on the length of the output section of the bend; the greater the speed of rotation, the longer the length of the output section of the bend. Lubrication of the inside and outside of the tube bends using “large inside, small outside” sub-area differentiation can effectively improve the inner side of the tube bends’ thickening wrinkles and the output section of the port by reducing the thinning phenomenon of cracking.

Grain boundary (GB) energy plays a crucial role in determining the physical and mechanical properties of polycrystalline materials, making it a key factor in the optimization of materials through GB engineering. This study computes the energies of 12,062 tilt and twist GBs in body-centered cubic (BCC) Fe using atomistic simulation. The resulting dataset facilitates a statistical analysis of GB energy anisotropy and comparison with those already revealed in face-centered cubic (FCC) Al. Results indicate that the energies of tilt and twist GBs in Fe overall increase with misorientation angle (θ) before plateauing. Tilt GB energies decrease as the misorientation axis (O) shifts from the center to edges and then to corners of the stereographic triangle, while twist GB energies vary smoothly, with a notable energy valley near 〈110〉 axis. The GB-plane orientation (n) dependency of boundary energy should be interpreted from the view of the surface energy corresponding to GB-plane. The relative significance of crystallographic parameters to GB energy is ranked as θ > n >> O, with the coincidence index primarily identifying local energy cusps on the energy versus angle curve. Trends in GB energy relative to crystallography in BCC structures highly resemble those in FCC structures. However, it seems impossible to determine a specific scaling factor between GB energies in two structures or correlate this factor with any material properties. This study can provide crucial data for GB energy fitting and simulations of thermodynamic behaviors related to GBs.

Recently, various universal image restoration methods have achieved notable success, employing a single model to handle distinct unknown degradations. However, most of these methods require a significant number of model parameters and computational resources to learn the correlations among multiple degradations. Inspired by the efficient parameter learning methods based on wavelet transform, this paper designs a simple wavelet-based guided transformer model for efficient universal image restoration. First, we utilize wavelet subbands to guide up-and-down sampling and frequency-aware degradation-specific feature aggregation. Then, we send the decomposed high-frequency components to a classifier designed for getting degradation weights. These weights can be used to guide the filtering of detail coefficients along with high-frequency components. Finally, we adaptively aggregate the processed high- and low-frequency components, effectively producing degradation-specific information for universal image restoration. Extensive experiments show the superior performance of the proposed WaveUIR, achieving state-of-the-art (SOTA) performance with 88.16% decrease in model parameters and 77.15% reduction in computational resources compared to previous SOTA method. The code is available at https://github.com/Archaic-Atom/WaveUIR.

Constructing built‐in electric fields is a proven method to enhance dielectric loss mechanisms by amplifying interfacial polarization. However, a single built‐in electric field is often insufficient for significantly improving electromagnetic (EM) polarization loss. To address this, dielectric ecosystems are developed utilizing an anion injection strategy to regulate work function differences. Through first‐principles calculations, the directional transfer of space charges at multi‐heterogeneous interfaces is visualized. The resulting work function differences spontaneously establish a dual built‐in electric field (DBIEF) structure, which substantially enhances EM polarization loss and EM wave absorption capabilities. Furthermore, an equivalent circuit model elucidates the competition between polarization and conduction species in the EM loss mechanism. This competition results in exceptional EM wave absorption performance, achieving a minimum reflection loss (RLmin) of −58.71 dB and an effective absorption bandwidth (EAB) of 7.92 GHz. Computer simulation technology demonstrates a maximum radar cross‐section (RCS) reduction of 39.18 dB·m². Additionally, the unique hollow‐truncated‐pyramid metamaterial design exhibits high incidence angle insensitivity (60°) over 2–38 GHz, and significant broadband absorption across 2–40 GHz. This comprehensive work offers novel insights into the structural design of EM nanomaterials and introduces a new dielectric ecosystem to elucidate the DBIEF loss mechanism for efficient EM wave absorption.

Vanadium oxide, as a cathode material for aqueous zinc-ion batteries (AZIBs), typically provides good cycling for the insertion/deinsertion of Zn2+, but it is also prone to structural collapse and slow ion diffusion rate, leading to low capacity and short lifespan. In this work, we reported the preparation of flower-spherical Cu0.4V2O5, which effectively enlarged the crystal spacing (0.987 nm) through the pillar effect of interlayer Cu2+. This not only alleviated the structural collapse but also provided good electrical conductivity. As the cathode, the electrode showed discharge capacities of 267 and 128 mAh·g−1 at 0.1 and 2 A·g−1, respectively. In addition, the Zn2+ storage mechanism was further analysed by ex situ X-ray diffraction, presenting the reaction of the intercalation. This work provides a good idea for pillar-type modification for layered materials.

The blade‐coating method has become an important technology that can be expanded to manufacture perovskite solar photovoltaics. However, the inherent conflict between rapid solvent removal and crystallization control in ambient blade‐coating process fundamentally constrains the production throughput and film quality of perovskite solar modules. Here, a ternary solvent system (DMF/NMP/2‐methoxyethanol) with hierarchical volatility gradients is developed, synergistically integrated with vacuum‐flash evaporation to decouple nucleation and crystal growth kinetics. Specifically, 2‐methoxyethanol (2‐ME) enables vacuum flash‐induced supersaturation for templated nucleation, while NMP facilitates strain‐relaxed grain coalescence, and DMF ensures optimal ink rheology. This approach yields pinhole‐free films with enlarged grains under ambient conditions (T = ≈30 ± 5 °C, RH = 30 ± 10%). The blade‐coated n‐i‐p perovskite solar cells (active area: 0.08 cm²) achieve a power conversion efficiency (PCE) of 23.24%, and 5 × 5 cm² mini‐modules (12 cm² active area) reach 22.12%, with merely 4.8% efficiency loss upon 150 times area upscaling. The devices exhibit improved stability, retaining 90% of their initial PCE after 800 h of maximum power point tracking (MPPT) at 25 °C. The approach establishes a unified solution that addresses crystallization precision, ambient compatibility, and industrial manufacturability in perovskite photovoltaics.

Sodium-ion batteries (SIBs) have gained increasing attention for commercial applications due to their low cost and environmental friendliness. However, developing high-performance and low-cost anode materials remains significant challenge. This study...

Transient hydraulic pressure is crucial for hydraulic pressure and pipeline leak detection in the fields of petroleum pipelines, gas pipelines, and so on. Real-time, long-distance, online, high-pressure, and high-precision measurement requirements can be precisely achieved through fiber optic sensing technology. In response to the need for pipeline leak detection, we propose a fiber-optic transient hydraulic pressure sensor based on single-hole-dual-core fiber Bragg grating (SHDC-FBG). By inscribing FBG on SHDCF using a deep ultraviolet laser, we conduct modal field analysis on the SHDCF and theoretical simulation analysis of the resonance wavelength of the SHDC-FBG. The simulation results closely match experimental data, demonstrating that air holes induce significant pressure-driven refractive index changes in the center core. Furthermore, the static and dynamic pressure sensing characteristics have been discussed. Experimental results indicate that the SHDC-FBG sensor exhibits a sensitivity of -5.4 pm/MPa within a wide dynamic hydraulic range of 0-20 MPa. To measure the hydraulic leak process, we compare the SHDC-FBG sensor with a conventional resistive pressure sensor. The experimental results show that the performance of the two sensors is essentially the same. Nevertheless, the compact size, low cost, and electromagnetic immunity make our sensor more competitive in harsh, long-distance environments.

Infrared sensors are widely used in human action recognition because of their low light influence and excellent privacy protection. However, the traditional deep learning networks and training or testing methods tend to fall into the trap of local optimum because of the similarity between infrared image classes and the lack of discriminative features such as texture and depth, and thus obtain poor recognition results. To address this issue, we propose a novel human action recognition method based on similarity evaluation. This method innovatively transforms the traditional training and testing (verification) mode. First, we use a feature-to-feature training method to make the network pay more attention to the behavioral information that distinguishes the classes. Second, we design a Integrate Channel Attention Module(ICA) to enable Siamese network to focus on the areas of interest. Finally, we propose the Multimodal Similarity Evaluation Module (MSE). The module aims to address the fuzzy matching problem of feature areas. The contrast experiment results show that our method outperforms existing mainstream methods on several benchmark datasets. The excellent accuracy provides an innovative method for addressing various problems related to high similarity between classes.

This study investigates the fabrication of a ZrSiO4-based coating (ZSO coating) on substrate surfaces using atmospheric plasma spraying (APS) technology, with ZrSiO4 as the feedstock material. A comprehensive characterization of the coating systems was conducted, including an in-depth analysis of phase composition and a systematic evaluation of the effects of spray thickness and heat treatment temperature on phase evolution, microstructural development, and the resulting properties. The coatings’ resistance to silicon corrosion and the associated failure mechanisms were thoroughly examined. The key findings reveal that the plasma-sprayed coatings form a multiphase system composed of ZrSiO4, along with the decomposition products of ZrO2 and SiO2. Optimal performance was observed within a critical thickness range of 154–240 μm. Post-deposition heat treatment at 1500 °C significantly improved the integrity of the coatings, as evidenced by a marked reduction in crack density and porosity, leading to substantial enhancement in densification. The coatings demonstrated outstanding performance in the high-temperature silicon corrosion tests, maintaining structural integrity after 4 h of exposure to molten silicon and its oxides at 1500 °C. Notably, the coatings effectively prevented the penetration of silicon into the C/C substrate, preserving strong interfacial adhesion without the formation of permeable cracks. Furthermore, post-corrosion analysis showed that the surface reaction products could be easily removed, underscoring the coatings’ exceptional protective capability for the underlying C/C substrate.