南昌交通学院

Single-walled carbon nanotube (SWCNT) films, owing to their superior tunable electron transport characteristics, are expected to enable flexible and high-performance energy harvesting materials towards photothermal, photovoltaic, and thermoelectric conversion fields. Thus, it is crucial to prepare semiconducting (s-) SWCNTs towards a highly efficient device. However, the available technology is mainly for sorting SWCNTs, which involves complex operations. Moreover, pure s-SWCNTs exhibit relatively poor electron transport performance compared with metallic (m-) SWCNTs. Here, we report an electrochemical-modulation approach that directly regulates the electronic structure of unsorted SWCNT networks without any separation process. By applying controlled potentials in an ionic-liquid electrolyte, the Fermi level and density of states of s-SWCNTs are reversibly tuned, thereby modifying the energetic alignment and carrier-filtering behavior. This unsorted treatment greatly reduces the reflectance of SWCNT films and thus improves the harvesting of light energy. With the electrical conductivity undisturbed under light illumination, the Seebeck coefficient completes a about 50% improvement for the SWCNTs obtained at an applied potential of -0.2 V, resulting in a large power factor of 261 & micro;W m- 1 K- 2, which is 2-fold higher than that of pristine SWCNTs. The reinforced photothermoelectric effect is associated with the changes in the energy barrier at the m-s junctions in unsorted SWCNTs, which provides an alternative way for unsorted SWCNTs in high-performance solar energy harvesting.

The nuclear magnetic resonance (NMR) T₂ distributions of free fluid are widely used to characterize the bulk relaxation properties of fluids. However, in the heavy crude oil of reservoirs in the western South China Sea, solid-phase impurities such as waxes, asphaltenes, and colloids result in multi-peak, broad-spectrum T₂ distributions. This complexity hinders accurate peak identification and fluid property analysis. To address this, typical crude oils from the study area were selected, and their free-fluid T₂ distributions were measured under reservoir-temperature conditions. The observed multi-peak patterns were analyzed to determine their physical and chemical origins. Based on the Gaussian distribution function, a fast Gaussian picking method is proposed to search for representative distribution peaks in crude oil in conjunction with extreme points. The non-negative least squares (NNLS) method is utilized to fit the data, and the complex T₂ distribution was decomposed into components representing different phases and viscosities. After mathematical-physical tests and demonstrations, the rapid classification of the T2 distribution of the free-fluid state of impurity-containing viscous crude oil is realized. Applied to downhole NMR data, the method accurately captured the T₂ characteristics of such crude oils, offering a fast and reliable tool for analyzing complex bulk relaxation behaviors and fluid identification. Finally, the method’s performance, influencing factors, and applicability were discussed.

This review paper systematically investigates the surface modification technology of wooden table tennis blades, with a particular focus on the inherent conflict between coating-induced protection and the preservation of acoustic performance—a critical yet underexplored aspect of blade design. While protective coatings are essential for enhancing durability against moisture, wear, and impact, they inevitably alter the blade’s vibrational characteristics and acoustic feedback, compromising the tactile–auditory perception that elite players rely upon. The current literature predominantly treats protection and acoustics as separate design objectives, lacking an integrated framework to resolve their inherent trade-off. To address this gap, this review establishes a material–structure–function integrated design paradigm that elucidates the synergistic optimization of coating protection and acoustic response. We systematically analyze the regulatory mechanisms of key coating parameters—specifically elastic modulus, density, and damping coefficient—on blade vibration modes and impact sound characteristics, demonstrating that conventional singular optimization inevitably leads to undesirable frequency shifts and diminished tactile feedback. Our synthesis of materials science, acoustic analysis, and biomechanics reveals that the key to synergy lies in constructing a mechanical impedance-matching transition system through material selection and thickness gradient design. Notably, we show that a multi-layer gradient coating architecture, guided by finite element simulation, can enhance protective performance by 40% while restricting acoustic deviation to within 5%, validating a rational “design–simulation–verification” closed-loop methodology. Furthermore, this review identifies critical research frontiers, including smart adaptive coatings and sustainable bio-based materials, and proposes a multi-objective optimization framework to bridge the gap between laboratory innovation and manufacturable, high-performance sporting equipment. This work provides a foundational theoretical roadmap for the next-generation design of competition-grade table tennis blades, balancing durability with the nuanced sensory demands of elite athletes.

Urban pedestrian areas create hazardous conditions through their multiple street vendor and vehicular traffic and street infrastructure and pedestrian elements. The research presents a real-time object detection system which improves footpath surveillance and navigation support. The system implements a lightweight YOLOv8n (Nano) model which uses class refinement and audio signature integration to achieve better detection accuracy and enhanced user experience. The dataset contains footpath images which have been annotated to display multiple object categories which include pedestrians and vendors and vehicles and infrastructure and obstacles and trees. The researchers applied preprocessing techniques which included image resizing and noise reduction and pixel normalization and data augmentation to enhance their feature extraction process. The system uses convolutional layers to extract features at multiple scales while its optimized detection pipeline enables real-time object detection. The experimental results show that the system demonstrates better performance than the baseline systems. The proposed method achieves mAP@50 of 0.954, precision of 0.928, recall of 0.912, and F1-score of 0.920, while maintaining an inference latency of 8.4 ms and 119 FPS on CPU, demonstrating potential for real-time applications on CPU-based systems. The study showed that detection performance of MobileNet-SSD and YOLOv5n was inferior to the system because it achieved better detection results and faster processing times. The study introduces a new approach which combines lightweight object detection with audio feedback to create better human-computer interaction while delivering real-time guidance to help pedestrians navigate safely.

The microstructure of titanium alloy is one of the key factors affecting its fatigue performance. In this work, the influence of the microstructure of an Extra-low-interstitial (ELI) Ti–6Al–4V alloy fabricated by electron beam additive manufacturing (EBAM) on its stress-life fatigue performance in the high cycle fatigue regime was investigated. The Ti–6Al–4V alloy after fabrication was subjected to hot isostatic pressing (HIP) and solid solution-aging treatments, and then the fatigue specimens were machined from the alloy in both the horizontal direction (HD) and vertical direction (VD). The results show that the EBAM-produced Ti–6Al–4V alloy displays excellent fatigue performance, which is comparable to that of wrought materials. The fatigue limit (σ−1) at a specified life of 107 cycles, tested by the up-and-down method, is 575 MPa in the HD, which is a little more than that in the VD of 565 MPa. Such excellent fatigue performances are mainly resulted from the alloy being free of defects and relative fine microstructure. Moreover, anisotropic fatigue performance is observed, particularly for the samples loaded at the condition of great peak stress. In this case, the fatigue life for samples loaded along the HD is greater than that along the VD, while the former presents a relatively larger scatter in fatigue life. The anisotropic fatigue performance is mainly due to the α textures of the alloy transformed from the <100> //VD β fiber texture, as well as the inhomogeneous deformability of large size columnar prior β grains which is sensitive to the loading direction. The small difference in fatigue limit between the HD and VD can be attributed to the large scatter nature.