Vortex spinning is a novel process for spinning short-staple yarns with high production rate and quality. The dynamics of the fiber in the nozzle plays a key role on the properties of the resultant yarn. In this paper, the images of fiber motion in the airflow inside the nozzle of vortex spinning are captured using a high-speed photography technique. The nozzle is magnified according to the Reynolds number similarity. Based on the high-speed photographic results, the effects of some parameters – the nozzle pressure, yarn delivery speed, and distance between the nozzle inlet and the hollow spindle – on the motional characteristics of the fiber are investigated.

This paper provides a new method for predicting the diameter of electrospun nanofibers. Based on the grey system theory, the effects of polyacrylonitrile mass fraction, voltage, flow rate, and receiving distance on fiber diameter were studied. The GM(1,1) (grey model) model and DNGM(1,1) (The DNGM (1,1) model is based on the whitening differential equation using parameters to Directly estimate the approximate Non-homogeneous sequence Grey prediction Model) model were established to predict fiber diameter by a single-factor change, and the results showed high prediction accuracy. The multi-variable grey model MGM(1,n) (MGM(1,n) is a Multivariate Grey prediction Model) was used for prediction of fiber diameter when multiple factors change simultaneously. The results showed that the average modeling fitting error is 8.62%. The background value coefficients of the MGM(1,n) model were optimized, the average modeling fitting error was reduced to 1.01%, and the average prediction error was reduced to 1.33%. Combining the fractional optimization with the background-value coefficient optimization, the optimal background-value coefficient $\alpha$ and the order r were selected. The results showed that the average modeling fitting error is 0.85%, and the average prediction error is 0.38%. The results demonstrate that the grey system theory can effectively predict the diameter of polyacrylonitrile electrospinning fibers with high prediction accuracy. This theory can increase the control of nanofiber diameters in production.

A kind of composite was designed and additive manufacturing (AM) technology was utilized in the braiding structure fabrication. The printed polylactic acid (PLA) braiding structures were integrated with two types of resins (Epon 828 resin and urethane dimethacrylate/triethylene glycol dimethacrylate (UDMA/TEDGMA) resin) used as the matrix to make composite specimens. The compression test of the composite specimens showed that the printed PLA braiding structures had the effect of varying the compression properties of pure resins: it decreased the compression properties of Epon 828 resin, but increased those of UDMA/TEGDMA resin. Observing scanning electron microscope (SEM) images, it was noted that the decreasing and increasing in the compression properties of the specimens were related to the bonding compactness between the printed braiding structure and resins. Our results may suggest a new methods for the fast manufacturing of AM-based composites, further research directions, and potential applications of this kind of composites.

The static and dynamic mechanical performances of notched and un-notched 3D braided composites were studied. The effect of longitudinal laid-in yarn was investigated in comparison with low braiding angle composites. The specimens were fatigue tested for up to millions of cycles, and the residual strength of the samples that survived millions of cycles was tested. The cross-section of the 3D braided specimens was observed after fatigue loading. It was found that the static and fatigue properties of low angle 3D braided behaved better than longitudinally reinforced 3D braided composites. For failure behavior, pure braids contain damage better and show less damage area than the braids with longitudinal yarns under fatigue loading. More cracks occurred in the 3D braided specimen with axial yarn cross-section along the longitudinal and transverse direction.

Diamond is an attractive substrate candidate for GaN high-electron-mobility transistors (HEMT) to enhance heat dissipation due to its exceptional thermal conductivity. However, the thermal boundary resistance (TBR) at the GaN–diamond interface poses a significant bottleneck to heat transport, exacerbating self-heating and limiting device performance. In this work, TCAD simulations were employed to systematically investigate the effects of thermal boundary layer (TBL) thickness (d_TBL) and thermal conductivity (κ_TBL) on the electrothermal behavior of GaN-on-diamond HEMTs. Results show that increasing the TBL thickness (5–20 nm) or decreasing its thermal conductivity (0.1–1.0 W/(m·K)) leads to elevated hotspot temperatures and degraded electron mobility, resulting in a notable deterioration of I–V characteristics. The nonlinear dependence of device performance on κ_TBL is attributed to Fourier’s law, where heat flux is inversely proportional to thermal resistance. Furthermore, the co-analysis of substrate thermal conductivity and interfacial quality reveals that interface TBR has a more dominant impact on device behavior than substrate conductivity. Remarkably, devices with low thermal conductivity substrates and optimized interfaces can outperform those with high-conductivity substrates but poor interfacial conditions. These findings underscore the critical importance of interface engineering in thermal management of GaN–diamond HEMTs and provide a theoretical foundation for future work on phonon transport and defect-controlled thermal interfaces.