Triboelectric nanogenerators (TENGs) have attracted much interest in recent years, due to its effectiveness and low cost for converting high-entropy mechanical energy into electric power. The traditional TENGs generate an alternating current, which requires a rectifier to provide a direct-current (DC) power supply. Herein, a dynamic p-n junction based direct-current triboelectric nanogenerator (DTENG) is demonstrated. When a p-Si wafer is sliding on a n-GaN wafer, carriers are generated at the interface and a DC current is produced along the direction of the built-in electric field, which is called the tribovoltatic effect. Simultaneously, an UV light is illuminated on the p-n junction to enhance the output. The results indicate that the current increases 13 times and the voltage increases 4 times under UV light (365 nm, 28 mW/cm 2 ) irradiation. This work demonstrates the coupling between the tribovoltaic effect and the photovoltaic effect in DTENG semiconductors, promoting further development for energy harvesting in mechanical energy and photon energy.

The study of flexible and stretchable strain sensors is growing rapidly owing to the demands for human motion detection, human–machine interaction, and soft robotics. However, super‐stretchable and highly sensitive strain sensors with high linearity and low hysteresis are especially lacking, which therefore limits the use of soft strain sensors in varied practical applications. The stretchability and sensitivity of the capacitive strain sensor are constrained by the material characteristics and structure of parallel plate capacitor (theoretical gauge factor [GF] is 1). To address these limitations, a super‐stretchable and highly sensitive capacitive strain sensor composed of two strips of wrinkled carbon nanotubes‐based electrodes separated by a tape dielectric, is presented. By integrating nanomaterials and wrinkled film structure, this device achieves a GF of 2.07 at 300% strain with excellent linearity and negligible hysteresis. This is the first type of capacitive strain sensors that can achieve super‐stretchability and sensitivity simultaneously. Additionally, the sensor has a fast signal response time of ≈80 ms, and good mechanical durability during 1000 stretching and releasing cycles. The authors demonstrate the use of this sensor as a versatile wearable device for human motion tracking, and as a smart real‐time monitoring device for soft pneumatic robots.

Intensive turbulence exists in the wakes of high speed trains, and the aerodynamic performance of the trailing car could deteriorate rapidly due to complicated features of the vortices in the wake zone. As a result, the safety and amenity of high speed trains would face a great challenge. This paper considers mainly the mechanism of vortex formation and evolution in the train flow field. A real CRH2 model is studied, with a leading car, a middle car and a trailing car included. Different running speeds and cross wind conditions are considered, and the approaches of unsteady Reynold-averaged Navier-Stokes (URANS) and detached eddy simulation (DES) are utilized, respectively. Results reveal that DES has better capability of capturing small eddies compared to URANS. However, for large eddies, the effects of two approaches are almost the same. In conditions without cross winds, two large vortex streets stretch from the train nose and interact strongly with each other in the wake zone. With the reinforcement of the ground, a complicated wake vortex system generates and becomes strengthened as the running speed increases. However, the locations of flow separations on the train surface and the separation mechanism keep unchanged. In conditions with cross winds, three large vortices develop along the leeward side of the train, among which the weakest one has no obvious influence on the wake flow while the other two stretch to the tail of the train and combine with the helical vortices in the train wake. Thus, optimization of the aerodynamic performance of the