Ultraviolet GaN photodetectors on Si via oxide buffer heterostructures with integrated short period oxide-based distributed Bragg reflectors and leakage suppressing metal-oxide-semiconductor contactsWe report on the composition pulling effect and strain relief mechanism in AlGaN/AlN distributed Bragg reflectors (DBRs) grown on GaN template/a-Al 2 O 3 (0001) by metal organic chemical vapor deposition. The reciprocal space mapping contours reveal that these DBRs are coherently grown. Cross-section transmission electron microscopy image of the AlGaN/AlN DBRs and the energy-dispersive x-ray analysis indicate that an AlGaN layer with gradient Al composition is located between the Al 0.4 Ga 0.6 N and AlN layers along the [0001] direction. It is attributed to the fact that Ga atoms in AlGaN are pulled and segregated to the upper layer by the strain. The density of strain energy is estimated to reduce more than one order by forming this quasi-three-sublayer structure comparing to the designed bi-sublayer structure.

Simultaneous localization and mapping (SLAM) systems have been generally limited to static environments. Moving objects considerably reduce the location accuracy of SLAM systems, rendering them unsuitable for several applications. Using a combined vision camera and inertial measurement unit (IMU) to separate moving and static objects in dynamic scenes, we improve the location accuracy and adaptability of SLAM systems in these scenes. We develop a moving object-matched feature points elimination algorithm that uses IMU data to eliminate matches on moving objects but retains them on stationary objects. Moreover, we develop a second algorithm to validate the IMU data to avoid erroneous data from influencing image feature points matching. We test the new algorithms with public datasets and in a real-world experiment. In terms of the root mean square error of the location absolute pose error, the proposed method exhibited higher positioning accuracy for the public datasets than the traditional algorithms. Compared with the closed-loop errors obtained by OKVIS-mono and VINS-mono, those obtained in the practical experiment were lower by 50.17% and 56.91%, respectively. Thus, the proposed method eliminates the matching points on moving objects effectively and achieves feature point matching results that are realistic.