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This article proposes a novel solution to the issue of protection instability caused by time synchronization error in high-speed differential protection schemes for dc microgrids. DC microgrids provide a more efficient platform to integrate fast-growing renewable energy sources, energy storage systems, and electronic loads. However, the integration of distributed generators (DGs) may result in variable fault current magnitude and direction during fault conditions, potentially causing miscoordination of conventional time graded overcurrent relays. One identified solution to this issue utilizes high-speed differential protection schemes to maintain effective selectivity in DG-dominated dc microgrids. However, as dc short-circuit fault currents are highly transient, microseconds of synchronization error in the measured line currents may cause protection stability issues, whereby maloperation of relays may occur as a result of faults external to the protected zone. This article investigates the impact of time synchronization errors for high-speed differential protection in dc distribution systems. It then proposes a multisample differential (MSD) scheme that performs multiple differential comparisons over a sampling window to ensure the stability of high-speed differential protection schemes for external faults while maintaining the sensitivity to internal faults.

The microstructure evolution of AlN implanted with Eu during thermal treatment is characterized by transmission electron microscopy (TEM), high‐resolution X‐ray diffraction, and atomic force microscopy. Three regions with different contrast can be observed in the TEM for the implanted samples. The region A is 30 nm below the surface, the region B is about 30–100 nm below the surface and is the worst damaged area, and the region C is the area below the region B. There is a relatively large stress in the region B due to the large radius difference between Eu and Al ions. After annealing at 750 °C, the stress in region B is only partially released outward, resulting in the increase of lattice defects in regions A and C. Both A and C regions show the same contrast in the weak‐beam bright‐field image. After annealing at 1040 °C, there are almost no shadow regions, which indicates that the stress is completely released and the lattice damage is removed. Meanwhile, the results of cathodoluminescence (CL) show that the luminescence of Eu3+is improved along with the stress releasing and damage removal. AlN:Eu films are obtained by implanting europium (Eu) ions into aluminum nitride (AlN) films and annealing at different temperatures. The experiment successfully removes the lattice damage and activates the luminescence centers of the AlN:Eu. At the same time, the evolution of the microstructure of AlN:Eu film is analyzed at different annealing temperatures.

Automatic segmentation of 3D tooth models into individual teeth is an important step in orthodontic CAD systems. 3D tooth segmentation is a mesh instance segmentation task. Complex geometric features on the surface of 3D tooth models often lead to failure of tooth boundary detection, so it is difficult to achieve automatic and accurate segmentation by traditional mesh segmentation methods. We propose a novel solution to address this problem. We map a 3D tooth model isomorphically to a 2D harmonic parameter space and convert it into an image. This allows us to use a CNN to learn a highly robust image segmentation model to achieve automated and accurate segmentation of 3D tooth models. Finally, we map the image segmentation mask back to the 3D tooth model and refine the segmentation result using an improved Fuzzy-Clustering-and-Cuts algorithm. Our method has been incorporated into an orthodontic CAD system, and performs well in practice. [ABSTRACT FROM AUTHOR]