Overview of Silicon Carbide Wafer Defect Types and Inspection Techniques

With the development of the semiconductor industry, Silicon Carbide (SiC) is becoming more and more important in high temperature, high frequency, power, RF devices and other applications, so more effort should be put into improving the quality of SiC wafers. Wafer defects directly affect the performance and reliability of the device, and may also lead to potential device failure. Therefore, an in-depth understanding of the types of defects and the methods of detecting them is essential for improving the fabrication process of SiC devices. In this paper, we systematically review the common types of defects in SiC wafers, including non-graphic defects before lithography and graphic defects after lithography, and the mechanisms of these defects and their impacts on device performance are also discussed in the paper. Subsequently, in order to identify and characterize these defects more accurately, this paper systematically reviews a variety of inspection methods, including optical microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and other imaging techniques combined with the now very hot machine learning automatic detection and identification methods. In addition, this paper discusses the historical process of wafer defect detection methods and the advantages and disadvantages of the current detection methods, and emphasizes the possibility of machine learning in defect detection and how to use cutting-edge technologies such as deep learning to further enhance the advantages of defect recognition such as accuracy and speed. Finally, this paper summarizes the shortcomings and challenges of the current research and proposes future research directions to advance the sustainable development of SiC wafer defect detection, and through this review, it is hoped that some references can be provided to improve the production quality and reliability of SiC devices.