Standard No.:	GB/T 43493.2-2023
English Name:	Semiconductor device—Non-destructive recognition criteria of defects in silicon carbide homoepitaxial wafer for power devices—Part 2: Test method for defects using optical inspection
Chinese Name:	半导体器件 功率器件用碳化硅同质外延片缺陷的无损检测识别判据 第2部分：缺陷的光学检测方法
Chinese Classification:	L90    Special electronic technology material
Professional Classification:	GB    National Standard
ICS Classification:	31.080.99 31.080.99    Other semiconductor devices 31.080.99
Issued by:	SAMR; SAC
Issued on:	2023-12-28
Implemented on:	2024-7-1
Status:	valid
Language:	English
File Format:	PDF
Word Count:	12500 words
Price(USD):	375.0
Delivery:	via email in 1~3 business day

Semiconductor device - Non-destructive recognition criteria of defects in silicon carbide homoepitaxial wafer for power devices - Part 2: Test method for defects using optical inspection 1 Scope This document provides definitions and guidance in use of optical inspection for detecting as-grown defects in commercially available 4H-SiC (Silicon Carbide) epitaxial wafers. Additionally, this document exemplifies optical images to enable the detection and categorization of the defects for SiC homoepitaxial wafers. This document deals with a non-destructive test method for the defects so that destructive methods such as preferential etching are out of scope in this document. 2 Normative references There are no normative references in this document. 3 Terms and definitions For the purposes of this document, the following terms and definitions apply. ISO and IEC maintain terminological databases for use in standardization at the following addresses: ——IEC Electropedia: available at http://www.electropedia.org/ ——ISO Online browsing platform: available at http://www.ISO.org/obp 3.1 optical inspection morphological inspection of wafers using optical imaging where an optical image sensor scans the wafer surface under a non-contact test method for obtaining features of defects, e.g. size and shape of defects 3.2 optical imaging technique for capturing, processing and analysing images of defects using light source for illumination, optical components, optical image sensor and computer systems 3.3 illumination application of light to defects and their surroundings so that they can be observed 3.4 reflective illumination illumination for observing the reflected light from defects by irradiating light onto the wafer surface 3.5 directional lighting lighting in which the light to the wafer is incident from a particular direction 3.6 diffused lighting lighting in which the irradiation direction of the light to the wafer is random 3.7 bright-field observation method of image capturing in which an optical image sensor detects both lights reflected and scattered from defects 3.8 dark-field observation method of image capturing in which an optical image sensor detects only light scattered from defects 3.9 differential interference contrast observation method of image capturing in which contrast derives from the difference in optical path between adjacent points on the wafer surface by irradiating two orthogonal polarized lights which are spatially displaced 3.10 polarized light observation method of image capturing in which an optical image sensor detects a polarized light using polarizing plates in a path from defects by irradiating polarized light 3.11 optical image sensor device to transform an optical image into digital data 3.12 optical component lenses, mirrors, filters and other components, which comprise an optical system and are used to capture optical images 3.13 image capturing process of creating a two-dimensional original digital image of defects on the wafer surface 3.14 original digital image digitized image taken by an optical image sensor, without performing any image processing Note: Original digital images are divided into pixels by a grid, and one grey level is assigned to each pixel. 3.15 charge-coupled device; CCD light-sensitive integrated circuit that stores and displays the data for optical images Note: CCD chips are subdivided into fine elements, each of which corresponds to a pixel of original digital images. 3.16 pixel smallest formative element of original digital images, to which a grey level is assigned 3.17 resolution number of pixels per unit length (or area) of original digital images Note: If resolutions in the X- and Y- directions are different, both values have to be recorded. 3.18 grey level shade of grey assigned to each pixel Note: Shade of grey is usually a positive integer taken from grey scale. 3.19 grey scale range of grey shades from black to white EXAMPLE: 8-bit grey scale has two-to-the-eighth-power (= 256) grey levels. Grey level 0 (the 1st level) corresponds to black, grey level 255 (the 256 t h level) to white. 3.20 image processing software manipulation of original digital images to prepare for subsequent image analysis Note: For example, image processing can be used to eliminate mistakes generated during image capturing or to reduce image information to the essential. 3.21 binary image image in which either 0 (black) or 1 (white) is assigned to each pixel 3.22 brightness average grey level of a specified part of optical images 3.23 contrast difference between the grey levels of two specified parts of optical images 3.24 shading correction software method for correcting non-uniformity of the illumination over the wafer surface 3.25 thresholding process of creating a binary image out of a grey scale image by setting exactly those pixels whose value is greater than a given threshold to white and setting the other pixels to black. Note: To make a binary image, grey level 0 (black) or 1 (white) is assigned to each pixel in the grey-scale image, depending on whether the pixel indicates a grey level greater than or less than or equal to a given threshold.