Polishing state analysis prediction program, storage device, cathode fluorescent device, and polishing state analysis prediction method

CN116490321BActive Publication Date: 2026-07-03NAT UNIV CORP NAGAOKA UNIV TECH +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NAT UNIV CORP NAGAOKA UNIV TECH
Filing Date
2021-09-15
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

Existing technologies make it difficult to quantitatively evaluate the grinding rate of GaN substrates in a short time, resulting in low grinding efficiency and difficulty in accurately controlling grinding time, thus failing to effectively improve the optimization efficiency of grinding conditions.

Method used

The CL image of the substrate is obtained by cathodoluminescence method. The luminescence intensity or brightness data is fitted by a logistic function to predict the polishing rate and final polishing time. Combined with the change in black line density, a quantitative analysis of the polishing state is achieved.

Benefits of technology

Accurate estimation of grinding rate and final grinding time in a short time improves grinding efficiency, reduces unnecessary grinding time, and optimizes grinding conditions.

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Abstract

A polishing state analysis and prediction program, storage device, cathodoluminescence device, and polishing state analysis and prediction method are provided, which contribute to the efficiency of polishing by objectively grasping the surface state of the substrate in the initial stage of polishing and estimating polishing conditions in a short time. The polishing state analysis and prediction program predicts the future polishing state of the substrate based on the cathodoluminescence image of the substrate to be polished obtained by cathodoluminescence method. The computer performs the following steps: after the start of substrate polishing, it acquires average luminous intensity data or average brightness data based on the cathodoluminescence images at predetermined time intervals; and it marks the average luminous intensity data or average brightness data and uses a predetermined function to derive an expression representing the fitted curve of the mark.
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