Poster + Paper
21 November 2023 An advanced 2D feature transmitted algorithm for mask defect detection
Author Affiliations +
Conference Poster
Abstract
Reticle defect problem caused by different reasons is an unavoidable issue for mask application in fab, which has great influence on the quality and yield of chip product. With the development of chip pitch size, defect management became increasingly important for the higher demand of defect printability. For different patterns of reticle, the impact is quite different owing to the defect location relative to patterns is different which may impact critical dimension (CD) and actual pattern distort on wafer and result in product yield loss. In this study, we used a special algorithm to combine die to die detection results with MEBES data, and defined the defects risk with the energy attenuation (energy loss) of the whole pattern region which different from traditional point-to-point comparison in KLA inspection equipment. Besides, we introduced sensitivity factor(S) for better evaluate the defect risk. The mathematical relationship between the size of the mask defect and the wafer CD are verified by experiments and based on the experimental results, we established the energy loss auto measurement system for monitoring and analysis system of the defect of the hole pattern mask by correlate the size of the defects to the light energy loss rate, which effectively reduces the process risk caused by the mask defect.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yilei Zeng, Yi Cheng, Mengyao Jin, and Hunter Li "An advanced 2D feature transmitted algorithm for mask defect detection", Proc. SPIE 12751, Photomask Technology 2023, 127510Z (21 November 2023); https://doi.org/10.1117/12.2684046
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KEYWORDS
Semiconducting wafers

Inspection

Algorithm development

Transmittance

Air contamination

Defect detection

Detection and tracking algorithms

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