Presentation + Paper
22 February 2021 Parametric modeling of patterned object with variations and expert tuning of edge placement
Author Affiliations +
Abstract
The research and development steps in the semiconductor industry require tools that are able to handle features with large variation across the images, but also tools that can reproduce the definition of an edge taught by an expert. This definition should be easily modified to mimic the expert decisions in order to reduce the time spent by process engineers during research and development phases. We developed a patterned edge model allowing to detect the profile of patterned objects in microscopic images. A complementary tool is proposed to customize the definition between two materials according to the expert targets. The obtained profiles serve as a basis to perform robust metrology and ensure quality control of the manufactured semiconductor components.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
B. Darbon, M. Grould, N. Clément, J. Baderot, S. Martinez, and J. Foucher "Parametric modeling of patterned object with variations and expert tuning of edge placement", Proc. SPIE 11615, Advanced Etch Technology and Process Integration for Nanopatterning X, 116150K (22 February 2021); https://doi.org/10.1117/12.2583810
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KEYWORDS
Machine learning

Semiconductors

Metrology

Microscopes

Process engineering

Algorithm development

Databases

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