Ms. Lina Mahmoud Profile

Lina Mahmoud

at Siemens EDA

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Proceedings Article | 10 April 2024 Poster + Paper

The effect of edge placement error on deformity and roughness calculation

Mohamed Abaidi, Ir Kusnadi, Stewart Wu, Lina Mahmoud, Loic Schneider, Borislava Dimitrova, Satya Sriram, Chris Clifford

Proceedings Volume 12955, 1295538 (2024) https://doi.org/10.1117/12.3010845

KEYWORDS: Contour modeling, Optical proximity correction, Contour extraction, Scanning electron microscopy, Deformation, Edge roughness, Calibration, Spectral density, Performance modeling, SRAF

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In semiconductor industry, CD-SEMs (Critical Dimension Scanning Electron Microscopes) play a pivotal role in metrology and process control. Furthermore, additional applications harnessing the potential of CD-SEM equipment have been developed, including contour extraction algorithms, to address the increasing metrological demands. The task of detecting deformity in semiconductor processes has become a formidable challenge due to the continuous reduction in device feature sizes as we progress from one node to another. Deformity in this case can be described as simulation extra prints or detected manufacturing defects. In this paper, we have utilized vector calculations to detect deformity and calculate roughness. Our product, Calibre ContourCal, facilitates the computation of differences between lithographical simulations and measurements. By evaluating the Root Mean Square Error (RMSE) value, we can identify defects in the SEM image or unexpected extra prints in simulation. Additionally, we have proficiently positioned the sites in critical areas based on contour curvature. To evaluate the quality of the model’s simulated contours, we have introduced a novel indicator based on the difference between the simulated model's Power Spectral Density (PSD) and the fitted PSD. The computation of RMSE for a large FoV (Field of View) containing high site count, exceeding one million sites for example, is a demanding task. For that we parallelized our calculation method using GPUs. With the utilization of GPUs, we have achieved significant time savings, simplifying the processing of high site count. Consequently, we can efficiently detect deformity and calculate roughness for large FoV.

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