Paper
10 May 2005 Influence of focus variation on linewidth measurements
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Abstract
The influence of spatial resolution on linewidth measurements in the critical dimension scanning electron microscope (CD-SEM) was investigated experimentally. Measurement bias variation and measurement repeatabilities of four edge detection algorithms were evaluated with a series of images at varying focus in order to determine the effect of resolution variation. Three of these algorithms, maximum derivative, regression to baseline, and sigmoidal fit, are commonly used on commercial CD-SEMs, and the other is a model-based library (MBL) approach that detects the line edge by comparing CD-SEM line scans to a library of simulated line scans. MBL is able to take into account beam size and other parameters (including sidewall angle of the line structure). These algorithms were applied to images of polycrystalline silicon lines with various sidewall angles taken under different focus conditions. In general, it was observed that repeatability is degraded by defocus, and bias varied with focus and target shape. These results indicate that if two or more tools had different resolutions, measurement results would have different biases depending on target shape. The amounts of errors depend on the algorithms, with MBL the most stable against focus variation. However, it still has some systematic errors and outliers far from best focus. Investigations of electron distributions and the effect of electron incident angle were performed for a better model.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maki Tanaka, John S. Villarrubia, and Andras E. Vladar "Influence of focus variation on linewidth measurements", Proc. SPIE 5752, Metrology, Inspection, and Process Control for Microlithography XIX, (10 May 2005); https://doi.org/10.1117/12.599741
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Cited by 16 scholarly publications and 2 patents.
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KEYWORDS
Beam shaping

Critical dimension metrology

Gold

Scanning electron microscopy

Carbon

Line scan image sensors

Mathematical modeling

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