30 May 2022 Unbiased line edge roughness measurement using profile-averaging method for precise roughness parameters measurement
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Abstract

Background: Scanning electron microscopy (SEM)-based line edge roughness (LER) measurement suffers from an error due to noise in SEM image. Noise correction methods have been developed to obtain unbiased roughness results, however, there are still concerns in the viewpoint of measurement precision.

Aim: To develop an unbiased roughness analysis for highly precise LER measurement.

Approach: Combining the conventional unbiased roughness analysis with a profile-averaging method, where a line pattern is repeatedly measured and then the obtained profiles are aligned and averaged. The experimental result measured by SEM was verified using atomic force microscopy (AFM)-based LER metrology, which has higher reliability than SEM.

Results: The experimental evaluation showed that the proposed method can obtain roughness parameters more precisely than the conventional method.

Conclusions: When the noise in the line edge profile by SEM is too large, it is necessary to reduce the noise beforehand and then perform roughness analysis in order to obtain precise roughness results. The proposed method enables to measure LER with the highest precision using SEM. Additionally, the AFM-based LER metrology was demonstrated as a feasible technique to evaluate the performance of SEM-based LER metrology.

© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE) 1932-5150/2022/$28.00 © 2022 SPIE
Ryosuke Kizu, Ichiko Misumi, Akiko Hirai, and Satoshi Gonda "Unbiased line edge roughness measurement using profile-averaging method for precise roughness parameters measurement," Journal of Micro/Nanopatterning, Materials, and Metrology 21(2), 024001 (30 May 2022). https://doi.org/10.1117/1.JMM.21.2.024001
Received: 25 January 2022; Accepted: 16 May 2022; Published: 30 May 2022
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KEYWORDS
Scanning electron microscopy

Line edge roughness

Metrology

Atomic force microscopy

Spatial resolution

Denoising

Error analysis

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