Measurement of pattern roughness and local size variation using CD-SEM

Abstract

Measurement of line edge roughness (LER) is discussed from four aspects: edge detection, power spectrum densities (PSD) prediction, sampling strategy, and noise mitigation. General guidelines and practical solutions for LER measurement today are introduced. Advanced edge detection algorithms such as the wave-matching method are shown to be effective for robustly detecting edges from low SNR images, whereas a conventional algorithm with weak filtering is still effective in suppressing SEM noise and aliasing. An advanced PSD prediction method such as the multitaper method is effective in suppressing sampling noise within a line edge to analyze, whereas a number of lines are still required for suppressing line-to-line variation. Two types of SEM noise mitigation methods, such as the “apparent noise floor” subtraction method and LER-noise decomposition using regression analysis, are verified to successfully mitigate SEM noise from PSD curves. These results are extended to local critical-dimension uniformity (LCDU) measurement to clarify the impact of SEM noise and sampling noise on LCDU.