Line edge roughness measurement through SEM images: effects of image digitization and their mitigation

Abstract

Line Edge Roughness is largely used in the current semiconductor research and industry for the evaluation of materials and processes since it is considered one of the critical factors to degrade device performance. Therefore, its accurate measurement and complete characterization though complicated is highly required. LER measurement is usually based on the analysis of top-down SEM images. As a result, it suffers from the limitations of image-based metrology which among others are the presence of noise and the digital nature of images. Recently, several studies have paid attention on the impact of image noise on LER metrics and the aliasing effects on the Power Spectrum Density curves caused by the discreteness of edge data along line/edge direction. However, image digitization imposes discretization of edge data also in the vertical to edge/line direction. In this paper, we focus on the effects of this aspect of edge data discretization on LER rms value and PSD curve. We explain and analyze the effect using synthesized SEM images and identify the critical role of the ratio of rms to pixel size. We find that for such ratios larger than 0.6, the image digitization has a fixed contribution to the measured rms roughness and PSD which should be removed to mitigate these effects.