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Line Edge Roughness measurement through SEM images: Effects of image digitization and their mitigation

机译:通过SEM图像线边缘粗糙度测量:图像数字化的影响及其缓解

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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.
机译:线边缘粗糙度主要用于当前的半导体研究和工业,用于评估材料和过程,因为它被认为是降低装置性能的关键因素之一。因此,非常需要复杂的精确测量和完整表征。 LER测量通常基于自上而下的SEM图像的分析。结果,它受到基于图像的计量的局限性,其中包括噪声的存在和图像的数字性质。最近,几项研究已经注意到图像噪声对LER度量上的影响以及由沿线/边缘方向的边缘数据的离散性引起的功率谱密度曲线的锯齿效应。然而,图像数字化也在垂直到边缘/线方向上施加边缘数据的离散化。在本文中,我们专注于该方面对LER RMS值和PSD曲线上的边缘数据离散化的影响。我们使用合成的SEM图像解释并分析效果,并识别RMS与像素大小的比率的关键作用。我们发现,对于大于0.6的这种比例,图像数字化对测量的RMS粗糙度和PSD具有固定贡献,这些粗糙度和PSD应该被移除以减轻这些效果。

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