Mask variability with extraction of SEM image contour and area measurements

Matthieu Piloto, Romain Bange, F. Sundermann
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Abstract

This paper presents contour-based methods to assess mask variability. Mask certification depends on the measurement reliability and on criteria relevance. By now, ST and its maskshop partners rely mostly on CDSEM measurements for mask certification. However, this kind of metrology has limitations and, looking at the future, we think it would be timely to search for metrology which bypass those limitations. That is why we are looking at 2D metrology [1], especially to area and contour measurements [2] on SEM images using extracted contours. Thanks to the added value of 2D metrology, we expect to assess mask variability, mask uniformity and pattern fidelity. We also take the opportunity to compare the results on two FOVs (field of view) from the images provided by mask shops. Finally, we also intend to automate the whole measurement process to make it easier to use.
利用扫描电镜图像轮廓和面积测量提取掩模变异性
本文提出了基于轮廓的方法来评估掩模可变性。口罩认证取决于测量的可靠性和标准的相关性。到目前为止,ST及其口罩商店合作伙伴主要依靠CDSEM测量来进行口罩认证。然而,这种计量方法有其局限性,展望未来,我们认为寻找绕过这些局限性的计量方法是及时的。这就是为什么我们正在研究二维计量学[1],特别是使用提取的轮廓对SEM图像进行面积和轮廓测量[2]。由于二维计量的附加价值,我们期望评估掩模可变性,掩模均匀性和模式保真度。我们也借此机会比较了两个fov(视场)的结果,这两个fov是由面具商店提供的图像。最后,我们还打算自动化整个测量过程,使其更容易使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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