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Cross-sectional profile prediction from top-view SEM images based on root-cause decomposition of line edge roughness

机译:基于线边缘粗糙度根源分解的顶视图SEM图像截面剖面预测

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Topographic profiles are reconstructed from top-view images in scanning electron microscope (SEM) by predicting a local slope angle based on how surface roughness (morphology) looks from top-view. Careful analysis of Line edge roughness (LER) reveals that LER obtained in top-view SEM images is decomposed into three components, parallel shift, cross-sectional shape deformation, and surface roughness, and the local slope angle of pattern surface is estimated from the surface roughness component, which corresponds to the projection of surface roughness onto the substrate plain. Cross-sectional profiles reconstructed by scanning this procedure across top-view SEM images showed good agreements with the results obtained by other metrology methods such as an atomic force microscope.
机译:通过基于表面粗糙度(形态)从顶视图的外观预测局部倾斜角,从扫描电子显微镜(SEM)中的顶视图图像重建地形轮廓。对线边缘粗糙度(LER)的仔细分析表明,在顶视图SEM图像中获得的LER被分解为三个部分,即平行移动,横截面形状变形和表面粗糙度,并且可以从图案表面估计局部倾斜角。表面粗糙度分量,它对应于表面粗糙度在基板平面上的投影。通过在顶视图SEM图像上扫描此过程而重建的截面轮廓与通过其他计量方法(例如原子力显微镜)获得的结果显示出良好的一致性。

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