Global minimization line-edge roughness analysis of top down SEM images

Line edge placement error is a limiting factor in multipatterning schemes which are required for advanced nodes in high volume manufacturing for the semiconductor industry. Thus, we aim to develop an approach which provides both a quantitative estimate of whether a segment of a feature edge is in the ideal location and a quantitative estimate of the long wavelength roughness. The method is described, numerical simulation models its application to the issue of distortion caused by SEM aberrations, and the method is applied to a sample data set of SEM images. We show that the method gives a robust estimate of a major component leading to feature edge placement error. Long wavelength distortions either from SEM aberrations or from long wavelength noise have a clear statistical signature. This methodology applied to a large, consistently acquired SEM data set allows estimates as to important elements required to assess the line edge placement error issue and to whether there is underlying long wavelength roughness which arises from physical sources