Improved geometry reconstruction and uncertainty evaluation for extreme ultraviolet (EUV) scatterometry based on maximum likelyhood estimation

Abstract

The task of solving the inverse problem of scatterometry is considered. As a non-imaging indirect optical metrology method the goal of scatterometry is, e.g., to reconstruct the absorber line profiles of lithography masks, i.e., profile parameters such as line width, line height, and side-wall angle (SWA), from the measured diffracted light pattern and to estimate their associated uncertainties. The impact of an appropriate choice of the statistical model for the input data on the reconstructed profile parameters is demonstrated for EUV masks, where light with wavelengths of about 13.5 nm is applied. The maximum likelihood method is proposed to determine more reliable estimations of all model parameters, including the sought profile dimensions. Finally, this alternative approach is applied to EUV measurement data and the results are compared to those obtained by a conventional analysis.