Efficient mask characterization through automated contour and corner rounding extraction

Abstract

Wafer CD Uniformity (CDU) and pattern fidelity are useful properties to monitor when considering yield improvement and scaling to smaller dimensions. Besides control of process fluctuations (e.g., focus, dose), wafer stack film thickness uniformity, and image quality (e.g., contrast), quality of mask manufacturing and OPC models are essential to optimize these properties. Therefore, a proper characterization of the written mask dimensions is becoming more and more important, especially as the mask pattern complexity increases through Inverse Lithography Technology (ILT) as well as the need for curvilinear or all-angle designs. Applying contour-based mask quality assessment instead of traditional gauge-based characterization of mask dimensions allows to intrinsically capture mask imperfections like corner rounding (CR) of the absorber for complex shapes which would be hard to measure and categorize by using only a few gauges. Thus, in our study, we examine ways to use contour-based mask characterization methods, including CD and area uniformity, linearity, and CR determination to evaluate mask quality. We present a method and flow to automatically extract contours and determine values for mask CR from top-down mask SEM images. Contour-based metrology and data evaluation is then used to quantitatively address the above-mentioned mask properties of interest. Finally, as an initial approach to investigate impact of mask quality on wafer printing, we apply a generic EUV model to ideal and imperfect masks and compare the simulated contour results. Using realistic mask patterns for lithography modeling and simulation is considered essential to achieve the required accuracy for advanced nodes and technologies.