Stochastic effects in EUV patterning refer to random variations that impact local pattern edge fidelity. It can be caused by the lithography or etch processes. Distorted edge placement can result in larger pattern edge roughness, distorted pattern shape for contract holes, poor CD uniformity, and in more severe cases, partially or fully closed contacts. Large statistical SEM metrology can be used to quantify the severity of distortion and failure probability by measuring line edge roughness (LER) and line width roughness (LWR) [3]. The attempt to differentiate between normal global uniformity and local uniformity pose a metrology challenge. In this paper, we present a scanning electron microscopy (SEM) based method for detecting stochastic defects. The detected defects are reviewed by metrology and classified by defect margin merit. The proposed merit converts geometrical attributes into statistical attributes which identify whether a pattern is statistically normal or a statistical outlier.
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