To maintain lithographic pitch scaling, extreme ultraviolet (EUV) processes have been adopted in high-volume manufacturing (HVM) for today’s advanced logic and memory devices. Among various defect sources, stochastic patterning defects are one of the most important yield detractors for EUV processes. In this work, we will limit our scope to patterning defects arising out of lithography. In the past, it has been shown that the patterning defect process window is often limited by stochastic hotspots. These hotspots have very low failure probabilities in a well-optimized process, and hence their detection necessitates large area sensitive defect inspection, such as with a broadband plasma (BBP) optical defect inspection system. It has also been shown that systematic issues in design can be exacerbated by stochastic variations. Hence, it is critical to discover these hotspots and study their variability with massive SEM metrology. Such analyses can uncover systematic trends, which can then be corrected and monitored. In this work, we discover hotspots using broadband plasma (BBP) optical inspection and study their variability using KLA’s aiSIGHT™ pattern-centric defect and metrology software solution for automatic defect classification and SEM metrology measurements. We also demonstrate the need for fast and rigorous 3D probabilistic stochastic defect detection on design as a continuation of this work.
Stochastics defect detection has been a topic of intense study by the extreme ultraviolet (EUV) patterning fraternity [1]. A large part of this initial feasibility work has been performed using electron microscope-based systems [1,2]. A limited sample area is imaged using electron microscopes and images are analyzed using offline analysis techniques [1,2]. However, to accurately quantify the stochastics failure rate, the entire area of interest needs to be inspected. Given such large area inspection requirements, automated and high throughput solutions are the need of the hour to enable stochastics quantification in HVM (high volume manufacturing). This paper demonstrates Broadband Plasma optical wafer inspection capability to capture two key defects on EUV layers a) missing contact in contact hole array patterns b) line breaks in line- space pattern.
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