Mr. Karthik Yogendra Profile

Karthik Yogendra

at IBM Corp

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Proceedings Article | 23 March 2020 Presentation + Paper

Simulation of photoresist defect transfer through subsequent patterning processes

Dominik Metzler, Mohamed Oulmane, Sagarika Mukesh, Phil Stopford, Karthik Yogendra, Lawrence Melvin

Proceedings Volume 11329, 113290H (2020) https://doi.org/10.1117/12.2551731

KEYWORDS: Defect inspection, Etching, Photoresist materials, Photomasks, Stochastic processes, Dielectrics, Data modeling, Process modeling, Lithography, Metals

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Stochastic defects in the photoresist profile are one of the main yield limiters in EUV lithography patterning. These stochastic defects can be, for example, local resist loss, resist profile footing, or resist scumming. A subset of these defects is transferred through the hardmask open (HMO) patterning, leading ultimately to electrical opens and shorts. We use on-wafer data and process recipes to inform a physical etch model of the HMO process. This model is tested and confirmed by comparison to additional on-silicon data. The established model provides a visualization of the defect transfer through individual process steps and highlights critical patterning steps that may limit electrical yield. For example, a change in in-situ deposition time is observed to be more sensitive than oxide open or planarization film open times both in the model and on-wafer. This provides us the insight to focus tuning deposition step times to reduce defectivity and improve process performance. Furthermore, this model provides insight into the type of defects which are eliminated during specific patterning steps, and the type of defects which are persistent and ultimately lead to electrical opens and shorts. To characterize these defects, we plant intentional defects with varying dimensions and study which ones stay through the entire HMO process and which ones are eliminated. This insight helps better understand the HMO process, which may lead in the future to further process improvements.

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