13 March 2018 Assessment of local variability by high-throughput e-beam metrology for prediction of patterning defect probabilities
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Abstract
We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.
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Fuming Wang , Fuming Wang , Stefan Hunsche, Stefan Hunsche, Roy Anunciado, Roy Anunciado, Antonio Corradi , Antonio Corradi , Hung Yu Tien, Hung Yu Tien, Peng Tang, Peng Tang, Junwei Wei, Junwei Wei, Yongjun Wang, Yongjun Wang, Wei Fang, Wei Fang, Patrick Wong, Patrick Wong, Anton van Oosten, Anton van Oosten, Koen van Ingen Schenau, Koen van Ingen Schenau, Bram Slachter, Bram Slachter, } "Assessment of local variability by high-throughput e-beam metrology for prediction of patterning defect probabilities", Proc. SPIE 10585, Metrology, Inspection, and Process Control for Microlithography XXXII, 1058525 (13 March 2018); doi: 10.1117/12.2297603; https://doi.org/10.1117/12.2297603
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