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17 August 2018 Assessment of pattern variability and defectivity by large-scale SEM metrology with >100 million measurements
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Abstract
We present an experimental study of pattern variability and defectivity, based on a large data set with <112 million critical dimension (CD) and via area measurements from a Hermes Microvision Inc. (HMI) high-throughput e-beam tool. The test case is a 10-nm node static random-access memory via array patterned with a deep ultraviolet immersion litho-etch-litho-etch process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to significant differences in defectivity. The large data volume made available by high-throughput inspection capability of the HMI eP5 tool enables analysis to reliably distinguish global and local CD uniformity variations, including a breakdown into local systematics and stochastics. From a closer inspection of the tail end of the distributions and estimation of defect probabilities, we conclude that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. In addition, we studied wafer fingerprints for both global CD uniformity (GCDU) and local CD uniformity (LCDU), including stochastics. We used LCDU and GCDU wafer maps to identify correlations between those parameters and defect count. We expect that the analysis methodology presented can be applied for defect probability modeling as well as general process qualification in the future.
Fuming Wang, Stefan Hunsche, Hung Yu Tien, Peng Tang, Junwei Wei, Yongjun Wang, Wei Fang, and Patrick Wong "Assessment of pattern variability and defectivity by large-scale SEM metrology with >100 million measurements," Journal of Micro/Nanolithography, MEMS, and MOEMS 17(4), 041007 (17 August 2018). https://doi.org/10.1117/1.JMM.17.4.041007
Received: 13 April 2018; Accepted: 25 July 2018; Published: 17 August 2018
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