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22 February 2021 Optimizing focus and dose process windows for robust process control using a multi-feature analysis
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Abstract
Advancing technology nodes in DRAM continues to drive the reduction of on-product overlay (OV) budget. This gives rise to the need for OV metrology with greater accuracy. However, the ever increasing process complexity brings additional challenges related to metrology target deformation, which could contribute to a metrology error. Typically, an accurate OV measurement involves several engineering cycles for target and recipe optimization. In particular, process optimization in either technology development (TD) phase or high volume manufacturing (HVM) phase might influence metrology performance, which requires re-optimization. Therefore, a comprehensive solution providing accuracy and process robustness hereby minimizing the cycle time is highly desirable. In this work, we report multi-wavelength μDBO enhanced with accuracy aware pixel selection as a solution for robust OV measurement against process changes as well as improved accuracy in HVM. Accuracy aware pixel selection is capable of tackling intra-target processing variations and is established on a multi-wavelength algorithm with immunity to target asymmetry impact. DRAM use cases in FEOL critical layers will be discussed in this paper. Superior robustness and accuracy will be demonstrated together with improved on-product OV performance, promising a process of record metrology solution in specific applications throughout the TD and HVM.
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© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philip Groeger, Ranjan Khurana, Aayush Mitra, Mycahya Eggleston, Stefan Buhl, Wan-Soo Kim, and Xaver Thrun "Optimizing focus and dose process windows for robust process control using a multi-feature analysis", Proc. SPIE 11611, Metrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV, 116111E (22 February 2021); https://doi.org/10.1117/12.2583928
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