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22 February 2021 Better prediction on patterning failure mode with hotspot aware OPC modeling
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A method to perform Optical Proximity Correction (OPC) model calibration that is also sensitive to lithography failure modes and takes advantage of the large field of view (LFoV) e-beam inspection, is presented. To improve the coverage of the OPC model and the accuracy of the after development inspection (ADI) pattern hotspots prediction - such as trench pinching or bridging in complex 2D routing patterns - a new sampling plan with additional hotpot locations and the corresponding contours input data is introduced. The preliminary inspected hotspots can be added to the traditional OPC modeling flow in order to provide extra information for a hotspot aware OPC model. A compact optical/resist 3D modeling toolkit is applied to interpret the impact of photoresist (PR) profiles, as well as accurate predictions of hotspot patterns occurring at the top or bottom of the PR. A contour-based modeling flow is also introduced that uses a site or edge based calibration engine, to better describe hotspot locations in the hotspot aware OPC model calibration. To quantify the improvement in pattern coverage in the modeling flow, feature vectors (FVs) analysis and comparisons between the conventional and the hotspot aware OPC models is also presented.[1] The time and cost of using conventional Critical Dimension Scanning Electron Microscope (CD-SEM) metrology to measure such a large amount of CD gauges are prohibitive. By contrast, using LFoV e-beam inspection with improved training algorithm to extract fine contours from wafer hotspots, a hotspot aware OPC model can predict ADI hotspots with a higher capture rate as compared to main feature OPC model. Presumably, a hotspot-aware modeling flow based on LFoV images/contours not only benefits users by improving the capture rate of the lithography defects, but also brings the advantages to the failure mode analysis for the post-etch stage.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chih-I Wei, Stewart Wu, Yunfei Deng, Gurdaman Khaira, Ir Kusnadi, Germain Fenger, Seulki Kang, Yosuke Okamoto, Kotaro Maruyama, Yuichiro Yamazaki, Sayantan Das, Sandip Halder, Werner Gillijns, and Gian Lorusso "Better prediction on patterning failure mode with hotspot aware OPC modeling", Proc. SPIE 11611, Metrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV, 1161112 (22 February 2021);


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