光学接近校正
热点(地质)
计算机科学
计量学
薄脆饼
人工智能
算法
光学
工程类
地质学
物理
电气工程
过程(计算)
地球物理学
操作系统
作者
Chih-I Wei,Seul-Ki Kang,Sayantan Das,Masahiro Oya,Yosuke Okamoto,Kotaro Maruyama,Germain Fenger,Azat Latypov,Ir Kusnadi,Gurdaman Khaira,Yuichiro Yamazaki,Werner Gillijns,Sandip Halder,Gian F. Lorusso
出处
期刊:Journal of micro/nanopatterning, materials, and metrology
[SPIE - International Society for Optical Engineering]
日期:2023-10-19
卷期号:22 (04)
标识
DOI:10.1117/1.jmm.22.4.041603
摘要
BackgroundFor complex two-dimensional (2D) patterns, optical proximity correction (OPC) model calibration flows cannot always satisfy accuracy requirements with the standard cutline-based input data. Utilizing after-development inspection e-beam metrology image contours, better model predictions of 2D shapes and wafer hotspots can be realized.AimWe compare model accuracy performance of conventional cutline-based and contour-based OPC models on the regular and hotspots patterns.ApproachBy utilizing image contours that are directly extracted from large field of view (LFoV) e-beam metrology, OPC models were calibrated and verified with both cutline-based and contour-based modeling flows. We also used a wafer sampling plan that contained bridging hotspots. Using that sampling plan, a hotspot-aware three-dimentional resist (R3D) compact model was created.ResultsFirst, a contour-based OPC model was generated with <1 nm root mean square error of contour sites. Compared with cutline-based models, it shows better predictions on 2D feature corners. Second, when combined with a hotspot sampling plan, a hotspot-aware compact model could be generated. The accuracy of hotspot predictions on false positives and false negatives was reduced to around 1% with this approach.ConclusionsOPC model calibration and verification with LFoV image contours provide improved predictions on corner rounding shapes and great potential to increase design space coverage. We also observed improved accuracy of hotspot predictions when using an update hotspot aware model when comparing with that of the OPC model. Furthermore, the combination of R3D and stochastic compact models also demonstrated great potential on predictions of rare wafer failure events.
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