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This paper will propose standard methodologies for analyzing common lithographic data in three areas: photoresist contrast curves, swing curves, and focus-exposure matrices. For most data types, physics-based algebraic equations will be proposed to fit the data. The coefficients of these equation will offer physical insight into the meaning and nature of the data. The equations will be fit to the data using standard non-linear least-squares fitting algorithms with standard statistical test for removing data flyers and options for weighting the data. Analysis of the resulting curve fits will provide important information about the data. For the case of contrast curve data, the curve fits will yield resist contrast and dose-to-clear results. For swing curves, the swing ratio, period and the positions of the minimums and maximums will be provided. For focus- exposure data, process windows will be generated based on resist profile specifications. These process windows will then be analyzed by fitting rectangles or ellipses inside the window and determining the resulting exposure latitude/depth of focus trade-of. By specifying the desired exposure latitude, for example, the depth of focus and the best focus and best exposure to yield this maximum depth of focus will be calculated. Multiple process window overlaps can also be analyzed.
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Chris A. Mack, Sven Jug, Dale A. Legband, "Data analysis for photolithography," Proc. SPIE 3677, Metrology, Inspection, and Process Control for Microlithography XIII, (14 June 1999); https://doi.org/10.1117/12.350829