20 April 2011 Fast and accurate calibration for OPC process-window model using inverse weight algorithm
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Abstract
A data-set comprising of lines and spaces was collected by inline scanning electron microscope at a single measurement threshold. Input data included measurements from features of several sizes at a range of pitch values as well as the entire Bossung curve for certain critical features. Models were calibrated with and without scaling of cost weight. Weights were scaled using inverse weight algorithm based on the differential sensitivity to focus for various feature types to a given lithography system. The imaging and the resist empirical parameters were extracted by regression over the entire data-set and a truncated version of the same data-set. The through-focus fitting error reduced by over 50% from +/- 5% to 2% with the cost weights scaled using the inverse weight algorithm. The quickness combined with the ability to extract fitting parameters precisely using this technique has enabled implementation on various digital and analog layers ranging from 180nm to 65nm nodes.
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Ashesh Parikh, Ashesh Parikh, } "Fast and accurate calibration for OPC process-window model using inverse weight algorithm", Proc. SPIE 7971, Metrology, Inspection, and Process Control for Microlithography XXV, 79710P (20 April 2011); doi: 10.1117/12.877489; https://doi.org/10.1117/12.877489
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