Paper
24 March 2006 Model-based calculation of weighting in OPC model calibration
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Abstract
Optimal Proximity Correction (OPC) models are calibrated with Scanning Electron Microscope (SEM) data where the measurement uncertainty vary among pattern types (i.e., line versus space, 1D versus 2D and small versus large). The quality of the SEM measurement uncertainty's impact on OPC model integrity is mitigated through a weighting scheme. Statistical methods such as relating the weight to the SEM measurements standard deviation require more measurements per calibration structure than economically feasible. Similarly, the use of experience and engineering judgment requires many iterations before some reasonable weighting scale is determined. In this paper we present the results of OPC model fitness statistics associated with metrology based weights (MtBW) versus model based weights (MBW). The motivation for the latter approach is the promise for an unbiased, consistent, and efficient estimate of the model parameters.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohamed Talbi, Amr Abdo, Daniel Fischer, Geng Han, Scott Mansfield, James Oberschmidt, and Ramya Viswanathan "Model-based calculation of weighting in OPC model calibration", Proc. SPIE 6152, Metrology, Inspection, and Process Control for Microlithography XX, 615202 (24 March 2006); https://doi.org/10.1117/12.656568
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Cited by 5 scholarly publications and 1 patent.
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KEYWORDS
Optical proximity correction

Calibration

Data modeling

Scanning electron microscopy

Statistical modeling

Model-based design

Error analysis

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