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Proceedings Paper

Model-based calculation of weighting in OPC model calibration
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Paper 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.

Paper Details

Date Published: 24 March 2006
PDF: 7 pages
Proc. SPIE 6152, Metrology, Inspection, and Process Control for Microlithography XX, 615202 (24 March 2006); doi: 10.1117/12.656568
Show Author Affiliations
Mohamed Talbi, IBM Corp. (United States)
Amr Abdo, IBM Corp. (United States)
Daniel Fischer, IBM Corp. (United States)
Geng Han, IBM Corp. (United States)
Scott Mansfield, IBM Corp. (United States)
James Oberschmidt, IBM Corp. (United States)
Ramya Viswanathan, IBM Corp. (United States)


Published in SPIE Proceedings Vol. 6152:
Metrology, Inspection, and Process Control for Microlithography XX
Chas N. Archie, Editor(s)

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