Slope-integrated methodology for OPC model calibration

Liang Zhu; Mark Lu; Dion King; Yili Gu; Steve Yang; Gensheng Gao

doi:10.1117/12.755663

21 November 2007 Slope-integrated methodology for OPC model calibration

Liang Zhu, Mark Lu, Dion King, Yili Gu, Steve Yang, Gensheng Gao

Proceedings Volume 6827, Quantum Optics, Optical Data Storage, and Advanced Microlithography; 682725 (2007) https://doi.org/10.1117/12.755663
Event: Photonics Asia 2007, 2007, Beijing, China

Abstract

As the semiconductor industry scales down to 90nm and below, Model-Based OPC has become a standard practice to compensate for optical proximity effects and process variations occurring when printing features below the exposure wavelength. For parametric OPC models, it is assumed that the empirical data are accurate and the model parameter space is sufficiently well sampled. In spite of advanced metrology tools, the measurement uncertainty for 1D small critical dimensions and 2D patterns remains to be a challenge. Traditionally, the weight of SEM measurement points are based on either statistical method such as standard deviations, or engineers' judgment, which is either time consuming or individual-dependent. In this paper, the slope-integrated OPC model calibration methodology is proposed, which takes into account the slope as a weighting indicator. The additional measurement objects per calibration structure are economically feasible, as most metrology tool time is spent on addressing and auto-focusing. When we consider one measurement point with both CD and slope measurements, the slightly increased time is tolerable for FAB, which requires a short turn around time (TAT). By this approach, we can distinguish measurement points with low confidence from those accurate ones. Furthermore, we check the fitting differences among equal-weighted data sheets, empiricalweighted data sheets and slope-weighted data sheets, by using the same variable threshold model form. From the edge placement error (EPE) of fitting results and the overlap between simulated contours and SEM images, it is found that the proposed slope-integrated methodology results in a more accurate and stable model.

Citation Download Citation

Liang Zhu, Mark Lu, Dion King, Yili Gu, Steve Yang, and Gensheng Gao "Slope-integrated methodology for OPC model calibration", Proc. SPIE 6827, Quantum Optics, Optical Data Storage, and Advanced Microlithography, 682725 (21 November 2007); https://doi.org/10.1117/12.755663

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KEYWORDS

Optical proximity correction

Data modeling

Calibration

Scanning electron microscopy

Metrology

Time metrology

Critical dimension metrology

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