Enabling full-field physics-based optical proximity correction via dynamic model generation

Michael Lam; Chris Clifford; Ananthan Raghunathan; Germain Fenger; Kostas Adam

doi:10.1117/1.JMM.16.3.033502

25 July 2017 Enabling full-field physics-based optical proximity correction via dynamic model generation

Michael Lam, Chris Clifford, Ananthan Raghunathan, Germain Fenger, Kostas Adam

Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 16, Issue 3, 033502 (July 2017). https://doi.org/10.1117/1.JMM.16.3.033502

Abstract

As extreme ultraviolet lithography becomes closer to reality for high volume production, its peculiar modeling challenges related to both inter and intrafield effects have necessitated building an optical proximity correction (OPC) infrastructure that operates with field position dependency. Previous state-of-the-art approaches to modeling field dependency used piecewise constant models where static input models are assigned to specific x/y-positions within the field. OPC and simulation could assign the proper static model based on simulation-level placement. However, in the realm of 7 and 5 nm feature sizes, small discontinuities in OPC from piecewise constant model changes can cause unacceptable levels of edge placement errors. The introduction of dynamic model generation (DMG) can be shown to effectively avoid these dislocations by providing unique mask and optical models per simulation region, allowing a near continuum of models through the field. DMG allows unique models for electromagnetic field, apodization, aberrations, etc. to vary through the entire field and provides a capability to precisely and accurately model systematic field signatures.

Citation Download Citation

Michael Lam, Chris Clifford, Ananthan Raghunathan, Germain Fenger, and Kostas Adam "Enabling full-field physics-based optical proximity correction via dynamic model generation," Journal of Micro/Nanolithography, MEMS, and MOEMS 16(3), 033502 (25 July 2017). https://doi.org/10.1117/1.JMM.16.3.033502

Received: 20 March 2017; Accepted: 5 July 2017; Published: 25 July 2017

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