This paper presents kernel convolution with pattern matching (KCPM), which is an updated version of fast-CAD pattern matching for assessing lithography process variations. With KCPM, kernels that capture lateral feature interaction between features due to process variations are convolved with a mask layout to calculate a match factor, which indicates approximate change in intensity at the target location. The algorithm incorporates a custom source, a mask with electromagnetic effects, and an arbitrary pupil function. For further accuracy improvement, we introduce a source splitting technique. Though the evaluation speed is decreased, R² correlation of the match factor and change in intensity is increased. Results are shown with R² correlation as high as 0.99 for nearly coherent and annular illumination. Additionally, with a numerical aperture of 1.35, unbalanced quadrapole illumination, 10mλ RMS random aberration in projection optics and complex mask with EMF effects included, R² correlation of more than 0.87 is achieved. This process is extremely fast (40μs per location) making it valuable for a wide range of applications, most commonly hot spot detection and optimization.

Date Published: 10 March 2010
PDF: 11 pages
Proc. SPIE 7640, Optical Microlithography XXIII, 764031 (10 March 2010); doi: 10.1117/12.846630

Published in SPIE Proceedings Vol. 7640:
Optical Microlithography XXIII
Mircea V. Dusa; Will Conley, Editor(s)