Share Email Print
cover

Proceedings Paper

Source optimization using particle swarm optimization algorithm in photolithography
Author(s): Lei Wang; Sikun Li; Xiangzhao Wang; Guanyong Yan; Chaoxing Yang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In recent years, with the availability of freeform sources, source optimization has emerged as one of the key techniques for achieving higher resolution without increasing the complexity of mask design. In this paper, an efficient source optimization approach using particle swarm optimization algorithm is proposed. The sources are represented by pixels and encoded into particles. The pattern fidelity is adopted as the fitness function to evaluate these particles. The source optimization approach is implemented by updating the velocities and positions of these particles. The approach is demonstrated by using two typical mask patterns, including a periodic array of contact holes and a vertical line/space design. The pattern errors are reduced by 66.1% and 39.3% respectively. Compared with the source optimization approach using genetic algorithm, the proposed approach leads to faster convergence while improving the image quality at the same time. The robustness of the proposed approach to initial sources is also verified.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9426, Optical Microlithography XXVIII, 94261L (18 March 2015); doi: 10.1117/12.2181335
Show Author Affiliations
Lei Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Sikun Li, Shanghai Institute of Optics and Fine Mechanics (China)
Xiangzhao Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Guanyong Yan, Shanghai Institute of Optics and Fine Mechanics (China)
Chaoxing Yang, Shanghai Institute of Optics and Fine Mechanics (China)


Published in SPIE Proceedings Vol. 9426:
Optical Microlithography XXVIII
Kafai Lai; Andreas Erdmann, Editor(s)

© SPIE. Terms of Use
Back to Top