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Pixel-based simultaneous source and mask optimization for resolution enhancement in optical lithography.

Xu Ma1, Gonzalo R Arce

  • 1Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA. maxu@udel.edu

Optics Express
|April 1, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces efficient simultaneous source and mask optimization (SMO) for semiconductor lithography. These advanced methods jointly optimize source and mask patterns, enhancing resolution and pattern fidelity beyond traditional techniques.

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Area of Science:

  • Semiconductor manufacturing
  • Optical lithography
  • Computational imaging

Background:

  • Optical proximity correction (OPC) and phase-shifting mask (PSM) are critical resolution enhancement techniques (RET) in semiconductor manufacturing.
  • Traditional RETs often fix the light source, limiting mask pattern optimization flexibility.

Purpose of the Study:

  • To develop computationally efficient, pixel-based simultaneous source mask optimization (SMO) methods.
  • To leverage the synergy between source and mask pattern optimization for both OPC and PSM.
  • To enhance pattern fidelity and resolution in optical lithography.

Main Methods:

  • Utilizing a Fourier series expansion model to represent partially coherent systems as sums of coherent systems.
  • Employing cost sensitivity analysis to minimize output pattern error during optimization.
  • Incorporating topological constraints into the optimization framework to improve manufacturability.

Main Results:

  • Demonstration of computationally efficient SMO algorithms for advanced lithography.
  • Successful joint optimization of source and mask patterns, yielding improved resolution and fidelity.
  • Validation of the effectiveness of topological constraints for manufacturability.

Conclusions:

  • The proposed SMO methods offer a powerful approach to overcoming limitations of traditional RETs.
  • Joint optimization of source and mask patterns provides greater design freedom and improved lithographic performance.
  • The integration of topological constraints enhances the practical applicability of SMO in semiconductor manufacturing.