Robust source and mask optimization compensating for mask topography effects in computational lithography.

Area of Science:

• Optical Lithography
• Computational Lithography
• Semiconductor Manufacturing

Background:

• Advanced optical lithography requires accurate source mask optimization (SMO) to address mask topography effects.
• Conventional SMO methods struggle with mask-induced phase errors that reduce usable depth of focus (uDOF) and process yield.
• Rigorous 3D mask models are computationally intensive.

Purpose of the Study:

• To develop an alternative SMO approach that maximizes uDOF by incorporating pupil wavefront aberrations.
• To compensate for mask topography effects in optical lithography.
• To enhance pattern fidelity and process yield.

Main Methods:

• Designed pupil wavefront function using Zernike polynomials for primary and secondary spherical aberrations.
• Applied conjugate gradient method for optimal source-mask pair under aberrated pupil conditions.
• Utilized a statistical model for Zernike coefficient determination for phase control.

Main Results:

• The proposed approach effectively compensates for mask topography effects.
• Improved pattern fidelity was observed in rigorous simulations of thick masks.
• Significant increase in usable depth of focus (uDOF) was achieved.

Conclusions:

• Incorporating pupil wavefront aberrations into SMO is a viable strategy to mitigate mask topography effects.
• The developed method enhances both pattern fidelity and uDOF, leading to improved lithographic performance.
• This technique offers a computationally efficient alternative for advanced optical lithography challenges.