A Hierarchical Inverse Lithography Method Considering the Optimization and Manufacturability Limit by Gradient...

Area of Science:

• * Semiconductor manufacturing and microelectronics.
• * Computational lithography and optical engineering.

Background:

• * Inverse lithography technology (ILT) utilizes gradient descent (GD) for improved lithographic imaging fidelity.
• * GD, a local optimization method, struggles with complex patterns, particularly in corner regions, due to the system's low-pass filtering effect, leading to local optima and over-optimization defects.

Purpose of the Study:

• * To enhance the efficiency and accuracy of GD-based ILT algorithms.
• * To address the limitations of GD in optimizing complex patterns, especially in corner regions.
• * To ensure the manufacturability of masks generated through ILT.

Main Methods:

• * Proposed a resolution layering method to incorporate high-frequency information from pattern corners during optimization.
• * Implemented a corner-rounding-inspired target retargeting strategy to mitigate GD's over-optimization.
• * Employed differentiable top-hat and bottom-hat operations for improved mask manufacturability and optimization efficiency.

Main Results:

• * The proposed method demonstrated higher optimization efficiency compared to existing ILT optimization techniques.
• * Successfully avoided the over-optimization defect commonly associated with GD in complex pattern optimization.
• * Numerical experiments confirmed the superiority and effectiveness of the resolution layering approach.

Conclusions:

• * The resolution layering method significantly improves GD-based ILT algorithms for complex pattern fabrication.
• * The approach offers a robust solution for enhancing lithographic imaging fidelity while ensuring mask manufacturability.
• * This work provides a valuable advancement in computational lithography for next-generation semiconductor manufacturing.