Unified SMO and DP Lithography Co-Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current lithographic processes face challenges in achieving better imaging performance due to the lack of integration between Source Mask Optimization (SMO) and Double Patterning (DP) in a computationally efficient manner, as well as the need to co-optimize design layouts for optical characteristics in lithography apparatuses.
Innovation Solution
A method is introduced to integrate SMO and DP in a unified process flow, incorporating co-optimization-aware splitting of patterns for lithographic processes, which includes selecting a representative set of design layout portions to expedite the co-optimization process and optimize both the source and mask simultaneously, while considering the optical settings of the lithography apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If Source Mask Optimization (SMO) and Double Patterning (DP) are integrated in a unified process flow, then imaging performance is improved, but computational complexity increases
Solution Approach 1:
The patent segments the design layout into multiple portions and processes them separately through the unified SMO-DP flow. This allows the complex optimization to be divided into manageable chunks, reducing the computational burden while maintaining overall imaging performance improvements.
2Manufacturing precision
If co-optimization of source and mask is performed, then imaging quality is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary selection of representative design layout portions before executing the full co-optimization process. By pre-identifying critical patterns and regions that most impact imaging quality, the system can focus computational resources on these areas, achieving quality improvement while reducing overall processing time.
3Productivity
If representative set of design layout portions is selected, then computational efficiency is improved, but optimization completeness may be reduced
Solution Approach 1:
The patent applies local quality by selecting specific representative portions of the design layout that exhibit critical imaging characteristics. Rather than uniformly processing the entire layout, the system identifies and optimizes regions with the greatest impact on imaging performance, maintaining optimization completeness for critical areas while improving overall computational efficiency.
Data Source
AI summary
The present invention relates to lithographic apparatuses and processes, and more particularly to multiple patterning lithography for printing target patterns beyond the limits of resolution of the lithographic apparatus. A method of splitting a pattern to be imaged onto a substrate via a lithographic process into a plurality of sub-patterns is disclosed, wherein the method comprises a splitting step being configured to be aware of requirements of a co-optimization between at least one of the sub-patterns and an optical setting of the lithography apparatus used for the lithographic process. Device characteristic optimization techniques, including intelligent pattern selection based on diffraction signature analysis, may be integrated into the multiple patterning process flow.