Sub-Resolution Assist Feature Checking for Iso-Dense Bias Correction
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Solution Overview
Problem
Conventional semiconductor fabrication methods fail to ensure proper positioning and sizing of sub-resolution assist features (SRAFs) in mask layouts, leading to incorrect pattern formation in photo-sensitive materials due to iso-dense bias issues.
Innovation Solution
A method and system that divide each edge of main features in a mask layout into sections, search for adjacent features within a specified distance, flag unassisted segments, and store segment data to classify features based on the number of unassisted segments, determining a pass/fail level for each feature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If SRAFs are added to correct iso-dense bias, then manufacturing precision of pattern formation is improved, but device complexity of mask layout increases
Solution Approach 1:
The patent segments the mask layout into main features and SRAF features, and further divides edges into sections for systematic checking. This segmentation allows the complex mask layout to be managed through structured analysis of individual components and their relationships.
Solution Approach 2:
The patent implements a feedback mechanism by checking the mask layout for proper SRAF positioning and sizing, identifying unassisted segments, and providing a risk priority profile. This feedback loop ensures that SRAFs are correctly placed to eliminate iso-dense bias while maintaining pattern formation accuracy.
2Manufacturing precision
If SRAFs are made larger to create denser mask pattern, then manufacturing precision is improved, but reliability of non-printing property deteriorates
Solution Approach 1:
The patent replaces physical trial-and-error mask fabrication with an automated computational checking system. The system uses algorithmic analysis to verify SRAF dimensions and positioning, ensuring they remain within the critical threshold for non-printing while maintaining their density-correcting function.
Solution Approach 2:
The patent employs a systematic searching mechanism that radiates from each edge section to detect features within a specified distance. This creates a controlled detection zone that verifies SRAF placement without requiring physical mask iteration.
3Manufacturing precision
If manual checking of SRAF positioning is performed, then manufacturing precision can be verified, but productivity of mask fabrication decreases
Solution Approach 1:
The patent implements a self-service checking system where the mask layout automatically verifies its own SRAF positioning and sizing. The system divides edges into sections, searches for adjacent features, flags unassisted segments, and generates a risk priority profile without requiring external manual intervention, thus maintaining both precision and productivity.
Solution Approach 2:
The patent transforms the checking process from manual visual inspection to automated parameter-based analysis. By defining specific parameters such as section division, search distance, and flagging criteria, the system enables rapid computational verification of SRAF placement accuracy.
4Manufacturing precision
If comprehensive checking of all mask features is performed, then manufacturing precision is improved, but loss of time in the fabrication process increases
Solution Approach 1:
The patent applies local quality by focusing the checking process specifically on edge sections and their adjacent segments where SRAF positioning is critical. Rather than uniformly analyzing the entire mask layout, the system concentrates computational resources on regions where iso-dense bias correction is most needed, reducing overall checking time while maintaining precision.
Solution Approach 2:
The patent implements partial action by checking only the necessary portions of the mask layout - specifically edge sections and their adjacent segments within a specified distance. This selective approach avoids redundant checking of areas where SRAF placement is not critical, reducing time loss while ensuring adequate verification of pattern correspondence.
Data Source
AI summary
In accordance with the invention, there is provided a system and method for checking a mask layout including sub-resolution assist features (SRAFs). A checking program divides each edge of each main feature into sections, forms a set of segments by searching perpendicularly over a distance to determine if any portion of a feature is located within the distance. Segments are then flagged based on whether a feature located within proximity to that segment. A classification program may then classify each of the main features based on the segment data.