Sub-Resolution Assist Feature Repair Flow
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Solution Overview
Problem
Current resolution enhancement techniques, such as optical proximity correction (OPC) and sub-resolution assist features (SRAFs), struggle to accurately reproduce complex layouts in microcircuit manufacturing due to issues like non-convergence of edges, mask rule constraint limitations, and SRAF placement errors, leading to potential print errors and increased computational intensity.
Innovation Solution
An iterative OPC repair flow is implemented, which detects and corrects sub-resolution assist feature errors by forming regions around errors and applying OPC processes with varying parameter sets, employing rule-based, model-based, or inverse lithography techniques to refine the layout design data, thereby addressing print errors and improving fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If optical proximity correction and sub-resolution assist features are used to enhance resolution, then manufacturing precision is improved, but device complexity increases due to multiple correction passes and parameter adjustments
Solution Approach 1:
The patent applies preliminary action by performing automated SRAF repair before final lithography. The system proactively identifies and corrects SRAF errors using rule-based, model-based, or inverse lithography techniques, preventing print defects before they occur rather than requiring post-lithography corrections
Solution Approach 2:
The patent implements feedback through iterative OPC repair flows that detect errors, apply corrections, and verify results. The system uses feedback from error detection to adjust SRAF parameters and positioning in subsequent iterations, continuously improving pattern accuracy while automating the correction process
2Manufacturing precision
If iterative OPC repair with multiple parameter sets is applied, then manufacturing precision improves, but processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the layout into regions containing SRAF errors and processing only those segments. The system identifies specific error locations and applies OPC corrections locally rather than reprocessing the entire layout, significantly reducing computational time while maintaining precision
Solution Approach 2:
The patent uses partial action by applying OPC corrections only to areas with detected SRAF errors rather than performing full-layout corrections. The system performs targeted repairs on affected regions using varying parameter sets, achieving necessary precision without the computational overhead of complete iterative processing
3Manufacturing precision
If sub-resolution assist features are added to enhance pattern reproduction, then manufacturing precision improves, but error detection difficulty increases due to complex layout modifications
Solution Approach 1:
The patent implements feedback mechanisms that automatically detect SRAF errors by comparing actual lithographic output with intended patterns. The system uses this feedback to identify misplaced or missing SRAFs and triggers automated repair processes, making error detection systematic rather than relying on manual inspection
Solution Approach 2:
The patent applies self-service by enabling the OPC system to automatically detect and repair its own errors. The system identifies SRAF placement mistakes and corrects them using integrated repair algorithms, eliminating the need for external manual detection and correction processes
Data Source
AI summary
After layout design data has been modified using a resolution enhancement process, a repair flow is initiated. This repair flow includes checking a layout design altered by a resolution enhancement process for errors. A repair process is performed to correct detected sub-resolution assist feature errors. The repair process may employ a rule-based sub-resolution assist feature technique, a model-based sub-resolution assist feature technique, an inverse lithography-based sub-resolution assist feature technique, or any combination thereof.