Special Cell General Database for Optical Proximity Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing complexity of special cell structures in semiconductor design layouts leads to repetitive and resource-intensive optical proximity correction calculations, causing inefficiencies and accuracy issues in identifying and correcting special cell regions.
Innovation Solution
A special cell general database is established by identifying and categorizing minimum repeating cell patterns, which are then used to create a database for pattern correction, reducing redundant calculations and improving correction accuracy by correlating each pattern's information with its correction results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If optical proximity correction is performed on each special cell structure region individually, then correction accuracy is maintained, but calculation time and resource consumption increase significantly
Solution Approach 1:
The patent creates a database storing correction results from previously corrected special cell structure regions. When the same or similar patterns are encountered in new designs, the system retrieves and applies the stored correction results directly, avoiding redundant calculations while maintaining correction accuracy.
Solution Approach 2:
The system performs optical proximity correction on special cell structure regions in advance and stores the correction results in a database before they are needed. This preliminary action allows rapid retrieval and application of correction results during subsequent design processes, significantly reducing calculation time.
2Reliability
If optical proximity correction is performed on each special cell structure region individually, then correction completeness is ensured, but computational resources are wasted on repetitive calculations
Solution Approach 1:
The patent creates a database storing correction results from previously corrected special cell structure regions. When the same or similar patterns are encountered in new designs, the system retrieves and applies the stored correction results directly, avoiding redundant calculations while maintaining correction accuracy.
Solution Approach 2:
The system compares the current special cell structure region with previously corrected patterns in the database, identifies matches or similarities, and applies appropriate correction results. This feedback mechanism ensures correction completeness by verifying that all regions are properly addressed while avoiding redundant computational resource consumption.
3Adaptability or versatility
If special cell regions are not identified and classified, then design flexibility is maintained, but optical proximity correction efficiency decreases
Solution Approach 1:
The patent segments the design layout into different types of special cell structure regions based on their geometric and structural characteristics. This segmentation enables the system to identify, classify, and process each region type efficiently using appropriate correction strategies from the database, thereby improving optical proximity correction efficiency while maintaining design flexibility.
Solution Approach 2:
The system changes parameters such as pattern geometry, cell type, and structural characteristics to classify special cell regions into different categories. These parameter-based classifications enable efficient retrieval of corresponding correction results from the database, improving productivity without compromising design adaptability.
Data Source
AI summary
The present disclosure discloses a special cell general database, a method for establishing the special cell general database and a pattern correction method. The pattern correction method includes: providing a to-be-corrected layout including a to-be-corrected region and a to-be-corrected special cell structure region; acquiring a to-be-corrected minimum repeating cell pattern in the to-be-corrected special cell structure region; providing a special cell general database; acquiring an information of a cell correction pattern corresponding to the to-be-corrected minimum repeating cell pattern in the special cell general database; performing an optical proximity correction on the to-be-corrected region to acquire an information of a second correction pattern; acquiring a correction layout according to the information of the second correction pattern and the information of the cell correction pattern. The present disclosure can improve a correction efficiency of the pattern correction method.