Lithography Light Source Image Optimization for Critical Patterns
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Solution Overview
Problem
Conventional light source images in lithography techniques are limited in shape and require extensive trial and error to achieve high-precision pattern resolution, failing to meet the requirements of increasingly smaller circuit elements in semiconductor manufacturing.
Innovation Solution
A light source optimization apparatus and method utilizing an ant colony optimization (ACO) algorithm, combined with deep learning (DL), to adjust initial light source images based on critical pattern data, optimizing the light source image to achieve high-precision patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional light source images (circular, annular, quasar, or dipole) are used in lithography, then the existing lithography process can be maintained, but the precision of pattern formation deteriorates and requires long trial and error periods
Solution Approach 1:
The invention changes the parameters of the light source image by generating optimized light source images with specific intensity distributions and shapes using computational algorithms. These optimized parameters enable precise pattern formation for small line widths without requiring extensive trial and error, directly resolving the contradiction between precision and time consumption.
2Adaptability or versatility
If conventional light source images are used, then the existing lithography system can operate, but the adaptability to meet precise requirements of smaller circuit elements is insufficient
Solution Approach 1:
The invention makes the light source image dynamic and adaptable by using computational algorithms to generate optimized light source images tailored to specific pattern requirements. This allows the system to adapt to different circuit element sizes and precision requirements, overcoming the limitation of fixed conventional light source shapes.
3Productivity
If the line width of the pattern is reduced to achieve smaller circuit elements, then the integration density increases, but the sensitivity to the light source image increases requiring higher precision
Solution Approach 1:
The invention performs preliminary optimization of the light source image using computational algorithms before the actual lithography process. By pre-calculating and generating optimized light source images that account for the specific pattern requirements and small line widths, the system achieves high precision without requiring extensive adjustments during production, thus enabling high integration density.
Data Source
AI summary
The invention provides a light source optimization apparatus including a storage apparatus and a processor. The storage apparatus stores a plurality of modules. The processor is coupled to the storage apparatus and configured to execute the plurality of modules. The plurality of modules include a critical pattern module and a light source optimization module. The critical pattern module retrieves critical pattern data. The light source optimization module executes an ant colony optimization (ACO) algorithm according to a preset parameter to adjust an initial light source image to generate an output light source image, and the initial light source image corresponds to the critical pattern data.