EUV Illumination System Configuration Optimization
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Solution Overview
Problem
Existing EUV illumination systems face challenges in optimizing the configuration of EUV point sources to achieve maximum fitness values for aerial images, which affects the performance and efficiency of EUV exposure processes.
Innovation Solution
A method is developed to configure an EUV illumination system by generating aerial images through optical simulations for each EUV point source, summing these images based on EUV mapping, and searching for a combination of EUV point sources that maximizes a fitness value, thereby optimizing the system configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optical simulation methods are used for EUV illumination system configuration, then comprehensive aerial image analysis can be achieved, but the computation time becomes excessively long
Solution Approach 1:
The patent divides the continuous illumination source into multiple discrete point sources, allowing the aerial image to be calculated as a superposition of individual point source contributions. This segmentation enables selective computation for different source positions and combinations, significantly reducing the overall simulation time while maintaining comprehensive aerial image analysis capability.
Solution Approach 2:
The patent pre-calculates and stores aerial images for individual point sources before the actual optimization process. These pre-computed aerial images are then reused during fitness evaluation, eliminating the need to perform full optical simulations repeatedly during the optimization iterations, thus dramatically reducing computation time.
2Illumination intensity
If the number of EUV point sources is increased to improve illumination coverage, then the illumination uniformity improves, but the system complexity and computation burden increase
Solution Approach 1:
The patent uses a finite number of discrete point sources (e.g., 5-10 points) distributed across the illumination source, which is sufficient to achieve good illumination uniformity without requiring the entire continuous source. This partial action approach achieves adequate illumination coverage while keeping the system and computation manageable.
Solution Approach 2:
The patent employs an optimization algorithm that dynamically determines the optimal positions and intensities of point sources based on the specific mask pattern and desired aerial image quality. This dynamic configuration adapts to different exposure requirements, achieving high illumination uniformity without fixed complex configurations.
3Manufacturing precision
If exhaustive search methods are used to find optimal point source combinations, then the fitness value optimization is thorough, but the computational complexity becomes unmanageable
Solution Approach 1:
The patent focuses the optimization on local variations in point source positions and intensities rather than searching the entire configuration space exhaustively. The optimization algorithm makes localized adjustments to point source parameters based on gradient information or heuristic rules, achieving sufficient fitness optimization without the computational burden of exhaustive search.
Solution Approach 2:
The patent optimizes continuous parameters such as point source positions, intensities, and relative weights rather than searching through discrete combinatorial configurations. This parameter-based optimization transforms the combinatorial problem into a continuous optimization problem, which can be solved efficiently using gradient-based methods or other numerical optimization techniques.
Data Source
AI summary
Provided are a method of configuring an optimized extreme ultraviolet (EUV) illumination system, and an EUV exposure method using the EUV illumination system. The method of configuring the EUV illumination system includes calculating an aerial image by performing an optical simulation with respect to each of EUV point sources, summing up the aerial images based on EUV mapping, searching for a combination of the EUV point sources by using a fitness value with respect to the summed aerial image, and configuring the EUV illumination system as a combination of the EUV point sources, which has a maximum fitness value.