Projection Exposure Aberration Mapping With Adaptive Measuring Points
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Solution Overview
Problem
Existing projection exposure systems face challenges in maintaining high imaging quality and throughput due to varying imaging aberrations across the image field, which are costly and time-consuming to measure and correct.
Innovation Solution
A method and system for optimizing measuring point distributions to efficiently gather aberration information, using customized metrology patterns that account for individual system variations and use cases, allowing for precise control of manipulators to correct aberrations while minimizing measurement time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If comprehensive aberration measurements are performed across the entire image field, then imaging quality is improved, but measurement time and cost increase
Solution Approach 1:
The image field is divided into multiple segments with different measuring point distributions assigned to different field regions. High-density measuring points are placed in regions requiring precise aberration correction, while low-density distributions are used in regions with lower requirements, thereby reducing overall measurement time while maintaining imaging quality where needed
Solution Approach 2:
Different measuring point densities are applied to different local regions of the image field based on their specific aberration characteristics and correction requirements. This localized approach ensures high measurement precision in critical areas while reducing measurement burden in less critical areas
2Ease of operation
If standardized measuring point distributions are used, then measurement process is simplified, but individual system variations cannot be adequately addressed
Solution Approach 1:
The measuring point distribution is made dynamic and adaptive rather than static and standardized. The system automatically determines optimal measuring point locations based on real-time aberration measurements and system characteristics, allowing the measurement strategy to adapt to individual system variations while maintaining operational simplicity
Solution Approach 2:
The measurement system performs self-optimization by automatically determining its own measuring point distribution based on measured aberration patterns. The system uses initial measurements to identify problematic regions and automatically concentrates measurement resources there, eliminating the need for external optimization input
Data Source
AI summary
A measuring system (MS) configured to measure a projection radiation property representing an aberration level at a plurality of spaced apart measuring points distributed in the image field; and an operating control system with at least one manipulator operatively connected to an optical element of a projection exposure system to modify imaging properties of the projection exposure system based on measurement results generated by the measuring system. In a measuring point distribution calculation (MPDC), a measuring point distribution defining a number and positions of measuring points is used. The MPDC is performed under boundary conditions representing at least: (i) manipulation capacities of the operating control system; (ii) measuring capacities of the measuring system; and (iii) predefined use case scenarios defining a set of representative use cases. Each use case corresponds to a specific aberration pattern generated by the projection exposure system under a predefined set of use conditions.