Photolithography Mask Defect Detection via Plausible Aerial Image Design
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Solution Overview
Problem
Current defect detection methods for photolithography masks, particularly die-to-database and die-to-die methods, face challenges in accuracy and computation time due to variations in image acquisition parameters and the difficulty in comparing aerial images to reference datasets, especially with repeater defects.
Innovation Solution
A method involving acquiring an aerial image of a photolithography mask, generating a plausible design by solving an optimization problem to minimize deviation from the acquired image, and comparing this design to an underlying design to detect defects, utilizing optical systems, machine learning models, and physical models to enhance accuracy and reduce computation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If die-to-database or die-to-die methods are used for defect detection, then defect detection capability is provided, but accuracy deteriorates due to variations in image acquisition parameters and difficulty in comparing aerial images to reference datasets
Solution Approach 1:
The patent introduces an intermediary optimization process that generates a plausible design from the acquired aerial image. This plausible design serves as a mediator between the acquired image and the reference database, enabling accurate defect detection by comparing the plausible design against the reference dataset rather than directly comparing aerial images with different acquisition parameters
Solution Approach 2:
The patent applies parameter changes by solving an optimization problem that adjusts design parameters to minimize deviation between the simulated aerial image of the plausible design and the acquired aerial image. This transformation accounts for variations in image acquisition parameters and enables accurate comparison across different imaging conditions
2Reliability
If conventional defect detection methods are used, then defect detection is performed, but computation time increases due to the complexity of comparing aerial images with reference datasets
Solution Approach 1:
The patent performs preliminary action by generating the plausible design and solving the optimization problem before the actual defect detection comparison. This pre-processing step creates an optimized representation that simplifies subsequent defect detection operations, reducing overall computation time while maintaining reliability
3Loss of information
If aerial images are acquired for defect detection, then defect information is obtained, but image quality varies due to different acquisition parameters affecting comparison accuracy
Solution Approach 1:
The patent compensates for acquisition parameter variations by solving an optimization problem that transforms the acquired aerial image into a plausible design with optimized parameters. This parameter transformation makes the defect detection process adaptable to different acquisition conditions while minimizing information loss during comparison
Data Source
AI summary
The invention relates to a method for detecting defects in a photolithography mask, the method comprising: i. Acquiring an aerial image of the photolithography mask; ii. Obtaining an underlying design of the photolithography mask; iii. Generating a plausible design of the acquired aerial image by solving an optimization problem that minimizes the deviation of a simulated aerial image of the plausible design from the acquired aerial image; and iv. Detecting defects in the photolithography mask by comparing the underlying design to the plausible design. The invention also relates to a corresponding system for detecting defects.