Mesoscopic Defect Detection in Reticle Inspection
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Solution Overview
Problem
Current defect detection methods in reticles and photomasks are inadequate for detecting mesoscopic defects, which can lead to yield-limiting or yield-killing consequences due to their limited sensitivity and inability to handle defects on a scale comparable to the processing patch.
Innovation Solution
A method and system that acquire images of reference and test dies, divide them into portions, reduce sizing differences, and detect defects by generating a graphical display map of differences in image intensity, capable of detecting mesoscopic scale defects using transmitted or reflected light, and calibrating theoretically modeled dies to derive bias parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional defect detection methods are used, then defects on the order of 101 to 102 nm length scale can be detected, but mesoscopic defects with length scales comparable to a processing patch cannot be detected
Solution Approach 1:
The patent divides the reticle into multiple processing patches and further segments each patch into sub-regions for comparative analysis. This segmentation enables the detection system to analyze different spatial scales simultaneously - detecting both small defects (101-102 nm) within sub-regions and larger mesoscopic defects (comparable to processing patch size) across the entire patch, thereby resolving the contradiction between detection sensitivity and detection range coverage
2Manufacturing precision
If dynamic compensation algorithms are applied to reduce tool noises and plate noises, then feature sizing differences between test die and reference die can be compensated, but the capability to detect mesoscopic defects is lost
Solution Approach 1:
The patent introduces an intermediary reference die that is imaged under identical conditions to the test die. By comparing the test die against this intermediary reference and then against a database die, the system maintains the ability to detect mesoscopic defects while still applying dynamic compensation for feature sizing differences. The intermediary reference acts as a mediator that preserves defect detection capability while enabling precision compensation
3Device complexity
If existing defect detection methods are used, then small fraction of defective pixels can be identified, but mesoscopic defects resulting from photomask writing errors cannot be detected
Solution Approach 1:
The patent extends defect detection from the traditional single-die dimension to a multi-dimensional approach by imaging and comparing multiple dies (test die, intermediary reference die, database die) under identical conditions. This dimensional expansion allows the system to maintain relatively simple detection algorithms while significantly improving defect detection sensitivity, enabling the identification of mesoscopic defects that result from photomask writing errors
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively detects mesoscopic and macroscopic defects, providing a more direct measurement of feature sizing differences and reducing sensitivity to pattern density effects, enabling detection in both die-to-die and die-to-database inspection modes.
Implementation Method 1
The first image and/or second image is acquired using transmitted light or reflected light
Implementation Method 2
The first image and/or second image is acquired using transmitted light or reflected light
Data Source
AI summary
In some embodiments, a method and/or system may include detecting defects in photomasks. The method may include acquiring a first image of a first die. The method may include acquiring a second image of a second die. In some embodiments, the method may include dividing the first and the second image into a number of first and second portions respectively. The method may include reducing one or more differences in sizing of the first and the second portions. In some embodiments, the method may include determining a difference in a function derived from an image intensity between the corresponding first and second portions. The method may include summing the differences in the function between the corresponding first and second portions. The method may include detecting mesoscopic scale defects in the second die.