Dynamic Threshold Defect Inspection for Sub-20nm Photomasks
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Solution Overview
Problem
In photomask defect inspection, especially for patterns with a half pitch less than 20 nm, variations in illumination and pattern shape cause unstable gray scale values in inspection images, leading to inaccurate defect detection.
Innovation Solution
A defect inspection device and method that uses an image sensor to capture optical images, divides them into pixels, and a processor to calculate representative values from adjacent pixels, adjusting the defect determination threshold based on these values to stabilize defect assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed defect determination threshold is used for defect inspection, then the inspection process is simple and fast, but the inspection accuracy deteriorates when illumination amount or pattern shape varies
Solution Approach 1:
The defect determination threshold is changed from a fixed value to a dynamic value that varies according to the gray scale of the inspection image. The threshold is set to a first value when the gray scale indicates low illumination or specific pattern shapes, and to a second value when the gray scale indicates normal illumination, thereby adapting the inspection criteria to actual imaging conditions
Solution Approach 2:
The inspection parameter (defect determination threshold) is changed based on the gray scale value obtained from the inspection image. By using the gray scale as a reference, the threshold is adjusted to compensate for variations in illumination amount and pattern shape, maintaining accurate defect detection across different imaging conditions
2Reliability
If the defect determination threshold is adjusted based on gray scale values, then the inspection accuracy improves under varying conditions, but the complexity of the inspection process increases
Solution Approach 1:
The inspection system performs self-adjustment by using the gray scale value obtained from the inspection image itself to determine the appropriate defect threshold. The system automatically selects the first or second threshold value based on the measured gray scale, without requiring external calibration or manual intervention, thereby maintaining reliability while keeping the adjustment mechanism relatively simple
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
This approach enables stable and precise defect inspection by adjusting the defect determination threshold according to the gray scale values, reducing erroneous detection and improving inspection accuracy for patterns with varying illumination and shape.
Implementation Method 1
an image sensor that obtains an optical image of an inspection target region
Data Source
AI summary
A defect inspection device includes an image sensor configured to obtain an image of a target region of an object and divide the image of the target region into an array of pixels, and a processor. The processor is configured to receive a signal indicating a value of a property of the divided image, select a first pixel in the divided image, determine the value of the property of the first pixel, determine a reference pixel value for the first pixel, compare the reference pixel value to the value of the first pixel to obtain a difference value, and set a threshold difference at which a defect is assessed to be present, based at least in part on the value of the property of second pixels in the divided image adjacent to the first pixel.