Nanoimprint Lithography Template Inspection via Luminance Correction
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Solution Overview
Problem
Current inspection methods for nanoimprint lithography templates struggle to detect defects due to the inability to resolve microstructures smaller than the light source wavelength, leading to inaccurate defect detection and prolonged imaging times, especially when the template's microstructure dimension varies within the plane.
Innovation Solution
An inspection method and apparatus that apply light to the template, calculate and correct luminance deviations in images of repetitive patterns unresolvable with the light source, allowing for accurate comparison and defect detection by normalizing luminance values to match reference averages, thereby enhancing defect identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an inspection apparatus uses a light source to image a template with microstructures smaller than the light source wavelength, then the inspection can be performed with conventional equipment, but the microstructure cannot be resolved and luminance values fluctuate making defect detection difficult
Solution Approach 1:
The patent applies preliminary action by calculating luminance deviations from a first image before acquiring the second image for defect detection. The processor calculates deviations of luminance values with respect to first regions in the first pattern, then uses these pre-calculated deviations to correct luminance values in the second image. This preliminary calculation enables accurate defect detection even when microstructures are unresolvable, as the correction compensates for luminance fluctuations caused by dimensional variations in repetitive patterns.
2Productivity
If imaging is performed with a light source wavelength larger than the microstructure dimension, then conventional inspection equipment can be used, but imaging time becomes excessively long
Solution Approach 1:
The patent performs preliminary action by acquiring a first image and calculating luminance deviations before acquiring the second image for defect detection. This pre-calculation of deviation values enables rapid correction of luminance fluctuations in the second image, allowing defect detection to be performed efficiently without requiring excessively long imaging times or multiple repeated acquisitions.
3Adaptability or versatility
If the dimension or dimensional ratio of repetitive patterns varies within the template plane, then the template can accommodate design variations, but luminance values of gray level fluctuate causing reference gray level to differ between comparison images
Solution Approach 1:
The patent applies local quality by calculating and correcting luminance deviations for each first region individually within the first pattern. The processor calculates the deviation of luminance values with respect to each first region, then corrects luminance values in the second image based on these localized deviations. This region-specific correction approach accounts for local variations in dimensional ratios while maintaining consistent reference levels for defect detection across the entire template.
Solution Approach 2:
The patent performs preliminary action by calculating luminance deviations from a first image before acquiring the second image for defect detection. The processor calculates deviations of luminance values with respect to first regions in the first pattern, then uses these pre-calculated deviations to correct luminance values in the second image. This preliminary calculation enables accurate defect detection even when microstructures are unresolvable, as the correction compensates for luminance fluctuations caused by dimensional variations in repetitive patterns.
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 efficient detection of defects in nanoimprint lithography templates by correcting luminance variations, improving the accuracy of defect identification and reducing imaging time, even for microstructures below the light source's resolution limit.
Implementation Method 1
receiving light from the inspection target to obtain a first image of the inspection target by a sensor
Data Source
AI summary
An inspection method according to the embodiments includes applying light of a light source to an inspection target; receiving light from the inspection target to obtain a first image of the inspection target by a sensor; based on an image of a first pattern comprising repetitive patterns unresolvable with a wavelength of the light source in the first image, calculating a deviation of luminance values with respect to each of first regions in the first pattern by a processor; obtaining a second image of the inspection target by the sensor; correcting luminance values of the second image by the processor based on the deviations of the luminance values; and comparing the repetitive patterns of the corrected second image with each other by a comparer.