Electron Beam ROI Stitching for Faster Metrology Imaging
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Solution Overview
Problem
Current electron beam metrology tools inefficiently scan entire fields of view, wasting electrons outside the region of interest and requiring manual user input for region of interest creation, leading to variability and errors.
Innovation Solution
A system and method to focus electron scans to predefined regions of interest using polygonal dimensions, automatically creating and stitching images to form a synthetic field of view, reducing electron usage and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the electron beam scans the entire field of view, then complete coverage of the target area is achieved, but electron usage efficiency deteriorates because electrons are wasted outside the region of interest
Solution Approach 1:
The patent divides the field of view into multiple regions of interest (ROIs) based on predefined rules. Instead of scanning the entire field of view, the system identifies and scans only specific regions containing features of interest, such as alignment marks or pattern features. This segmentation approach reduces electron beam usage by focusing only on necessary areas while maintaining complete measurement capability through strategic ROI selection.
2Reliability
If manual user input is used to create regions of interest, then flexibility in selecting measurement areas is achieved, but user variability and errors increase
Solution Approach 1:
The patent implements automated region of interest creation using predefined rules that the system applies independently of user intervention. The system automatically identifies ROIs based on target design rules, feature geometry, and measurement requirements. This self-service approach eliminates user variability and errors in ROI definition while maintaining the flexibility to adapt to different measurement scenarios through programmable rules.
3Loss of energy
If the electron beam scans only the region of interest, then electron usage efficiency improves, but the complexity of stitching multiple images increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining the rules and parameters for region of interest identification before the actual scanning begins. The system pre-calculates ROI boundaries, selects appropriate scan regions, and prepares stitching parameters in advance. This preliminary action simplifies the overall process by establishing clear guidelines for ROI selection and image stitching, reducing the complexity that would otherwise arise from real-time decision-making.
4Productivity
If the entire field of view is scanned, then all target features are captured in a single image, but the time required for image acquisition increases
Solution Approach 1:
The patent segments the field of view into multiple regions of interest and scans each region separately instead of scanning the entire field of view in a single pass. By dividing the scanning task into smaller, targeted segments, the system reduces the total electron beam exposure time and electron consumption while maintaining complete feature capture capability through coordinated ROI scanning and stitching.
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
Enhances electron beam inspection efficiency by 20-60% and reduces cost of ownership through 60% less electron usage and 50% improvement in image acquisition time, while maintaining accuracy and eliminating user-induced errors.
Implementation Method 1
the target image is grabbed by deflecting the eBeam from one pixel to the other to raster the entire image and the emitted electrons are captured using detectors and converted to a grayscale image
Data Source
AI summary
Systems and methods provide for localizing a beam to a plurality of regions of interest for creating a synthetically stitched image. The process includes creating at least a first region of interest of a target and at least a second region of interest of the target, each of the first region of the target and the second region of interest defined by one or more previously established rules for polygonal dimensions. Next, performing a first scan of the target to capture at least one first image of the first region of interest and performing a second scan of the target to capture at least one second image of the second region of interest occurs. The captured images are then stitched together to create a stitched final image of the target.