Nanometric Defect Detection via Spatial Spectrum Analysis
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Solution Overview
Problem
Current nanometric metrology methods are inadequate for detecting manufacturing process defects in nanometric structural elements, particularly in identifying relationships between spatial spectrums that indicate defects during multiple manufacturing phases.
Innovation Solution
A method involving charged particle metrology tools to obtain multiple edge measurements, generate spatial spectrums, determine relationships between these spectrums, and search for manufacturing process defects, with the ability to modify process parameters based on detected defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current nanometric metrology methods are used, then measurement capability is maintained at existing levels, but defect detection capability is insufficient
Solution Approach 1:
The patent transforms edge measurements from spatial domain to frequency domain by generating spatial spectrums. This dimensional transformation enables the system to analyze manufacturing process defects through frequency band relationships that are not apparent in the original spatial measurements, thereby improving defect detection capability while maintaining measurement precision.
Solution Approach 2:
The system changes the parameter representation from direct spatial edge measurements to spatial spectrum frequency bands. By determining relationships between different frequency bands in the spatial spectrums, the system can identify manufacturing process defects more accurately, resolving the contradiction between measurement precision and defect identification accuracy.
2Measurement precision
If multiple edge measurements are obtained and spatial spectrums are generated for each manufacturing phase, then defect detection capability is improved, but computational complexity increases
Solution Approach 1:
The patent segments the spatial spectrums into multiple frequency bands and analyzes relationships between these bands. This segmentation approach allows the system to process complex multi-phase manufacturing data by breaking it down into manageable frequency components, improving defect detection while managing computational complexity through structured analysis.
Solution Approach 2:
The system extracts specific frequency band relationships from the complete spatial spectrums to identify manufacturing process defects. By focusing on relevant frequency band relationships rather than processing all measurement data equally, the system improves defect detection capability while reducing unnecessary computational complexity.
3Manufacturing precision
If real-time defect detection is implemented through spatial spectrum analysis, then manufacturing precision is improved, but processing time increases
Solution Approach 1:
The patent performs spatial spectrum generation and frequency band relationship analysis as part of the manufacturing process monitoring. By implementing this analysis during or immediately after manufacturing phases, the system enables real-time defect detection that improves manufacturing precision without significant time loss, as the computational work is integrated into the existing manufacturing workflow.
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 effective detection of manufacturing process defects by analyzing spatial spectrums, allowing for real-time adjustments to manufacturing parameters, thereby improving the precision and yield of nanometric structural elements.
Implementation Method 1
A charged particle metrology tool may be used to obtain multiple edge measurements
Data Source
AI summary
A system, computer program product and a method for detecting manufacturing process defects, the method may include: obtaining multiple edge measurements of one or more structural elements after a completion of each one of multiple manufacturing phases; generating spatial spectrums, based on the multiple edge measurements, for each one of the multiple manufacturing phases; determining relationships between bands of the spatial spectrums; and identifying at least one of the manufacturing process defects based on the relationships between the bands of the spatial spectrums.