Wafer Geometry Metric for Overlay Control
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Solution Overview
Problem
Current semiconductor fabrication processes face challenges in accurately characterizing and controlling wafer geometry changes, leading to misregistration and overlay errors due to in-plane distortions, which are not effectively addressed by traditional global shape metrics.
Innovation Solution
A method and system that acquire wafer shape values at multiple points, generate slope of shape change values, and calculate residual slope shape change metrics to provide improved wafer geometry metrics, enabling process tool correctables and residual slope shape change metrics for enhanced overlay and process control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional global shape metrics (warp, bow) are used to characterize wafer geometry, then measurement simplicity is maintained, but measurement precision and ability to detect localized shape variations deteriorate
Solution Approach 1:
The patent segments the wafer surface into multiple discrete measurement points and divides the shape characterization into different frequency components (low frequency global shape and high frequency localized shape variations). This allows precise detection of localized variations while maintaining systematic organization through segmentation of the measurement approach.
Solution Approach 2:
The patent introduces a new dimensional approach by adding high frequency shape components to the traditional low frequency global shape metrics. This multi-dimensional characterization (combining global warp/bow with localized high frequency variations) enables comprehensive shape analysis without requiring a single complex metric.
2Manufacturing precision
If global shape metrics are used, then ease of operation is maintained, but manufacturing precision for overlay control deteriorates
Solution Approach 1:
The patent performs preliminary characterization of both low frequency global shape and high frequency localized shape variations before the overlay measurement process. By pre-characterizing the wafer geometry at multiple frequency components, the system prepares correction data in advance that can be applied during lithography to compensate for both global and localized distortions, improving overlay precision without adding real-time complexity.
Solution Approach 2:
The patent implements feedback by using the measured high frequency shape components to generate corrections that are applied back to the lithography process. The system continuously monitors wafer shape at multiple points, compares against reference data, and adjusts patterning parameters to compensate for localized distortions, creating a closed-loop control system that improves overlay precision.
3Reliability
If traditional overlay measurement methods are used, then process simplicity is maintained, but reliability for detecting in-plane distortions deteriorates
Solution Approach 1:
The patent applies local quality by placing measurement targets and performing shape characterization at multiple localized regions across the wafer surface rather than relying on a single global measurement. This localized approach enables detection of region-specific in-plane distortions and high frequency shape variations, improving reliability of overlay error detection while maintaining systematic measurement protocols.
Data Source
AI summary
The present invention may include acquiring a wafer shape value at a plurality of points of a wafer surface at a first and second process level, generating a wafer shape change value at each of the points, generating a set of slope of shape change values at each of the points, calculating a set of process tool correctables utilizing the generated set of slope of shape change values, generating a set of slope shape change residuals (SSCRs) by calculating a slope of shape change residual value at each of the points utilizing the set of process tool correctables, defining a plurality of metric analysis regions distributed across the surface, and then generating one or more residual slope shape change metrics for each metric analysis region based on one or more SSCRs within each metric analysis region.