Optical Metrology for Spatial Deposition Thickness Prediction
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Solution Overview
Problem
Conventional methods for measuring substrate deposition processes are either destructive, leading to unusable substrates, or rely on erroneous assumptions about uniformity across different regions of a substrate, resulting in non-uniformity and malfunctioning substrates.
Innovation Solution
A method and system that utilize optical metrology data and structure data from a known region of a substrate to determine the growth rate of that region, and then predict the thickness data of regions without known structure data, allowing for non-destructive and accurate measurement of substrate deposition processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If destructive metrology methods are used to measure substrate deposition, then measurement accuracy is improved, but substrate usability deteriorates (substrates become unusable)
Solution Approach 1:
The patent uses optical metrology to create an optical copy or representation of the substrate surface properties without physically contacting or damaging the substrate. By measuring optical properties (reflectance, absorbance, etc.), the system obtains accurate thickness and uniformity data while preserving substrate integrity for continued use.
Solution Approach 2:
The patent replaces destructive mechanical or chemical measurement methods with non-destructive optical measurement methods. Instead of physically sectioning, etching, or otherwise mechanically interfering with the substrate to obtain thickness measurements, the system uses light interaction (reflectance, absorbance, ellipsometry) to achieve the same measurement goals without damage.
2Device complexity
If erroneous assumptions about uniformity are made across substrate regions, then measurement simplicity is improved, but manufacturing precision deteriorates (non-uniformity and malfunctioning substrates)
Solution Approach 1:
The patent divides the substrate into multiple discrete regions (first region with known structure data, second region with unknown structure data) and applies different measurement and prediction strategies to each. Rather than treating the entire substrate uniformly, the system segments it to enable accurate local measurements in known regions and predictive modeling in unknown regions, thereby capturing spatial variations in deposition.
Solution Approach 2:
The patent changes the approach from assuming uniform deposition parameters across all regions to using region-specific growth rates determined from optical metrology data. The system measures actual deposition parameters (growth rates, thickness) in known regions and uses these measured parameters to predict properties in unknown regions, rather than assuming uniformity based on simplified models.
3Reliability
If optical metrology data is used to predict thickness in regions without structure data, then substrate usability is improved (non-destructive measurement), but measurement precision may deteriorate (prediction uncertainty)
Solution Approach 1:
The patent uses feedback from optical metrology measurements in known regions to refine and validate the predictive model for unknown regions. By continuously comparing predicted thickness values with actual measured values in regions where structure data is available, the system can calibrate and improve the accuracy of predictions in regions where structure data is unknown, thereby reducing prediction uncertainty while maintaining non-destructive measurement benefits.
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 the prediction of thickness data for regions with unknown structure data, reducing non-uniformity and substrate malfunctions, while also saving time, energy, and resources by avoiding destructive metrology and erroneous assumptions.
Implementation Method 1
receiving optical metrology data of the substrate associated with one or more substrate deposition processes
Data Source
AI summary
A method includes identifying first structure data of a first region of a substrate and receiving optical metrology data of the substrate associated with one or more substrate deposition processes in a processing chamber. The method further includes determining, based on the optical metrology data and the first structure data, a first growth rate of the first region of the substrate associated with the one or more substrate deposition processes. The method further includes predicting, based on the optical metrology data and the first growth rate, thickness data of a second region of the substrate without second structure data of the second region.