Color Metrology for Substrate Thickness During CMP
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Solution Overview
Problem
Current optical metrology systems for detecting the thickness of layers on substrates during chemical mechanical polishing face challenges in accuracy due to variations in slurry distribution, polishing pad conditions, and initial thickness, leading to potential over- or under-polishing, and existing techniques like spectrometry are computationally heavy and expensive.
Innovation Solution
A system utilizing a color imaging system with a controller that performs color correction and calculates thickness by analyzing images from multiple angles of incidence, enhancing accuracy and reducing computational load through the use of a color correction matrix and dimensionality of the color space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectrographic or ellipsometric optical metrology systems are used to measure layer thickness, then measurement capability is provided, but computational load and system cost increase significantly
Solution Approach 1:
The patent replaces expensive, complex spectrographic and ellipsometric systems with a simple color camera system. The color camera uses standard RGB sensors and basic lighting to capture optical properties of the layer, eliminating the need for sophisticated spectrographs and complex optical paths while maintaining thickness measurement capability through color space analysis.
Solution Approach 2:
The patent substitutes complex optical measurement mechanisms with a simplified color imaging approach. Instead of using spectrographic dispersers, ellipsometric polarizers, and complex optical paths, the system uses a color camera to capture reflected light colors and processes the data through color space transformations and machine learning algorithms to determine thickness.
2Ease of operation
If polishing time is used as the sole criterion for endpoint detection, then process simplicity is maintained, but measurement precision deteriorates due to variations in material removal rate
Solution Approach 1:
The patent implements real-time optical feedback during the polishing process. The color camera continuously monitors the layer thickness by capturing color images at different angles of incidence, and the system uses this feedback to detect the polishing endpoint based on color space transformations and machine learning analysis, rather than relying solely on predetermined polishing times.
Solution Approach 2:
The patent performs preliminary color correction and calibration before the actual polishing measurement. The system captures reference images of the substrate, performs color space transformations, and establishes baseline color profiles that are used to accurately detect thickness changes during polishing, enabling precise endpoint detection.
3Productivity
If color images are captured without color correction, then processing speed is maintained, but measurement precision decreases due to color inaccuracies
Solution Approach 1:
The patent performs color correction as a preliminary step before thickness measurement. The system captures reference color images of the substrate under known conditions, establishes color correction matrices through color space transformations, and applies these corrections to subsequent measurement images, ensuring accurate color representation for thickness determination.
Solution Approach 2:
The patent transforms color image data from standard RGB color space to alternative color spaces (such as LAB or LUV) that separate luminance from chrominance information. This parameter transformation enhances the precision of thickness measurements by focusing on chromatic variations that correlate with layer thickness while maintaining efficient processing through matrix operations.
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
The system improves thickness measurement accuracy, enabling precise control of polishing parameters and achieving uniformity by enhancing color contrast and reducing degeneracies in the measurement path, thus providing reliable and accurate thickness measurements.
Implementation Method 1
an optical assembly to capture a first color image of at least a portion of the substrate held by the support with light impinging the substrate at a first angle of incidence and a second color image of the at least a portion of the substrate held by the support with light impinging the substrate at a different second angle of incidence
Data Source
AI summary
A layer thickness measurement system includes a support to hold a substrate, an optical sensor to capture a color image of at least a portion of the substrate, and a controller. The controller is configured to receive the color image from the optical sensor, perform a color correction on the color image to generate an adjusted color image having increased color contrast, determine a coordinate of the pixel in a coordinate space of at least two dimensions including a first color channel and a second color channel from color data in the adjusted color image for each of the adjusted color image, and calculate a value representative of a thickness based on the coordinate of the pixel of the adjusted color image in the coordinate space.