EDS Elemental Maps for Substrate Process Model Validation
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Solution Overview
Problem
Existing methods for predicting changes in materials during substrate processing, such as deposition and etching, lack accuracy due to limited information from transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images, which fail to accurately reflect chemical element distributions and reaction fronts, leading to inaccuracies in film thickness determination and halide inclusion detection.
Innovation Solution
The use of x-ray energy-dispersive spectroscopy (EDS) data to create and validate process models, providing detailed elemental maps that allow for precise determination of film thickness, halide inclusion, and interface analysis, even in cases of thin films and rough surfaces, by correlating EDS data with imaging data from TEM or SEM.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If TEM or SEM imaging data is used to predict changes in materials during substrate processing, then the process can be monitored and analyzed, but the accuracy is limited due to inability to accurately reflect chemical element distributions and reaction fronts
Solution Approach 1:
The patent combines multiple imaging modalities (TEM, SEM) with EDS spectroscopy data to create a comprehensive process model. This merging of different measurement techniques allows simultaneous observation of morphological features and chemical element distributions, resolving the contradiction between measurement capability and information completeness
Solution Approach 2:
The patent introduces a process model as an intermediary that integrates data from multiple imaging techniques and EDS measurements. This model acts as a mediator that translates raw imaging data into accurate predictions of material changes, film thickness, and reaction fronts, overcoming the limitations of individual imaging methods
2Reliability
If traditional imaging methods are used to detect halide inclusion, then the process can be monitored, but the detection accuracy is insufficient for thin films and rough surfaces
Solution Approach 1:
The patent changes the measurement parameters by transitioning from purely optical/morphological imaging to spectroscopic analysis using EDS. This parameter change enables detection of halide inclusions based on chemical composition rather than just visual appearance, significantly improving reliability for thin films and rough surfaces where traditional imaging fails
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 enhances the predictive accuracy of process models, enabling precise control over deposition and etching processes, improving the quality and uniformity of manufactured materials by accurately determining film thickness and halide inclusion, even in challenging conditions like thin films and rough surfaces.
Implementation Method 1
x-ray energy-dispersive spectroscopy (EDS) data to create and validate process models
Data Source
AI summary
Implementations disclosed describe a method of using a model to predict a change of a physical state of a sample caused by one or more stages of a technological process in a substrate processing apparatus and obtaining imaging data associated with an actual performance of the one or more stages of the technological process. The imaging data includes a distribution of one or more chemical elements for a number of regions of the sample. The method further includes identifying, based on the imaging data, a difference between the predicted change of the physical state of the sample and an actual change of the physical state of the sample caused by the actual performance of the one or more stages of the technological process. The method further includes determining parameters of the model based on the identified difference.