Spectrum Data Analysis Iterative Least Squares Algorithm
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Solution Overview
Problem
Standard-based spectral analysis in scanning electron microscopy faces challenges with overlapping elemental spectra, low count spectra analysis, and artefact introduction due to overlapping peaks and variability, making it difficult to accurately determine the elemental composition of samples, especially for minerals like galena and zirconia.
Innovation Solution
The method employs an iterative least squares algorithm for spectrum data analysis, which involves collecting a spectrum, providing element data templates, calculating optical least squares weights, removing templates with negative weights, and re-calculating the spectrum to improve accuracy and reduce artefacts, while also using non-uniform sub-sampling and low count channel optimization to enhance peak discrimination and reduce noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If standard-based spectral analysis is used to determine elemental composition, then the analysis can be performed using known spectra templates, but overlapping elemental spectra and artefacts reduce measurement precision
Solution Approach 1:
The patent segments the spectral analysis process into multiple iterative steps: initial template matching, identification of problematic overlapping peaks, selective removal or adjustment of specific templates, and re-calculation. This segmentation allows the system to handle complex overlapping spectra by breaking down the problem into manageable iterations, improving precision without sacrificing the ease of using template-based methods
Solution Approach 2:
The patent changes parameters by adjusting the set of active templates during analysis. When overlapping peaks are detected, the system modifies which templates are applied (e.g., removing templates for elements with overlapping peaks or adjusting their weightings), thereby adapting the analysis parameters to improve measurement precision for specific spectral conditions
2Measurement precision
If more spectrum data is collected to improve analysis accuracy, then measurement precision improves, but analysis time increases
Solution Approach 1:
The patent performs preliminary actions by pre-identifying which elemental templates are likely to cause overlapping peaks based on known spectral characteristics. This allows the system to proactively adjust the template set before full analysis, reducing the need for extensive iterative calculations and thereby reducing analysis time while maintaining precision
Solution Approach 2:
The patent skips unnecessary calculation steps by identifying and removing templates that contribute to overlapping peaks early in the analysis. This allows the system to rush through the analysis process by focusing computational resources only on the relevant, non-overlapping spectral features, thereby reducing overall analysis time without sacrificing accuracy
3Measurement precision
If iterative template removal and re-calculation is performed to reduce artefacts, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent implements self-service by having the algorithm automatically identify overlapping peaks, select which templates to remove or adjust, and perform re-calculation without external intervention. The system uses built-in criteria (such as peak overlap detection and artefact identification) to guide the iterative process, thereby managing algorithmic complexity through automation rather than requiring complex external control mechanisms
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 allows for rapid and accurate determination of elemental composition from low-count spectra, reducing artefacts and improving peak resolution, enabling more precise analysis of minerals with overlapping peaks and low-count data, thus overcoming limitations of standard-based methods.
Implementation Method 1
When these electrons enter an atom, they can knock electrons out of the material. In the process, the first electron looses some energy, but can go on to smash into other atoms until it no longer has enough energy to continue doing so.
Implementation Method 2
By analyzing the energy of the emitted x-ray, the type of the emitting atom can be determined. Each element in the periodic table has a specific set of energies corresponding to these x-ray energies.
Implementation Method 3
Alternatively, the electrons from the SEM may not enter an atom, but may be deflected away from an atom. This is caused by the negative electric charge on the electron being repelled by the negative charge of the electron cloud around the atoms. The deflection of the path causes a small drop in energy of the high energy electron. This generates the Bremsstrahlung radiation.
Data Source
AI summary
A method and system for spectrum data analysis. The method comprises the steps of collecting a spectrum of an unknown material; providing a set of data templates; calculating weighting factors for the element data templates to minimize error in approximating the spectrum; removing one or more of the templates having negative weights in approximating the spectrum; and re-calculating an approximation of the spectrum with said one or more templates removed. Embodiments of the invention are suitable for analyzing noisy spectra having relatively few data points.