Spectral Data Condensing for Real-Time Microanalysis
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Solution Overview
Problem
Spectral microanalysis is time-consuming due to the need for extensive data collection and analysis of hyperspectral data cubes, particularly when dealing with large specimen areas and complex compositions, as existing methods require scanning and statistical processing that can take minutes to hours even with fast computers.
Innovation Solution
The method involves condensing spectral data by combining emission counts in adjacent energy intervals and spatially combining pixel spectra during data collection, allowing for preliminary analysis results to be provided in real-time, with the option to gradually increase resolution as more data is collected, significantly reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectra are collected from multiple pixels across a specimen region using an excitation beam scan, then spatial composition information is obtained, but data collection and analysis time increases significantly
Solution Approach 1:
The patent performs preliminary statistical analysis during the data collection phase rather than after complete data acquisition. By analyzing spectra as they are being collected from multiple pixels, the system provides preliminary composition information before the full hyperspectral data cube is complete, thereby reducing the perceived analysis time while maintaining measurement precision.
Solution Approach 2:
The patent divides the analysis process into segments that can be performed independently and in parallel. By collecting and analyzing spectra from different pixel regions simultaneously or in overlapping time periods, the system processes spatial composition data in manageable segments rather than treating the entire dataset as a single analysis unit, thus reducing overall processing time.
2Measurement precision
If statistical analysis is performed on complete hyperspectral data cubes, then accurate component identification is achieved, but processing time extends to minutes or hours
Solution Approach 1:
The patent performs preliminary statistical analysis during the data collection phase rather than after complete data acquisition. By analyzing spectra as they are being collected from multiple pixels, the system provides preliminary composition information before the full hyperspectral data cube is complete, thereby reducing the perceived analysis time while maintaining measurement precision.
Solution Approach 2:
The patent accepts that preliminary analysis results may be based on incomplete data (partial action) rather than waiting for complete data acquisition. The system provides useful composition information from the portion of data that has been collected and analyzed so far, enabling faster turnover with the understanding that results may be refined as additional data is processed.
3Measurement precision
If spectra from multiple pixels are analyzed to determine specimen composition, then comprehensive material characterization is obtained, but data volume and analysis complexity increase
Solution Approach 1:
The patent divides the analysis process into segments that can be performed independently and in parallel. By collecting and analyzing spectra from different pixel regions simultaneously or in overlapping time periods, the system processes spatial composition data in manageable segments rather than treating the entire dataset as a single analysis unit, thus reducing overall processing complexity.
Solution Approach 2:
The patent performs preliminary statistical analysis during the data collection phase rather than after complete data acquisition. By analyzing spectra as they are being collected from multiple pixels, the system provides preliminary composition information before the full hyperspectral data cube is complete, thereby reducing the perceived analysis time while maintaining measurement precision.
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 reduces analysis time from minutes to seconds, enabling analysts to receive preliminary results promptly and update them as data is collected, enhancing productivity and accuracy without significantly degrading component identification.
Implementation Method 1
directing an excitation beam - such as an electron beam or X-ray beam - at a specimen, and then capturing and analyzing the radiation and/or particles emitted by the specimen in response to the excitation beam
Implementation Method 2
directing an excitation beam - such as an electron beam or X-ray beam - at a specimen
Data Source
Figure 1
Figure 2~3C
Figure 4A~4C
AI summary
A system for performing spectral microanalysis delivers analysis results during the course of data collection As spectra are collected from pixels on a specimen, the system periodically analyzes the spectra to statistically derive underlying spectra representing proposed specimen components(A), wherein the derived spectra combine in varying proportions to result (at least approximately) in the measured spectra at each pixel Those pixels having the same dominant proposed component, and/or which contain at least approximately the same proportions of the proposed components, may then have their measured spectra combined (i e, added or averaged) (C, D) These spectra may then be cross-referenced via reference libraries to identify the components actually present(E) During the foregoing analysis, the measured spectra are preferably condensed, as by reducing the number of energy channels /intervals making up the measured spectra and/or by combining the measured spectra of adjacent pixels, to reduce the size of the data cube and expedite analysis results (G).