EDX Acquisition Stop Criteria Using Gaussian Peak Fitting Error
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Solution Overview
Problem
Existing charged particle beam microscopes with Energy Dispersive X-ray (EDX) analysis face challenges in setting optimal operational parameters, such as dwell time and signal strength, which can lead to wasted time or unusable data if not accurately set, affecting the quality and precision of elemental analysis.
Innovation Solution
Implementing intelligent EDX acquisition stop criteria based on Gaussian peak fitting error to determine optimal electron beam exposure time and signal strength, using a database of mathematical relationships between dwell time and fitting error for specific sample types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the electron beam exposure time (dwell time) is increased to improve the signal strength and statistical validity of EDX analysis, then the measurement precision and reliability of elemental composition data are improved, but the productivity and time efficiency of the analysis are reduced
Solution Approach 1:
The system continuously monitors the Gaussian fitting error of spectral peaks during data acquisition and uses this feedback to dynamically determine when to terminate the acquisition. When the fitting error reaches a predetermined threshold, the system automatically stops collecting data, eliminating the need for fixed prolonged exposure times while ensuring sufficient statistical validity is achieved.
Solution Approach 2:
The patent transforms the static, predetermined dwell time approach into a dynamic acquisition process where the exposure time is continuously adjusted based on the real-time quality of spectral data. The system adapts the acquisition duration to the specific characteristics of each sample and spectral region, optimizing the balance between data quality and analysis speed.
2Reliability
If the electron beam exposure time is extended to ensure accurate statistical analysis, then the reliability of elemental composition data is improved, but the loss of time and resource waste increase
Solution Approach 1:
The system uses Gaussian peak fitting error as a real-time feedback metric to monitor data quality during acquisition. This feedback mechanism allows the system to confidently terminate acquisition once sufficient statistical reliability is achieved, preventing unnecessary time loss while maintaining high reliability standards.
Solution Approach 2:
The patent replaces the traditional mechanical/time-based approach (fixed dwell time settings) with an intelligent, algorithm-based termination criterion. Instead of relying on predetermined time intervals, the system uses computational analysis of spectral peak quality to determine the optimal stopping point, substituting brute-force time accumulation with smart decision-making.
3Measurement precision
If manual setting of operational parameters is used to optimize EDX analysis, then the measurement precision can be improved for experienced users, but the ease of operation deteriorates for infrequent or inexperienced users
Solution Approach 1:
The system performs self-optimization by automatically determining the optimal acquisition duration based on real-time spectral quality assessment. The instrument serves itself by making intelligent decisions about when to stop data collection, eliminating the need for user expertise in parameter selection while maintaining high data quality. The system autonomously adjusts operational parameters based on the actual sample characteristics.
Solution Approach 2:
The patent implements dynamic parameter adjustment where the acquisition time parameter is continuously modified based on the observed spectral peak quality. Instead of requiring users to manually set fixed parameters, the system automatically changes the acquisition duration parameter in response to real-time feedback from the spectral analysis, adapting to each unique sample and analysis condition.
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
Enhances the accuracy and efficiency of EDX analysis by automatically terminating data acquisition when predetermined fitting error thresholds are met, optimizing resource use and ensuring statistically valid results.
Implementation Method 1
exposing a sample with a focused electron beam, which results in the emission of characteristic X-rays from the atoms within the sample
Implementation Method 2
directing a beam of electrons onto a sample
Implementation Method 3
The emitted X-rays are then detected and analyzed by an energy-dispersive spectrometer
Data Source
AI summary
A method for constructing an optimal-setting prediction model, comprises: (1) setting one or more microscope operational parameters to respective initial values; (11) directing a charged particle beam onto a specimen of a first known sample type and imaging or analyzing the specimen using the most recently set microscope operational parameters while detecting emissions from the specimen; (III) repeatedly: (i) changing a value of at least one of the one or more operational parameters; (ii) directing the charged particle beam onto a different specimen of the first known sample type and imaging or analyzing the different specimen using the most recently set microscope operational parameters while detecting emissions from the different specimen; and (iii) recording the values of the microscope operational parameters and recording a value that is a measure of the detected emissions from the different specimen; and (IV) constructing and storing a mathematical relationship, pertaining to the first known sample type, between at least one variable that represents a microscope operational parameter and a variable that represents the detected emissions.