WDX X-Ray Intensity Modeling for Faster Calibration and Background Correction
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Solution Overview
Problem
Existing WDX detection systems face challenges in accurately approximating X-ray intensities due to complex interactions within the system, leading to increased background artifacts and the need for extensive empirical calibration for each device configuration, which is time-consuming and inefficient.
Innovation Solution
A physics- and geometry-based model is developed to simulate and correct X-ray intensities by accounting for the impacts of collimators, crystal monochromators, and detectors, using a computer-implemented method to adjust sample model parameters until simulated intensities match measured intensities within a predefined distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a physics- and geometry-based model is used to simulate X-ray intensities, then analytical accuracy and reliability are improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent transforms the complex physical simulation problem into a parameter optimization problem. Instead of directly solving the complex physics equations in real-time, the system pre-calculates intensity values for various parameter combinations and stores them in lookup tables. During measurement, the system simply retrieves and compares these pre-calculated values, achieving high accuracy without real-time computational complexity.
Solution Approach 2:
The patent performs preliminary calculations of X-ray intensities for various sample compositions and measurement conditions before actual analysis. These pre-calculated intensities are stored and used as reference data during the actual measurement process, eliminating the need for complex real-time physics simulations while maintaining accuracy.
2Measurement precision
If extensive empirical calibration is performed for each device configuration, then measurement accuracy is improved, but calibration time and productivity are reduced
Solution Approach 1:
The patent creates a universal calibration approach that works across different device configurations. By using a physics-based model with parameters that can be adjusted for different collimators, monochromators, and detectors, the system eliminates the need for separate empirical calibration for each configuration. The same fundamental model serves all device variations.
Solution Approach 2:
The patent uses pre-calculated intensity values from physics simulations as copies of what empirical calibration would produce. These simulated intensity patterns serve as reference standards that can be directly compared with measured data, replacing the need for time-consuming empirical calibration while maintaining the accuracy benefits of extensive calibration.
3Quantity of substance
If background artifacts from crystal fluorescence and diffuse scattering are included in measurements, then comprehensive data collection is improved, but signal-to-noise ratio and analytical reliability deteriorate
Solution Approach 1:
The patent separates the total measured signal into distinct components: the desired analytical signal from sample fluorescence and the unwanted background from crystal fluorescence and diffuse scattering. By calculating and subtracting the background components based on the physics model, the system retains complete data information while removing harmful artifacts that would otherwise contaminate the analysis.
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 provides a reliable approximation of sample composition and layer thickness by reducing the complexity and time required for calibration, improving analytical performance and accuracy in WDX spectroscopy.
Implementation Method 1
The radiation is directed on a sample to be analyzed. The radiation generates polychromatic X-ray fluorescence and scattered radiation in the sample. In a wavelength-dispersive X-ray fluorescence spectrometer, the radiation emitted by the sample is analyzed by measuring, with a goniometer, the radiation reflected by a monochromator of the spectrometer (typically a crystal) at various diffraction angles θ. This technique is based on Bragg's law
Implementation Method 2
In WDX spectroscopy, an X-ray tube generates polychromatic radiation including characteristic lines and Bremsstrahlung
Implementation Method 3
The radiation generates polychromatic X-ray fluorescence and scattered radiation in the sample
Implementation Method 4
Thus, the detector must be able to discriminate between photons of the diffraction orders. Most detectors are designed to define this discrimination windows in fractions of the first diffraction order energy. A lower discrimination limit of 50 % together with an upper discrimination limit of 150 % means that photons that are registered by the detector with energies between half and one and a half of the first order energy are summed up to form the analytical relevant intensity for the spectrometer.
Data Source
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Figure 3~4A
AI summary
System (100), method and computer program product for approximating one or more X-ray intensities for a sample (202) measured by an X-ray detection system (200-1) with at least one collimator (205, 206) having a given angular range, a monochromator (203) and an X-ray detector (204). Measured intensities (212) are received from the detection system (200-1) at respective one or more diffraction angles (θ). A sample simulation module (130) computes simulated sample intensities (112) from an X-ray fluorescence sample model (130M) with initial sample model parameters (130P) indicating the sample composition and/or layer thickness of one or more sample layers. A correction module (120) applies a triangular collimator correction (121) to the simulated sample intensities (112) and determines a mathematical distance between the corrected simulated sample intensities and corresponding measured intensities. The sample model parameters (130P) are adjusted and the correction steps are repeated until the distance change falls below a minimal distance change. Finally, the sample model parameters (130P) regarding sample composition and/or the layer thickness associated with the corrected simulated intensities (112-c) are provided as approximated concentration values of respective components contained in the measured sample (202) and/or the layer thickness of the measured sample.