Predictor Model for X-Ray Structure Analysis Feasibility
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Solution Overview
Problem
Current methods for analyzing multi-layered structures using electron beam excitation of x-rays face challenges in determining the feasibility and precision of structure and composition analysis, often requiring extensive experimentation and expertise, with iterative procedures prone to failure due to inappropriate starting guesses and statistical variations.
Innovation Solution
A method involving the generation of predicted x-ray data and analysis of changes to structure data based on predetermined feasibility criteria, using a predictor model to simulate various process conditions and assess the solvability of the structure analysis problem, including Monte Carlo simulations to estimate precision and reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative procedures are used to solve structure analysis problems, then structure and composition can be determined, but the procedure may fail to converge due to inappropriate starting guesses
Solution Approach 1:
The patent applies preliminary action by performing a feasibility study before the actual structure analysis. The method simulates x-ray data generation using a predictor model with predetermined structure parameters, then tests whether a structure solver can successfully retrieve these parameters. This preliminary simulation identifies potential convergence issues and determines optimal starting conditions before real analysis begins, preventing iterative procedure failures.
Solution Approach 2:
The patent uses copying by creating simulated x-ray data that replicates real measurement conditions. Instead of directly analyzing real x-ray spectra, the method generates synthetic data using a predictor model that copies the physical processes of electron beam excitation and x-ray emission. This copied data allows testing and optimization of analysis procedures without the uncertainties of real measurements.
2Reliability
If extensive experimentation is conducted to determine analysis feasibility, then reliable results can be obtained, but time and resources are consumed
Solution Approach 1:
The patent replaces extensive physical experimentation with computational copying. The predictor model generates synthetic x-ray spectra that replicate real measurement conditions, allowing feasibility assessment through simulation rather than repeated experimental trials. This copying approach maintains reliability while dramatically reducing time consumption.
Solution Approach 2:
The method performs preliminary feasibility assessment through simulation before committing to actual analysis experiments. By testing structure solver performance on generated data with known parameters, the method determines whether analysis is feasible and identifies optimal conditions in advance, avoiding wasted experimental time on impossible or suboptimal configurations.
3Measurement precision
If iterative structure solving is performed with statistical variations, then real measurement uncertainties are accounted for, but precision estimates become difficult to obtain
Solution Approach 1:
The patent copies real measurement conditions including statistical variations into the simulated data generation process. The predictor model incorporates Poisson counting statistics and other measurement uncertainties, allowing precision estimation through multiple simulated trials. This approach quantifies the impact of statistical variations on parameter retrieval precision without the complexity of analyzing real experimental variability.
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 the determination of optimal analysis conditions, reducing the need for extensive experimentation and improving the reliability and precision of layer thickness and composition estimates, making the analysis more accessible and efficient.
Implementation Method 1
x-rays may be generated at any point along the electron trajectory as a result of ionisation of atoms
Implementation Method 2
characteristic x-rays are generated from elements in both the substrate and the various layers
Data Source
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AI summary
A method of determining the feasibility of a proposed structure analysis process is disclosed. The process involved the electron beam excitation of x-rays from a multi- layered structure. The method comprises generating predicted x-ray data representing the x-ray excitation response of the multi-layered structure according to one or more sets of process conditions. The x-ray data are generated using structure data defining the structure and composition of the layers. The effects upon the x-ray data of changes to the structure data are then analysed in accordance with one or more predetermined feasibility criteria, so as to determine the feasibility of performing the proposed structure analysis process upon the multi-layered structure.