What Remains to Be Done to Allow Quantitative X-Ray Microanalysis Performed with EDS to Become a True Characterization Technique?
Bibliographic record
Abstract
This article reviews different methods used to perform quantitative X-ray microanalysis in the electron microscope and also demonstrates the urgency of measuring the fundamental parameters of X-ray generation for the development of accurate standardless quantitative methods. Using ratios of characteristic lines acquired on the same X-ray spectrum, it is shown that the Cliff and Lorimer K A-B factor can be used in a general correction method that is appropriate for all types of specimens and electron microscopes, providing that appropriate corrections are made for X-ray absorption, fluorescence, and indirect generation. Since the fundamental parameters appear in the K A-B factor, only the ratio of the ionization cross sections needs to be known, not their absolute values. In this regard, the measurement of ratios of the K A-B factor (or intensities at different beam energies of the same material with no change of beam spreading in the material) permits the validation for the best models to compute the ratio of ionization cross sections. It is shown, using this method, that the nonrelativistic Bethe equation, to compute ionization cross section, is very close to the equation of E. Casnati et al. (J Phys B 15, 155-167, 1982) and also to the equations proposed by D. Bote and F. Salvat (Phys Rev A 77, 042701, 2008) for the computation of the ratio of ionization cross sections. The method is extended to show that it could be used to determine the values of the Coster-Kronig transitions factors, an important fundamental parameter for the generation of L and M lines that is mostly known with poor accuracy. The detector efficiency can be measured with specimens where their intensities were measured with an energy dispersive spectrometer detector, the efficiency of which has been measured in an X-ray synchrotron (M. Alvisi et al., Microsc Microanal 12, 406-415, 2006). The spatial resolution should always be computed when performing quantitative X-ray microanalysis and the equations of R. Gauvin (Microsc Microanal 13(5), 354-357, 2007) for bulk materials and the one presented in this article for thin films should be used. The effects of X-rays generated by fast secondary electrons and by Auger electrons are reviewed, and their effect can be detrimental for the spatial resolution of materials involving low-energy X-ray lines, in certain specific conditions. Finally, quantitative X-ray microanalysis of heterogeneous materials is briefly reviewed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".