Electron Probe Microanalysis of Bromine in Minerals and Glasses with Correction for Spectral Interference from Aluminium, and Comparison with Microbeam Synchrotron X‐Ray Fluorescence Spectrometry
Bibliographic record
Abstract
The strong spectral interference between Br‐ and Al‐induced X‐ray lines hampers the utilisation of electron probe microanalysis (EPMA) for measuring Br mass fractions in Al‐bearing minerals and glasses. Through measuring Br‐free Al‐bearing materials, we established an EPMA method to quantify the overlap from AlKα on BrLβ, which can be expressed as a linear function of the Al2O3 content. The count rate of the BrLβ peak signal was enhanced by high beam currents and long measurement times. Application of this EPMA method to Al‐ and Br‐bearing materials, such as sodalite and scapolite, and to five experimental glasses yielded Br mass fractions (in the range of 250–4000 μg g−1) that are consistent with those measured by microbeam synchrotron X‐ray fluorescence (μ‐SXRF) spectrometry. The EPMA method has an estimated detection limit of ~ 100–300 μg g−1. We propose that this method is useful for measuring Br mass fractions (hundreds to thousands of μg g−1) in Al‐bearing minerals and glasses, including those produced in Br‐doped experiments. In addition, the natural marialitic scapolite (ON70) from Mpwapwa (Tanzania) containing homogeneously distributed high mass fractions of Br (2058 ± 56 μg g−1) and Cl (1.98 ± 0.03% m/m) is an ideal reference material for future in situ analyses.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".