Impact of using a 3.5 μm film to analyze the chemical composition of crystal samples with a handheld X-Ray Fluorescence equipment
Bibliographic record
Abstract
Some potassium-feldspar crystals from lithium-rich aplite-pegmatites from Northern Portugal have been analyzed with a handheld X-Ray-Fluorescence (XRF) equipment. This study compares the impact of analyzing the samples with an XRF film versus analyzing them without it. The film used was a Hitachi Poly-S High Performance XRF Sample Film of 3.5 μm, commonly used for analyzing samples in cups and powders. Although Hitachi alerts for the unsuitability of the film for analyzing light elements, this study helps understand the extent of error that this film can cause when analyzing this type of sample. 15 cleaned potassium feldspar crystals with a size between 1-3 cm have been analyzed with a Bruker S1 TITAN 600 containing an X-ray tube with a 2 W and 5-100 μA Rh anode. The Geomining factory calibration was used for the sample analysis.The results show that the potassium-feldspars analyzed with the film had their major elements drop by 20-40% for silica (SiO2), 30-50% for aluminum (Al2O3) and 10-20% for potassium (K2O). As for the trace elements, calcium (Ca) dropped by 20-30%, phosphorous (P) by 20-40% and rubidium (Rb) and iron (Fe) have small errors that can vary from plus 0-10% to minus 0-10%. Knowing the film impact will hopefully be of assistance for the correct interpretation of portable XRF results during field campaigns for mineral exploration.This study was financially supported by FCT, I.P., in the framework of the ICT (UIDB/04683/2020 and UIDP/04683/2020), by the PhD project (2020.05534.BD) and by national funds from MCTES, through FCT, co-financed by ESF through POCH and NORTE 2020. This work is also supported by the Greenpeg project, reference 869274, funded by the Horizon 2020 framework program of the European Union.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".