XRF online analyzer for measurements of P2O5 content in phosphate slurry
Bibliographic record
Abstract
Abstract Online X-ray Fluorescence (XRF) setup was constructed and optimized for analysing the P 2 O 5 content in phosphate slurry (PS). Serval samples were analysed using two configurations of the setup, one with low and vertical flow and another with high and horizontal flow. The mean absolute error achieved through the first configuration was 0.87% and 0.38% using the second configuration. Reference samples were analyzed using the two configurations to construct the calibration curves. The curves cover a concentration range of P 2 O 5 from 13.50 to 18.50% when considering the horizontal flow configuration, and a range of 14.00–15.60% when considering the vertical flow setup. An experimental study was conducted in order to optimize the measurement parameters for the online measurement of P 2 O 5 in the phosphate slurry using the horizontal flow setup. A good signal-to-noise ratio (SNR) of $$P\left(K\alpha \right)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>P</mml:mi> <mml:mfenced> <mml:mi>K</mml:mi> <mml:mi>α</mml:mi> </mml:mfenced> </mml:mrow> </mml:math> was attained using an excitation energy of 20 kV or 25 kV, an excitation current of 600 µA, a distance of 18 mm between the sample and the detector, a measurement time of 60 s per spectrum and the use of an Aluminum filter between the X-ray tube and the measurement window. Online X-ray fluorescence analysis of P entails some challenges due to the low characteristic energy of P , the phosphate slurry matrix and the online analysis mode. However, the outcomes of this study indicate that XRF is a promising technology to meet the requirement for digitalization of chemical analysis of phosphate products.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".