Geochemical Partitioning of Major Elements in Brine Impacted Coal Fly Ash Residues
Bibliographic record
Abstract
Fly ash-brine co-disposal technique has been considered as a way of disposing fly ash and brine (hyper-saline water) by some power stations in South Africa. This practice was aimed at using the fly ash to capture most of the elements in brine. However, the geochemical partitioning of the major elements in the waste materials after the fly ashbrine interaction has not been fully understood. This study focuses on understanding the geochemical partitioning of the major elements captured in the fly ash solid residues after the fly ash-brine interaction experiment. XRF and sequential extraction procedure were respectively applied to determine the chemical composition and partitioning of the major elements in fresh fly ash and the solid residues recovered after fly ash-brine interaction. The comparison of the results of the XRF analysis carried out on the fresh fly ash and the solid residues showed that the major elements such as Si, Ca, Mg and Na increased in the solid residues after the fly ash-brine interaction. This indicates that Ca, Mg and Na in the brine solution were captured by the fly ash during the interaction. However, the sequential extraction results showed that significant concentrations of Ca, Na and Mg were released into the water soluble, exchangeable and carbonate fractions. The results show that significant amounts of the elements captured in the fly ash solid residues during fly ash-brine interaction exist in the form which can be easily leached out when in contact with aqueous solution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".