New Evidence for Rejuvenation of Phosphorus Retention Capacity in EAF Steel Slag
Bibliographic record
Abstract
The purpose of this research was to investigate phosphorus (P) retention capacity and rejuvenation potential of electric arc furnace (EAF) steel slag from Quebec and New Zealand (NZ) iron melter slag (IMS). Columns filled with slag materials were fed with dairy effluent and subjected to two feeding and one resting cycle(s). P retention capacities and rejuvenation potentials were determined after each feeding cycle. Elemental composition and mineralogical analysis were performed on IMS samples. Finally, chemical fractionation analysis was conducted on both NZ IMS and Quebec EAF steel slags. The results revealed that initiating a resting period in EAF steel slag filters prior to reaching their P saturation point increased the overall filter P retention capacity by 49.5 and 42.4% compared to 28% in a filter which had its resting period initiated after reaching P saturation. The rejuvenation property could play a significant role in full-scale applications by prolonging life expectancy and increasing cost efficiency. P retention and rejuvenation by NZ slag materials was negligible relative to EAF steel slag material from Quebec. Chemical fractionation analysis revealed differences between materials, indicating that the highest quantities of P were bound to Ca and Fe in EAF steel slag and to Ca and Al fractions in iron melter slag. This study also demonstrates that slag's performance is dependent on the source of the material and the steel making practices. Therefore, testing of the P adsorptive capability and, if relevant, the rejuvenation potential of individual steel mill slags, should be a prerequisite prior to their use in field applications.
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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 | 0.001 | 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) | 0.002 | 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".