Removal of copper, zinc and cadmium ions through adsorption on water-quenched blast furnace slag
Bibliographic record
Abstract
Water-quenched blast furnace slag (WBFS) has been assessed regarding its capacity to remove Cu2+, Cd2+, and Zn2+ from aqueous solutions. The physicochemical properties of the slag were characterized by ICP, SEM, and XRD. Batch experiments were conducted to study the effects of the adsorbent dosage, pH, initial concentration of heavy metal ions, temperature, and contact time on the removal of Cu2+, Cd2+, and Zn2+. The results showed that the removal efficiency increased with increasing adsorbent dosage and the optimum conditions for the removal of Cu2+, Cd2+, and Zn2+ were obtained in the dosage of 12, 16, and 16 g/L, respectively. The removal efficiency and adsorption amount of Cu2+, Cd2+, and Zn2+ onto WBFS increased on increasing the solution pH from 1 to 9, while the values decreased slightly as the pH further increased above 9. The adsorption process could fit the pseudo-second-order kinetic and Langmuir isotherm models. Various thermodynamic parameters were calculated and the results indicated the adsorption of Cu2+, Cd2+, and Zn2+ onto WBFS was feasible and endothermic in nature. These results have significant implications for the treatment of heavy metal wastewater using low-cost adsorbents.
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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".