Effects of Operation Parameters on Heavy Metallic Ion Removal from Mine Waste by Natural Zeolite
Bibliographic record
Abstract
This study investigates the effects of particle size (0.420-1.1410 mm), dosage (40, 80 g/L), influent concentration (total 10 meq/L, 400 mg/L), contact time (5-180, 270, 360 min), set-temperature (20-32 o C), and heat pre-treatment (200, 400, 600 o C) of natural zeolite on the removal efficiency of heavy metallic ions (HMIs); lead (Pb 2+ ), copper (Cu 2+ ), iron (Fe 3+ ), nickel (Ni 2+ ), and zinc (Zn 2+ ).The sorption process is performed in batch mode with a 100 mL aqueous solution, acidified to a pH level of 2 with concentrated nitric (HNO3) acid.For all experimental parameter conditions examined, the removal efficiency order follows: Pb 2+ >>Fe 3+ >Cu 2+ >Zn 2+ >Ni 2+ ; the zeolite mineral exhibits the greatest preference towards the Pb 2+ ion in all parameter trends.Overall, the removal efficiency is increased with decreasing particle size, as well as increasing dosage, contact time, and set-temperature.The operation is influenced by the studied parameters in the order of: influent concentration > heat pre-treatment level > dosage > particle size > contact time > set-temperature.
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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 | 0.001 |
| 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) | 0.000 | 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".