Kinetic Modelling of the Removal of Multiple Heavy Metallic Ions from Mine Waste by Natural Zeolite Sorption
Bibliographic record
Abstract
This study investigates the sorption of heavy metallic ions (HMIs), specifically lead (Pb2+), copper (Cu2+), iron (Fe3+), nickel (Ni2+) and zinc (Zn2+), by natural zeolite (clinoptilolite). These HMIs are combined in single-, dual-, triple-, and multi-component systems. The batch mode experiments consist of a total initial concentration of 10 meq/L normality for all systems, acidified to a pH of 2 by concentrated nitric (HNO3) acid. A zeolite dosage of 4 g per 100 mL of synthetic nitrate salt aqueous solution is applied, for a contact period of 5 to 180 min. Existing kinetic models on HMIs sorption are limited for multi-component system combinations. Therefore, this study conducts kinetic analysis by both reaction and diffusion models, to quantify the sorption process. The study concludes that the process correlates best with the pseudo-second-order (PSO) kinetic model. In the multi-component system combining all five HMIs, the initial sorption rate and theoretical equilibrium capacity are determined as 0.0033 meq/g·min and 0.1159 meq/g, respectively. This provides significant insight into the mechanisms associated with the sorption process, as well as contributing to the assessment of natural zeolite as a sorbent material in its application in industrial wastewater treatment.
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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 | 0.000 | 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 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".