Separation of Lead and Copper Ions in Acidic Media Using an Ion-Exchange Resin with a Thiourea Functional Group
Bibliographic record
Abstract
This research studied the selective separation of lead and copper ions in acidic solutions using Puromet MTS 9140 resin with a thiourea functional group. The effects of operation parameters, that is, resin dosage, solution pH, ion exchange time, metal concentration, and temperature, on metal ion exchange were investigated using batch-test protocols. Ion-exchange experimental data were analyzed with Langmuir, Freundlich, and Temkin models. The results demonstrate that the MTS 9140 resin has ion-exchange selectivity for copper ions over lead ions. The ion-exchange recovery of Cu exceeded 95%, while Pb coloading was under 19% with MTS 9140 resin dosage of 0.070 g/mL in the pH range of 2.5 to 4.5. The kinetic studies showed that the ion exchange process could be better described by the pseudo-second-order model for lead and copper ions. The temperature dependence indicates the endothermic nature of the ion-exchange process. The resin also showed potential application as an effective adsorbent for removing heavy metal ions in water or 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) | 0.000 | 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 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".