Molecular simulation using electronic structure methods on copper and lead ions separation with thiourea‐functionalized resin
Bibliographic record
Abstract
Abstract The selective separation of copper and lead ions in acidic solutions was successfully achieved utilizing a thiourea‐functionalized resin, specifically Puromet MTS 9140, which demonstrated a strong adsorption preference for copper ions. To further elucidate the adsorption mechanism of Cu(II) ions, density functional theory (DFT) calculations using the B3LYP technique and ab initio unrestricted Hartree–Fock (UHF) methods were employed to analyze electronic structure features, such as Mulliken population/charge, frontier orbital energies, and Gibbs free energy (∆G° f ) of three structural units in the resin (i.e., m‐thiourea‐styrene, o‐thiourea‐styrene, and p‐thiourea‐styrene) and their interaction with Cu(II) and Pb(II) ions. The Frontier molecular orbital (FMO) theory analysis using the B3LYP DFT method verified that the resin bearing thiourea group interacts with Cu(II) and Pb(II) ions through S atom bonding. This research enhances the understanding of mechanisms involved in the recovery and removal of metal ions from aqueous systems using selective resins, indicating potential applications in water and wastewater treatment.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".