A novel magnetite nanorod-decorated Si-Schiff base complex for efficient immobilization of U(<scp>vi</scp>) and Pb(<scp>ii</scp>) from water solutions
Bibliographic record
Abstract
A novel silicon Schiff base complex (Si-SBC) and magnetite nanorod-decorated Si-SBC (M/SiO2-Si-SBC) were synthesized and well characterized in detail. The synthesized materials were applied for the removal of U(vi) and Pb(ii) from water solutions under various experimental conditions. The monolayer maximum adsorption capacities of M/SiO2-Si-SBC (6.45 × 10-4 mol g-1 for Pb(ii) and 4.82 × 10-4 mol g-1 for U(vi)) obtained from the Langmuir model at 25 °C and pH = 5.00 ± 0.05 were higher than those of Si-SBC (5.18 × 10-4 mol g-1 for Pb(ii) and 3.70 × 10-4 mol g-1 for U(vi)). Moreover, DFT calculations showed that the high adsorption energies (Ead) of 7.61 kcal mol-1 for Pb2+-(Si-SBC) and 2.72 kcal mol-1 for UO22+-(Si-SBC) are mainly attributed to stronger electrostatic interactions. The results revealed that the Si-SBC and M/SiO2-Si-SBC could be used as efficient adsorbents for the effective elimination of U(vi) and Pb(ii) from contaminated wastewater. High sorption capacity and reusability indicated the practical applications of the synthesized materials in environmental pollution cleanup.
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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".