Silanation of Nanostructured Mesoporous Magnetic Particles for Heavy Metal Recovery
Bibliographic record
Abstract
Nanostructured mesoporous magnetic (m-Fe 3 O 4 ) particles are promising candidate materials for separation, detoxification, and precious metal recovery. The silanation of m-Fe 3 O 4 particles using 3-aminopropyltriethoxysilane is described. The silanized films were characterized using XPS, diffuse-reflectance FTIR spectroscopy, and electrokinetic techniques. The loading capacity of the silanized m-Fe 3 O 4 particles was found to be superior to that of m-Fe 3 O 4 or directly silanized Fe 3 O 4 particles. Extraction and separation of transition metals (II) were investigated using the silanized m-Fe 3 O 4 particles. The effectiveness of metal (II) extraction was found to increase with increasing solution pH, but was less effective at pH below 2. Satisfactory separation with loading efficiency in the order of Cu 2+ > Ni 2+ > Zn 2+ was obtained. The adsorbed metals were successfully desorbed with 1 M aqueous HCl solutions. As a result, the recovered m-Fe 3 O 4 particles can be recycled in industrial applications.
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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".