Synthesis and Characterization of Hausmannite‐Activated Carbon Nanocomposites for Removal of Lead from Aqueous Solutions
Bibliographic record
Abstract
Abstract Nano‐hausmannite (Mn3O4; NH) was prepared together with its composites with activated carbon (AC), namely, HAC‐1 and HAC‐2. These materials were characterized by different techniques, and the adsorption properties of the studied sorbents NH, AC, HAC‐1, and HAC‐2 for Pb(II) were evaluated considering the effects of shaking time, pH, sorbent weight, initial Pb(II) concentrations, and temperature using batch experiments. The kinetics of sorption was described by the pseudo‐first‐order model. The adsorption isotherm was well fitted to the Sips model. The adsorption process was endothermic. Desorption experiments indicated that Pb(II) was released from the loaded adsorbents: NH, AC, HAC‐1, and HAC‐2 using 1.0 M HCl (97 % efficiency). Infrared spectral analysis suggested adsorption of Pb(II) through chemical bonding between the negatively charged functional groups of Mn–O, Mn–O–Mn, OH, and COO− with Pb(II).
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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) | 0.000 | 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 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".