Adsorptive removal of nickel by modified natural adsorbents: optimization, characterization and application
Bibliographic record
Abstract
ABSTRACT The adsorptive removal of nickel by persimmon tannin-based adsorbents was first evaluated. NaOH modified persimmon powder-formaldehyde resin (NPPFR) showed significantly enhanced adsorption capacity towards Ni(II). The adsorption process was completely achieved equilibrium within 60 min, and the well-fitted pseudo-second-order kinetics data indicated that chemisorption is the main rate-limiting step. The adsorption isotherms followed the Langmuir model, where the maximum adsorption capacity reached 81.6 mg g –1 at pH 5.0. The adsorbed Ni(II) ions were desorbed by 0.1 mol L –1 HNO 3 and the regenerated adsorbent exhibited undiminished sorption efficiency for 4 cycles. The removal of Ni(II) from actual industrial wastewaters in both batch and column experiments was demonstrated to be effective. The adsorption mechanism was proposed to be electrostatic attraction and ion exchange. In addition, competition and replacement during the adsorption process were found in the multiple metal ions systems. The results indicated that NPPFR can serve as a low-cost, eco-friendly and effective alternative for Ni(II) removal in 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 | 0.000 |
| 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".