Kinetic and equilibrium investigation of the lead (II) adsorption via orange peel and lemon peel: realistic adsorption design for poly(limonene) framework
Bibliographic record
Abstract
A laboratory investigation was performed to regulate the physicochemical attributes—geomorphological and organizational, kinetic estates, and purposeful groups—of orange ( Citrus × sinensis) and lemon ( Citrus × limon) with a view toward a prospective adsorbent of toxic lead ions from aquatic solution. Outcomes demonstrated that optimal requirements for the Pb (II) removal are a preliminary concentration of 50 mg/L, an adsorbent mass of 0.2 g, and 6 and 4.4 as pH for orange peel and lemon peel, respectively. The investigational statistics were discussed via Freundlich, Langmuir, and D–R isotherm. Equilibrium statistics matched appropriately via Langmuir typical with a qmax of 16.76 mg/g for orange peel and 76.92 mg/g for lemon peel. The kinetic adsorption process was inspected and was adequately accomplished via a second-order equivalence. The characterization of lemon peel and orange peel was examined with a scanning electron microscope, Vis-IR spectroscopy, and GC-mass. The Pb(II) adsorption spontaneity onto orange peel is enhanced by enhancing temperature. The positive ∆ H° (53.76 kJ/mol) estimate implies an endothermic system. The positive ∆ S° (180.41 J/mol) estimate implies an enhanced randomness on the solid/liquid periphery during adsorption. In the case of lemon peel, the Pb(II) adsorption spontaneity is reduced by temperature. The negative ∆ H° (−32.71 kJ/mol) estimate implied an exothermic adsorption nature. The ∆ S° parameter was (−70.17 J/mol.K) for lemon peel, indicating that the Pb(II) in the bulk phase was more disorderly. Scanning electron microscopy exhibits a distinctive development in the adsorbent surface. The removal efficiency reached 92.34 and 90.4 for lemon peel and orange peel, respectively, at 0.2 mol/L KOH. Molecular electrostatic potential, frontier molecular orbital, and the density of states analysis were conducted to investigate the important active sites on the adsorption.
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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".