Compost from poultry hatchery waste as a biosorbent for removal of Cd(II) and Pb(II) from aqueous solutions
Bibliographic record
Abstract
Abstract Compost from poultry hatchery waste (CPHW) was used as an efficient biosorbent for the removal of heavy metals from aqueous solutions. Single and competitive adsorption of Cd(II) and Pb(II) onto CPHW were studied. The optimum pH of the aqueous solution for Cd(II) and Pb(II) adsorption was found to be in the range 3 to 5. The pseudo‐second order model enabled a better description of the adsorption kinetics. Equilibrium data obtained at 25, 35, and 45 °C were better described by the Sips isotherm than by the Freundlich and Langmuir models. The maximum adsorption capacities calculated by applying the Sips isotherm were 32.3 mg/g for Cd(II) and 142.6 mg/g for Pb(II) at 25 °C. In binary metal ion solutions, a decrease in the adsorption capacity for both heavy metals was observed. The single and competitive adsorption tests revealed that the adsorption affinity was higher for Pb(II) than for Cd(II). Thermodynamic parameters such as ΔG0, ΔH0, and ΔS0 indicated that the adsorption was feasible, spontaneous, and endothermic. FTIR spectroscopy characterization showed that carboxyl and hydroxyl groups were involved in the adsorption of the metals. SEM‐EDX analysis confirmed that Cd(II) and Pb(II) may replace Ca(II) from biosorbent surface. Therefore, the results suggest that CPHW can be used as an economical biosorbent for Pb(II) and Cd(II) removal from aqueous solutions.
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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".