Removal of Pb2+ and Cd2+ From Contaminated Water Using Activated Carbon from Canola Seed Wastes
Bibliographic record
Abstract
The objective of this work was to produce activated carbon chemically from canola seeds wastes and to apply the activated carbon produced in the sorption of Pb 2+ and Cd 2+ from contaminated water.The activation of the canola seeds wastes was performed with NaOH (1 mol L -1 ) for 6 h under constant stirring.Then the activated material was pyrolyzed for 1 h at 750 °C.The activated carbon was subjected to nitroperchloric digestion for the determination of P, K, Ca, Mg, Mn, Zn, Cu and Pb by flame atomic absorption spectrometry (FAAS).It was also realized the thermogravimetric evaluation (TG), infrared spectra (FT-IR), pHPCZ and scanning electron microscopy (SEM).The metals were evaluated for ideal amounts of adsorbent dose and pH and kinetic, thermodynamic and equilibrium parameters.The mass and pH results demonstrated that four grams of adsorbent is needed to decontaminate one liter of contaminated solution.Linearization were obtained by the mathematical models of Langmuir, Freundlich and D-R, with high capacity of removal of both metals.Thus, using canola waste to produce activated carbon it is possible to add value to the canola seed wastes, also, it contributes directly with the economic, social and environmental sustainability of this productive system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".