Lead Removal from Acidic Solutions by Sorption on Cocoa Shells: Effect of Some Parameters
Bibliographic record
Abstract
The objectives of this work were to evaluate the effects of different parameters (Pb concentration, solution pH, Ca/Mg/Na/K salt concentrations) on Pb uptake by cocoa shells and to study the mechanisms of Pb removal in very acidic conditions. Sorption tests were conducted in shaken flasks with synthetic Pb solutions and 15 g/L cocoa shells. A lead uptake value of 161 mmol/kg was measured during the assay with [Pb]i=3.66 mmol/L in solution at pHi=2.0 and T=22°C. Results show that Pb uptake is very similar (14.5–16.0 mmol/kg) for an initial pH between 2.0 and 4.0, but a moderate decrease (10.8 mmol/kg) occurred when the initial pH=1.5 and the [Pb]i=0.25 mmol/L. High Ca and Mg concentrations (2.35 mol/L) in solution induced a significant decrease in Pb removal by cocoa shells, whereas high K and Na concentrations did not affect Pb uptake by this sorbent. This suggests that Pb uptake by cocoa shells is controlled by ion-exchange reactions with Ca/Mg ions and protons. Finally, chemical tests have shown that carboxyl and amine functional groups play a dominant role in Pb uptake by cocoa shells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".