Sélectivité des écailles de cacao pour l'enlèvement des métaux des effluents de décontamination de sols
Bibliographic record
Abstract
Washing using inorganic acids is a common method for treatment of metal-polluted soils. Metals solubilized during soil washing have to be removed from washing solutions (leachates). The purpose of this research was to evaluate the efficiency and the selectivity of cocoa shells to adsorb metals contained in acid leachates of soil decontamination. Shake flask experiments were done using 15 g/L of cocoa shells and a doped (addition of 100 and 300 mg metal/L) acid leachate (pH i = 2.4) using 1 or 10 metal salts. These tests have revealed that this natural sorbent is particularly efficient to remove lead and, to a lesser degree, copper from solution. A maximal lead concentration of 17 900 mg/kg, corresponding to 75 % of lead removal, has been adsorbed on cocoa shells during tests using a soil leachate doped with 300 mg Pb/L. This research also showed that cocoa shell selectivity generally follows this order: Pb >> Cu >> Fe > Al > Cr >> Co > Zn > Mn > Cd > Ni. Kinetic studies over a 24-h period have indicated that the equilibrium of metals adsorption is almost reached in the first 2 h of contact. Moreover, metal uptake on cocoa shells is controlled by an ion-exchange mechanism involving magnesium and potassium release from the adsorbent. Finally, cocoa shells are a promising natural adsorbent for the treatment of metal-contaminated acid effluents and particularly for the removal of lead from these solutions. Key words: adsorption, metals, lead, cocoa shells, leachate, soils.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".