Cobalt recovery from leached solutions of lithium‐ion batteries using waste materials as adsorbents
Bibliographic record
Abstract
Abstract In this research, chitin and rice husks were used as adsorbents to recover cobalt from leached solutions of lithium‐ion batteries. The waste materials were obtained and characterized. At first, the adsorption study was performed in batch systems using synthetic solutions, where the pH effect, kinetic, equilibrium, and thermodynamic aspects were investigated. Later, in the best conditions, chitin and rice husks were applied to recover cobalt from real leached solutions of lithium‐ion batteries. For both materials, the adsorption was favoured at pH = 6.0. The maximum adsorption capacities were 50.0 mg g−1 and 17.6 mg g−1 for chitin and rice husks, respectively, obtained at 318 K. The Co+2 recovery percentages from real leached solutions were 95.0 % and 40.0 % for chitin and rice husks respectively. These results revealed that chitin can be used as an alternative and low‐cost waste material to recover Co+2 from real leached solutions of lithium‐ion batteries.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".