A Novel Layered Roasting Strategy for Spent LiCoO<sub>2</sub> Batteries: Toward Cleaner Lithium Extraction and Low Residue Processing
Bibliographic record
Abstract
The green and efficient recycling of valuable metals from spent lithium-ion batteries (LIBs) is of great significance for ensuring the security of national strategic mineral resources and achieving sustainable development. Aiming at the technical bottlenecks of traditional roasting processes, such as high yield of water-leaching slag, low comprehensive recovery rate of valuable metals, and high risk of secondary pollution, this study developed a novel layered roasting process based on gradient isolation of raw materials. The results show that under the optimal conditions, the recovery rate of lithium can reach 84.10%, and the production of water-leaching slag is reduced by 66.71%. Li 2 CO 3 products with a purity of 99.74% can be obtained from the water-leaching solution, meeting the purity standard (≥99.5%) for battery-grade Li 2 CO 3 . The pressurized leaching process of water-leaching slag can realize the recovery of cobalt and prepare CoSO 4 ·6H 2 O products. This process not only reduces the production of water-leaching slag but also achieves high metal recovery rates, providing new ideas for the optimization of sulfide roasting processes.
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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 | 0.000 | 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 | 0.001 |
| 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".