All-dry upcycling of used cathodes to single-crystal LiNi0.8Mn0.1Co0.1O2 for Lithium-ion batteries
Bibliographic record
Abstract
The growing demand for lithium-ion batteries (LIBs) has resulted in a rise in the production and disposal of LiNi x Mn y Co z O 2 (x + y + z = 1) (NMC) cathodes, creating significant environmental and economic challenges. Effective recycling or upcycling of NMC cathodes is crucial to address these concerns and maintain the supply chain for essential materials. Herein, we report an all-dry upcycling method, directly converting used cathodes including LiCoO 2 (LCO), LiMn 2 O 4 (LMO), LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622), LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811), and their mixtures, to single-crystal NMC811. Phase-pure NMC811 with low levels of impurities were upcycled from all of previously mentioned used cathodes. However, it was found that the crystal structure, homogeneity, and electrochemical performance of the NMC811 product depended on the used cathode material employed in its synthesis. Of these, the single-crystal NMC811 upcycled from used LCO had the highest performance with 207.09 mAh/g (at C/20) initial discharge capacity, 89.71 % initial coulombic efficiency and improved cycling performance compared to commercial NMC811. Our study presents a practical approach for cost-effective upcycling in the sustainable development of NMC batteries, paving the way for the recycling and upcycling of next generation LIBs. • All-dry method directly upcycles used cathodes into single-crystal NMC811 • Electrochemical performance of upcycled NMC811 depends on the type of used cathode • Upcycled NMC811 from LCO exhibits a reversible capacity of 207.09 mAh/g • This work enables practical upcycling for sustainable Li-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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".