Cathode regeneration processes enabled transition from spent batteries to lithium-ion alternatives
Bibliographic record
Abstract
Abstract The development of electric vehicles is accelerating the world's transition to sustainable energy, but the millions of end-of-life electric vehicles generated over the next decade pose serious waste management challenges, especially the recycling of spent batteries. Here we propose two cathode regeneration processes to enable scalable and affordable recycling of spent lithium-ion batteries (LIBs) into brand-new LIBs and their alternatives, such as sodium-ion batteries (SIBs). The regenerated layered oxide materials deliver a reversible area capacity of up to 2.73 mAh cm− 2 with excellent structural stability for LIBs, while obtained cyanide complex manifests an 83.7% retention over 2000 cycles for SIBs and robust cycling stability for pouch cells. By contrast, the manufacturing costs for LIBs and SIBs using our regenerated materials have dropped to an all-time low of $47.16 and $37.49 per kWh, with conspicuous reductions in energy consumption, water consumption, and harmful gas emissions. Our sustainable battery recycling designs pave the way for the transition to more sustainable energy storage technologies, enabling post-LIBs with regenerated materials.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".