Sustainable Management of Spent Lithium-Ion Batteries: The Role of Reverse Logistics in the Automotive Sector
Bibliographic record
Abstract
In this age of global advancement in technology, environmental sustainability has become increasingly important. Electric vehicles (EVs) have gained popularity due to their lower carbon impact. One of the most important components of an electric vehicle (EV) is its lithium-ion battery. Increased use of lithium-ion battery (LIB) packs has produced a possible concern in the form of excess LIBs unless adequate recycling or remanufacturing procedures are followed. To repurpose previously used LIBs in an eco-friendly and efficient way, it is essential to implement appropriate reverse logistics procedures. This field of research holds significant potential for the future of the automotive sector. In this study, we briefly reviewed spent LIB management, recycling procedures, demographic locations, remanufacturing concerns, transportation costs, deterioration, and regulations in North America. A brief review of the reverse logistics for lithium-ion batteries improves comprehension and paves the way for future research considerations in this evolving field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".