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Record W4403894489 · doi:10.3390/engproc2024076061

Sustainable Management of Spent Lithium-Ion Batteries: The Role of Reverse Logistics in the Automotive Sector

2024· article· en· W4403894489 on OpenAlex
Md. Shahariar Ahmed, Sheikh Md Shahadat Kabir, Arafat Sultan Khan, Sharfuddin Ahmed Khan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsReverse logisticsAutomotive industryLithium (medication)BusinessAutomotive engineeringWaste managementManufacturing engineeringEngineeringSupply chainMarketing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.248
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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