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Record W4416252716 · doi:10.1002/bte2.20250061

Multifunctional Carbon Fiber–Nanotube Frameworks for Safe, Recyclable, High‐Performance Lithium‐Ion Batteries

2025· article· en· W4416252716 on OpenAlexafffund
Ritu Malik, Mohini Sain

Bibliographic record

VenueBattery energy · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsFord Motor Company (Canada)University of Toronto
FundersMitacsFord Motor Company
KeywordsCurrent collectorAnodeCarbon fibersCarbon nanotubeGraphiteFaraday efficiencyElectrodeNanoarchitectures for lithium-ion batteriesEnergy storage

Abstract

fetched live from OpenAlex

ABSTRACT This study introduces a multifunctional carbon fiber–carbon nanotube (CFCNT) architecture as a lightweight, thermally stable, and recyclable current collector for lithium‐ion batteries (LIBs). Compatible with both graphite anodes and LiFePO 4 cathodes, the CFCNT platform reduces collector mass to 4.4 mg/cm 2 —substantially lower than conventional copper (10.1 mg/cm 2 ) and aluminum (5.1 mg/cm 2 ) while enhancing electrical conductivity and interfacial stability. Full pouch cells employing CFCNT collectors achieve an initial capacity of 153 mAh/g and retain 126 mAh/g after 150 cycles (0.11% fade per cycle), with > 91% coulombic efficiency. Safety testing reveals minimal thermal response (< 2°C rise) during nail penetration, underscoring robust mechanical and electrochemical resilience. Critically, the architecture enables direct recovery and reuse of electrodes and current collectors, supporting a closed‐loop recycling strategy. These results position CFCNT collectors as a viable pathway toward safer, high‐performance, and circular energy storage technologies.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score1.000

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)0.0010.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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