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Record W2159145669 · doi:10.1149/2.060309jes

Predicting and Extending the Lifetime of Li-Ion Batteries

2013· article· en· W2159145669 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of The Electrochemical Society · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsE-One Moli Energy (Canada)Dalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBattery (electricity)ElectrolyteWarrantyIonMaterials scienceFaraday efficiencyElectrical impedanceNuclear engineeringAutomotive engineeringReliability engineeringChemistryElectrical engineeringEngineeringThermodynamicsElectrodePower (physics)Physics

Abstract

fetched live from OpenAlex

Battery and EV manufacturers carry out extensive long-term tests to estimate the lifetime of the battery and base warranty durations on those tests. The long duration of these tests slows progress in the research and development required to improve the lifetime of Li-ion batteries. This paper shows that accurate measurements of coulombic efficiency (CE) and impedance spectra of Li-ion batteries, that take a few weeks to acquire, can be used to rank the resulting lifetime of Li-ion cells. Adding one or more electrolyte additives to Li-ion batteries that act synergistically can dramatically improve the CE and long-term tests show corresponding ten-fold improvements in lifetime.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.192

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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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