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Record W2133125942 · doi:10.4236/aces.2012.23037

Enhanced Electrochemical Properties of LiFePO<sub>4</sub> as Positive Electrode of Li-Ion Batteries for HEV Application

2012· article· en· W2133125942 on OpenAlexaff
C. Julien, Karim Zaghib, A. Mauger, Henri Groult

Bibliographic record

VenueAdvances in Chemical Engineering and Science · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsElectrochemistryElectrodeMaterials scienceGraphiteIonFOIL methodDissolutionChemical engineeringLithium (medication)Inorganic chemistryAnalytical Chemistry (journal)ChemistryMetallurgyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

LiFePO4 materials synthesized using FePO4(H2O)2 and Li2CO3 blend were optimized in view of their use as positive electrodes in Li-ion batteries for hybrid electric vehicles. A strict control of the structural properties was made by the combination of X-ray diffraction, FT-infrared spectroscopy and magnetometry. The impact of the ferromagnetic clus-ters (γ-Fe2O3 or Fe2P) on the electrochemical response was examined. The electrochemical performances of the opti-mized LiFePO4 powders investigated at 60℃ are excellent in terms of capacity retention (153 mAh·g-1 at 2C) as well as in terms of cycling life. No iron dissolution was observed after 200 charge-discharge cycles at 60℃ for cells containing Li foil, Li4Ti5O12, or graphite as negative electrodes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.172
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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 designBench or experimental
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

Citations42
Published2012
Admission routes1
Has abstractyes

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