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Record W2099966681 · doi:10.1149/1.2795101

Temperature Effect on LiFePO4 Cathode Performance

2007· article· en· W2099966681 on OpenAlexaff
Abdelbast Guerfi, Nathalie Ravet, Patrick Charest, Martin Dontigny, Michel Petitclerc, M. Gauthier, Karim Zaghib

Bibliographic record

VenueECS Transactions · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversité de MontréalHydro-Québec
Fundersnot available
KeywordsCathodeMaterials scienceFadeWettingComposite materialLithium iron phosphateCarbon blackElectrodeCarbon fibersParticle sizeComposite numberChemical engineeringLithium (medication)Analytical Chemistry (journal)ElectrochemistryChemistryChromatography

Abstract

fetched live from OpenAlex

Two forms of LiFePO4 material were evaluated in lithium cells. One type of LiFePO4 (PI) that has a particle size ranging from 1-5 µm is compared to LiFePO4 (P-II) consisting of nano-particles. Coated electrodes on Al-carbon with thickness varying from 18 to 25 µm were used in this study. The addition of VGCF carbon fiber greatly improved the rate capability at low temperature. This suggests a good conductivity networking and wettability in the cathode. LiFePO4 (P-II) has improved the low- and high-rate discharge capacity. When VGCF fibers were combined with LiFePO4 (P-II) in the same composite cathode, the high rate capacity at 12C was increased by 51% compared to LiFePO4 (P-I) cathode with carbon black. At -10{degree sign}C and at 2C rate, 90 mAh/g was delivered from the cell. Cycling at 60{degree sign}C occurred with negligible capacity fade after 400 cycles. Furthermore, the cell was capable of good performance at high rate with 120 mAh/g at 10C, and it still has a good reserve at 25C with 73mAh/g.

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 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 score0.306
Threshold uncertainty score0.530

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 head0.007
GPT teacher head0.232
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2007
Admission routes1
Has abstractyes

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