MétaCan
Menu
Back to cohort
Record W2339933036 · doi:10.1149/2.0801607jes

ARC Study of LiFePO<sub>4</sub>with Different Morphologies Prepared via Three Synthetic Routes

2016· article· en· W2339933036 on OpenAlexafffund
Soumia El Khakani, Dominic Rochefort, Dean D. MacNeil

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsNational Research Council CanadaUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologies
KeywordsEthylene carbonateElectrolyteLithium iron phosphateChemistryCathodeSolventThermal stabilityInorganic chemistryChemical engineeringCarbonateLithium (medication)ElectrochemistryElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

We report on the thermal stability of lithium iron phosphate (LiFePO 4 ) cathode material as investigated by accelerating rate calorimetry (ARC). LiFePO 4 (LFP) was prepared using three different synthetic methods, namely, solid state (P1), hydrothermal (P2) and molten state (P3) and have different particle sizes (in the range of ∼100 nm–3 μm) and different surface areas (in the range of ∼6–14 m 2 g −1 ). The thermal stability was evaluated, prior and after charging LiFePO 4 , in the presence of either carbonate solvents (ethylene carbonate (EC): diethyl carbonate (DEC) (1:2 v/v)) or electrolyte (1 M LiPF 6 in the same solvent). In the presence of the electrolyte, LiFePO 4 is shown to be stable up to 280°C or 220°C for uncharged or charged cathode materials, respectively. The surface area of LiFePO 4 is found to affect the initial self-heating rate (SHR) of the charged materials reaction with the electrolyte, while the presence of the LiPF 6 salt reduces significantly the SHR of the combustion reaction of carbonates solvent initiated by the oxygen released from the cathodes; forming Fe 2 P 2 O 7 at elevated temperatures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicAdvancements in Battery MaterialsFrench-language works237,207