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Record W2026369224 · doi:10.1039/c0jm04190d

Surface effects on electrochemical properties of nano-sized LiFePO4

2011· article· en· W2026369224 on OpenAlex
C. Julien, A. Mauger, Karim Zaghib

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.

Bibliographic record

VenueJournal of Materials Chemistry · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsMaterials scienceIonMagnetismScanning electron microscopeElectrochemistryElectronElectrodeNanotechnologyDiffractionSurface modificationImpurityHumidityAnalytical Chemistry (journal)Chemical engineeringOpticsComposite materialCondensed matter physicsChemistryPhysical chemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

LiFePO4 has won the challenge to be the active element for the positive electrode of Li-ion batteries for electromobility. In an attempt to optimize the electrochemical performance, efforts have been made to reduce the size of the particles, so that the electrons and Li+ ions have a reduced path to travel inside the material. However, when the size decreases below 100 nm, surface effects become increasingly important, and can eventually dominate the physical and the chemical properties. The purpose of this work is to review them and their implications, involving sensitivity to exposure to humidity, and separate between surface disorder effects, impurities and intrinsic properties. This goal is achieved by the combination of different techniques to characterize the particles, including X-ray diffraction, electron microscope imaging, optical spectroscopy, and magnetism.

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 score0.001
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.207
Teacher spread0.193 · 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