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Record W2332658667 · doi:10.1021/acs.nanolett.5b00326

New Lithium Metal Polymer Solid State Battery for an Ultrahigh Energy: Nano C-LiFePO<sub>4</sub> versus Nano Li<sub>1.2</sub>V<sub>3</sub>O<sub>8</sub>

2015· article· en· W2332658667 on OpenAlex
Pierre Hovington, Marin Lagacé, Abdelbast Guerfi, Patrick Bouchard, A. Mauger, C. Julien, Michel Armand, 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

VenueNano Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsMaterials scienceVanadiumNano-Lithium (medication)ElectrolyteDissolutionElectrochemistryBattery (electricity)Lithium iron phosphateElectrodeLithium batteryChemical engineeringMetalPolymerNanoparticleLithium vanadium phosphate batteryNanotechnologyChemistryPhysical chemistryMetallurgyIonComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Novel lithium metal polymer solid state batteries with nano C-LiFePO4 and nano Li1.2V3O8 counter-electrodes (average particle size 200 nm) were studied for the first time by in situ SEM and impedance during cycling. The kinetics of Li-motion during cycling is analyzed self-consistently together with the electrochemical properties. We show that the cycling life of the nano Li1.2V3O8 is limited by the dissolution of the vanadium in the electrolyte, which explains the choice of nano C-LiFePO4 (1300 cycles at 100% DOD): with this olivine, no dissolution is observed. In combination with lithium metal, at high loading and with a stable SEI an ultrahigh energy density battery was thus newly developed in our laboratory.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.066
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.244
Teacher spread0.222 · 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