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Record W2412610340 · doi:10.3390/inorganics4020017

Olivine-Based Blended Compounds as Positive Electrodes for Lithium Batteries

2016· article· en· W2412610340 on OpenAlex

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

VenueInorganics · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
FundersUniversité Pierre et Marie Curie
KeywordsOlivineLithium (medication)ElectrodeMaterials scienceChemical engineeringOptoelectronicsNanotechnologyEngineering physicsMineralogyChemistryPsychologyEngineeringPhysical chemistry

Abstract

fetched live from OpenAlex

Blended cathode materials made by mixing LiFePO4 (LFP) with LiMnPO4 (LMP) or LiNi1/3Mn1/3Co1/3O2 (NMC) that exhibit either high specific energy and high rate capability were investigated. The layered blend LMP–LFP and the physically mixed blend NMC–LFP are evaluated in terms of particle morphology and electrochemical performance. Results indicate that the LMP–LFP (66:33) blend has a better discharge rate than the LiMn1−yFeyPO4 with the same composition (y = 0.33), and NMC–LFP (70:30) delivers a remarkable stable capacity over 125 cycles. Finally, in situ voltage measurement methods were applied for the evaluation of the phase evolution of blended cathodes and gradual changes in cell behavior upon cycling. We also discuss through these examples the promising development of blends as future electrodes for new generations of Li-ion batteries.

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 score0.183
Threshold uncertainty score0.665

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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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