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Record W2028306056 · doi:10.1039/c2jm35538h

Atomistic modeling of site exchange defects in lithium iron phosphate and iron phosphate

2012· article· en· W2028306056 on OpenAlexaff
Christian Kuß, Guoxian Liang, Steen B. Schougaard

Bibliographic record

VenueJournal of Materials Chemistry · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsLithium (medication)DiffusionLithium iron phosphateChemistryIonPhosphateIron phosphateInorganic chemistryIon exchangeThermodynamicsMaterials sciencePhysical chemistryElectrodeElectrochemistryPhysics

Abstract

fetched live from OpenAlex

A new set of potentials is presented that allows for modeling of the entire lithium insertion range of the lithium iron phosphate system (LixFePO4, 0 ≤ x ≤ 1). By comparing calculated values to experimental crystallographic, spectroscopic and thermodynamic data, the potentials ability to reproduce experimental results consistently and reliably is demonstrated. Calculations of site exchange defect thermodynamics and diffusion barriers for lithium and iron inside the lithium diffusion path suggest that the site exchange defect related capacity loss may be justified exclusively by thermodynamic considerations. Moreover, a low activation barrier for iron transport in the lithium diffusion channel in FePO4 brings into question the significance of the antisite iron ion as an obstacle to lithium diffusion.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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 designSimulation or modeling
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

Citations32
Published2012
Admission routes1
Has abstractyes

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