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Record W2316519985 · doi:10.1021/jp308093b

Chemical and Morphological Changes of Li–O<sub>2</sub> Battery Electrodes upon Cycling

2012· article· en· W2316519985 on OpenAlexaff
Betar M. Gallant, Robert Mitchell, David G. Kwabi, Jigang Zhou, Lucia Zuin, Carl V. Thompson, Yang Shao‐Horn

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
Fundersnot available
KeywordsXANESElectrolyteElectrodeTransmission electron microscopySelected area diffractionBattery (electricity)ChemistryChemical engineeringCarbon nanotubeMaterials scienceNanotechnologyPhysical chemistry

Abstract

fetched live from OpenAlex

We report considerable chemical and morphological changes of reaction products in binder-free, vertically aligned carbon nanotube (VACNT) electrodes during Li–O 2 battery cycling with a 1,2-dimethoxyethane (DME)-based electrolyte. X-ray absorption near edge structure (XANES) of discharged oxygen electrodes shows direct evidence for the formation of Li 2 CO 3 -like species at the interface between VACNTs and Li 2 O 2 but not significantly on the Li 2 O 2 surfaces exposed to the electrolyte. Although Li 2 O 2 and Li 2 CO 3 -like species were largely removed upon first charge, the oxidation kinetics became increasingly difficult during Li–O 2 cycling, which is accompanied by the accumulation of Li 2 CO 3 in the discharged and charged electrodes as evidenced by selected area electron diffraction (SAED) and transmission electron microscopy (TEM). Together, these results indicate that the irreversibility during Li–O 2 cycling in DME can be attributed largely to the growth of Li 2 CO 3 -like species associated with the reactivity between carbon and Li 2 O 2 or other reaction intermediates.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.011
GPT teacher head0.229
Teacher spread0.219 · 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

Citations378
Published2012
Admission routes1
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicAdvancements in Battery MaterialsFrench-language works237,207