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Record W2032665807 · doi:10.1021/ja2111543

Screening for Superoxide Reactivity in Li-O<sub>2</sub> Batteries: Effect on Li<sub>2</sub>O<sub>2</sub>/LiOH Crystallization

2012· article· en· W2032665807 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

VenueJournal of the American Chemical Society · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChemistrySuperoxideElectrolyteElectrochemistryBattery (electricity)CrystallizationChemical engineeringReactivity (psychology)Lithium (medication)Energy storageElectrodeNanotechnologyPhysical chemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Unraveling the fundamentals of Li-O(2) battery chemistry is crucial to develop practical cells with energy densities that could approach their high theoretical values. We report here a straightforward chemical approach that probes the outcome of the superoxide O(2)(-), thought to initiate the electrochemical processes in the cell. We show that this serves as a good measure of electrolyte and binder stability. Superoxide readily dehydrofluorinates polyvinylidene to give byproducts that react with catalysts to produce LiOH. The Li(2)O(2) product morphology is a function of these factors and can affect Li-O(2) cell performance. This methodology is widely applicable as a probe of other potential cell components.

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 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 score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
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