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Record W2064281777 · doi:10.1021/nn505337p

The Importance of Nanometric Passivating Films on Cathodes for Li–Air Batteries

2014· article· en· W2064281777 on OpenAlexafffund
Brian D. Adams, Robert W. Black, C. Radtke, Zack Williams, B. Layla Mehdi, Nigel D. Browning, Linda F. Nazar

Bibliographic record

VenueACS Nano · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersBasic Energy SciencesNatural Resources CanadaBiological and Environmental ResearchNatural Sciences and Engineering Research Council of CanadaOffice of ScienceConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsOverpotentialMaterials scienceLithium (medication)ElectrochemistryX-ray photoelectron spectroscopyChemical engineeringCarbon fibersCathodeRedoxCrystalliteNanoparticleBattery (electricity)ElectrodeNanotechnologyInorganic chemistryChemistryComposite materialPhysical chemistry

Abstract

fetched live from OpenAlex

Recently, there has been a transition from fully carbonaceous positive electrodes for the aprotic lithium oxygen battery to alternative materials and the use of redox mediator additives, in an attempt to lower the large electrochemical overpotentials associated with the charge reaction. However, the stabilizing or catalytic effect of these materials can become complicated due to the presence of major side-reactions observed during dis(charge). Here, we isolate the charge reaction from the discharge by utilizing electrodes prefilled with commercial lithium peroxide with a crystallite size of about 200-800 nm. Using a combination of S/TEM, online mass spectrometry, XPS, and electrochemical methods to probe the nature of surface films on carbon and conductive Ti-based nanoparticles, we show that oxygen evolution from lithium peroxide is strongly dependent on their surface properties. Insulating TiO2 surface layers on TiC and TiN - even as thin as 3 nm-can completely inhibit the charge reaction under these conditions. On the other hand, TiC, which lacks this oxide film, readily facilitates oxidation of the bulk Li2O2 crystallites, at a much lower overpotential relative to carbon. Since oxidation of lithium oxygen battery cathodes is inevitable in these systems, precise control of the surface chemistry at the nanoscale becomes of upmost importance.

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 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 score0.059
Threshold uncertainty score0.368

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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 teacher head, 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

Citations133
Published2014
Admission routes2
Has abstractyes

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