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Record W2159625236 · doi:10.1039/c5nr00303b

First-time electrical characterization of nanotubular ZrO<sub>2</sub> films for micro-solid oxide fuel cell applications

2015· article· en· W2159625236 on OpenAlexafffund
Aligül Büyükaksoy, Tobias Fürstenhaupt, Viola Birss

Bibliographic record

VenueNanoscale · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology FuturesUniversity of Calgary
KeywordsSolid oxide fuel cellMaterials scienceCharacterization (materials science)Fuel cellsOxideNanotechnologyChemical engineeringChemistryElectrodeMetallurgyPhysical chemistryAnode

Abstract

fetched live from OpenAlex

In this work, anodically grown ZrO2 nanotubes (NTs) are examined for the first time for use in micro solid oxide fuel cell (μ-SOFC) applications. This is due to their high surface area to volume ratio and useful nanoscale morphological features (e.g., 5-100 nm thick NT bases that could serve as the electrolyte layer). To understand their full potential for these applications, the determination of their electrical properties is necessary. Therefore, ZrO2 NTs, in the form of a uniform and crack-free film, were obtained by the two-step anodization of Zr foil in aqueous solutions. The films exhibited excellent adhesion to the Zr substrate, which facilitated impedance spectroscopy analyses, used for the first time to obtain the resistivity of the nanotubular array separately from the contact resistances. This gave a conductivity of the ZrO2 NTs of 1.6 × 10(-6) S cm(-1) at 600 °C in N2, approximately twice that reported for dense ZrO2 films measured at the same temperature in air, and also a very reasonable activation energy of 0.90 eV in the 400-600 °C temperature range.

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 score0.037
Threshold uncertainty score0.995

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)0.0000.001

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 head0.241
Teacher spread0.230 · 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

Citations5
Published2015
Admission routes2
Has abstractyes

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