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Record W2003502757 · doi:10.1155/2013/706513

Nanostructured TiO<sub>2</sub> Doped with Nb as a Novel Support for PEMFC

2013· article· en· W2003502757 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 Materials · 2013
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsPolytechnique Montréal
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsProton exchange membrane fuel cellMaterials scienceCatalysisDurabilityOxideDispersion (optics)Carbon fibersCatalyst supportElectrochemistryChemical engineeringDopingConductivityMetalNanotechnologyComposite materialMetallurgyChemistryElectrodeComposite numberPhysical chemistry

Abstract

fetched live from OpenAlex

Nowadays, one of the major issues of the PEMFC concerns the durability. Historically, carbon has been used as a catalyst support in PEMFC; nevertheless, under the environmental conditions of the cell, the carbon is oxidized, leaving the catalyst unsupported. In order to increase the stability and durability of the catalyst in the PEMFC, a novel nanostructured metallic oxide support is proposed. In this work, TiO 2 was doped with Nb to obtain a material that combines chemical stability, high surface area, and an adequate electronic conductivity in order to be a successful catalyst support candidate for long-term PEMFC applications. The TiO 2 -Nb nanostructured catalyst support was physically and electrochemically characterized. According to the results, the TiO 2 -Nb offers high surface area and good particle dispersion; also, the electrochemical activity and stability of the support were evaluated under high potential conditions, where the TiO 2 -Nb proved to be much more stable than carbon.

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)0.000
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 score0.005
Threshold uncertainty score0.894

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)0.0010.000

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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