MétaCan
Menu
Back to cohort
Record W2622973924 · doi:10.1002/ppsc.201700051

The 3D Nanoscale Evolution of Platinum–Niobium Oxide Fuel Cell Catalysts via Identical Location Electron Tomography

2017· article· en· W2622973924 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueParticle & Particle Systems Characterization · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)McMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPlatinumDissolutionOxideMaterials scienceCatalysisNiobium oxideCorrosionElectrolyteCarbon fibersProton exchange membrane fuel cellChemical engineeringNiobiumInorganic chemistryMetallurgyComposite materialChemistryElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Current state‐of‐the‐art catalysts for polymer electrolyte membrane fuel cells, comprised of platinum nanoparticles on a high surface area carbon support, are susceptible to platinum dissolution and carbon support corrosion during operation. The use of transition metal oxides in the support material is proposed to stabilize the catalyst material by minimizing platinum dissolution and carbon corrosion. Here, the 3D structural changes are tracked for a hybrid Pt–Nb oxide on carbon catalyst before and after potential cycling utilizing identical location electron tomography. Pt dissolution is observed to varying degrees in both high and low Nb oxide content structures and appreciable carbon support corrosion in the high Nb oxide content structure but not in the low Nb oxide structure.

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 score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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