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Record W1969996112 · doi:10.1021/cm800713g

Formation of a Porous Platinum Nanoparticle Froth for Electrochemical Applications, Produced without Templates, Surfactants, or Stabilizers

2008· article· en· W1969996112 on OpenAlexaff
De‐Quan Yang, Shuhui Sun, Hui Meng, Jean‐Pol Dodelet, E. Sacher

Bibliographic record

VenueChemistry of Materials · 2008
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsPolytechnique MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsNanoporousPorosityX-ray photoelectron spectroscopyChemical engineeringNanoparticleMaterials sciencePlatinumAqueous solutionFormic acidPlatinum nanoparticlesCarbon blackPlatinum blackColloidElectrochemistryNanotechnologyCatalysisChemistryOrganic chemistryElectrodeComposite material

Abstract

fetched live from OpenAlex

Pt nanoparticles (NPs), synthesized via the reduction of H 2 PtCl 6 by formic acid at 80 °C, formed a nanoporous froth at the upper surface of the aqueous solution in which they were produced. The NPs, brought to the surface by the escape of CO 2 bubbles produced by the reduction, partly coalesced to form a froth film with a porosity >95%. Scanning and transmission electron microscopies were used to characterize the froth morphology and the NP dimensions, and X-ray photoelectron spectroscopy was used to characterize the NP surface chemistry. The froth was found to be composed of 3−5 nm zerovalent Pt NPs. The porous froth films, which could be removed and handled, demonstrated an electroactive surface area of 168 ± 8 m 2 /g Pt, more than 4 times that of a commercial colloidal Pt black, and equivalent to that of the best Pt particle/carbon black electrocatalysts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
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 head0.023
GPT teacher head0.266
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2008
Admission routes1
Has abstractyes

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