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Record W4210440672 · doi:10.1007/s12274-021-4049-9

Synergistic combination of Pd nanosheets and porous Bi(OH)3 boosts activity and durability for ethanol oxidation reaction

2022· article· en· W4210440672 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

VenueNano Research · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern University
Fundersnot available
KeywordsCatalysisAdsorptionEthanolStripping (fiber)DurabilityChemical engineeringMaterials scienceEthanol fuelChemistryPalladiumInorganic chemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Highly active and durable Pd-based electrocatalysts for ethanol oxidation reaction (EOR) play a crucial role in the commercialization of direct ethanol fuel cells (DEFCs). However, the poisonous intermediates (especially adsorbed CO species (COad)) formed during the EOR process can easily adsorb and block the active sites on Pd electrodes, which in turn limits the catalytic efficiency. Hence, we present a series of Pd-based composites with a strong coupling interface consisting of Pd nanosheets and amorphous Bi(OH)3 species. The incorporation of Bi(OH)3 can induce an electron-rich state adjacent to the Pd sites and effectively separate the Pd ensemble, leading to excellent CO tolerance. The optimal Pd-Bi(OH)3 NSs catalyst manifests a mass activity of 2.2 A·mgPd−1, which is 5.7 and 2.0 times higher than that of Pd NSs and commercial Pd/C catalyst, respectively. Further CO-stripping experiments and CO-DRIFTS tests confirm the excellent CO tolerance on Pd-Bi(OH)3 NSs electrode, leading to the enhanced EOR durability.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.037
GPT teacher head0.322
Teacher spread0.285 · 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