MétaCan
Menu
Back to cohort
Record W2964253484 · doi:10.1021/acsaem.9b00625

Oxidation and Corrosion of Platinum–Nickel and Platinum–Cobalt Nanoparticles in an Aqueous Acidic Medium

2019· article· en· W2964253484 on OpenAlexafffund
Sadaf Tahmasebi, Soran Jahangiri, Nicholas J. Mosey, Gregory Jerkiewicz, Stéve Baranton, Christophe Coutanceau, Yoshihisa Furuya, Atsushi Ohma

Bibliographic record

VenueACS Applied Energy Materials · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's UniversityCanada Foundation for Innovation
KeywordsNanomaterial-based catalystPlatinumCyclic voltammetryMaterials scienceCobaltNickelThermogravimetric analysisCrystalliteNanoparticleAqueous solutionNuclear chemistryChemical engineeringInorganic chemistryElectrochemistryCatalysisChemistryNanotechnologyMetallurgyPhysical chemistryOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

We report on the synthesis, characterization, and corrosion behavior of randomly oriented platinum–nickel and platinum–cobalt nanoparticles (PtNi-NPs, PtCo-NPs). Unsupported and carbon-supported nanocatalysts were synthesized using the “water-in-oil” microemulsion method. X-ray diffraction (XRD) was used to examine their average crystallite size, which was 2.3 nm in both cases. The shape, size, and size distribution of the nanoparticles were evaluated using transmission electron microscopy (TEM); they were determined to be spherelike with an average size of 3.3 and 3.2 nm for PtNi-NPs and PtCo-NPs, respectively, and a narrow size distribution. Comparison of the XRD and TEM data indicated that the nanocatalysts were polycrystalline in nature. Thermogravimetric analysis (TGA) measurements were carried out to evaluate the metal loadings of the carbon-supported nanocatalysts, which were 38.1 wt % for PtNi-NPs and 40.8 wt % for PtCo-NPs. Static Density Functional Theory (DFT) calculations were performed to analyze the structures and energetics of the PtNi and PtCo systems; it was found that the presence of Ni and Co introduced ca. 8% of volume reduction, as compared to the volume of pure, bulk Pt. Cyclic voltammetry (CV) measurements at potential scan rates of 5.0 and 50.0 mV s–1 in 0.50 M aqueous H2SO4 indicated that the specific surface areas (As) of the PtNi-NPs and PtCo-NPs were 74.5 m2 gPt–1 and 33.1 m2 gPt–1, respectively. In situ confocal Raman spectroscopy was successfully used to monitor the formation and reduction of surface oxide layers in the submonolayer and monolayer ranges. Corrosion of the nanocatalysts was studied using anodic and cathodic potentiodynamic polarization (PDP) measurements at a very low potential scan rate of s = 0.10 mV s–1 in 0.50 M aqueous H2SO4 saturated with different gases (N2(g), O2(g), or H2(g)). The nature of the dissolved gas had a profound impact on the corrosion characteristics of the nanoparticles. The nanocatalysts were stable in the electrolyte saturated with H2(g) and underwent slight corrosion in the electrolyte saturated with N2(g) and significant corrosion in the electrolyte saturated with O2(g). The carbon support was also observed to undergo corrosion and porosity changes. The degradation of the nanocatalysts was more pronounced in the case of the anodic PDP measurements than the cathodic ones. Cyclic voltammetry was employed to analyze the loss of As of the nanocatalysts as a result of PDP measurements, and the results were found to corroborate the corrosion data. Evolution of the value of As of the nanocatalysts in 0.50 M aqueous H2SO4 outgassed using N2(g) was examined by recording 500 CV transients in the 0.05 V ≤ E ≤ 1.45 V range at s = 50.0 mV s–1. It was found that in both cases this treatment resulted in a 50% reduction in As.

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 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 score0.049
Threshold uncertainty score1.000

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)0.0000.000

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 head0.207
Teacher spread0.201 · 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.

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

Citations20
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueACS Applied Energy MaterialsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207