MétaCan
Menu
Back to cohort
Record W3024825014 · doi:10.1149/ma2020-01462665mtgabs

Regeneration of Reactive Pd Surfaces in Au-Pd Nanoparticles after Electrochemical Aging

2020· article· en· W3024825014 on OpenAlexaff
Sagar Prabhudev, Sebastian Kohsakowski, Cybelle Palma de Olivera Soares, Sven Reichenberger, Stephan Barcikowski, Ana C. Tavares, Daniel Guay

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDissolutionNanoparticleMaterials scienceElectrochemistryAlloyPalladiumLaser ablationChemical engineeringNanotechnologyElectrodeMetallurgyChemistryCatalysisLaserPhysical chemistry

Abstract

fetched live from OpenAlex

One major hurdle in the development of efficient electrocatalysts is deterioration of activity, which can be caused by selective dissolution of metals [1]. The recent development of gold-palladium (Au-Pd) alloy nanoparticles outlines a contemporary strategy to impart increased stability in nanoparticles by combining a more electrochemically stable metal such as Au with lesser stable Pd [2, 3]. Unfortunately, the relative surface-reactivity of Au is poor, and as a result, there is an inevitable design constraint to form Pd-rich outer shell structure - a task that is particularly daunting considering the high dissolution tendency of Pd [4]. Here we present an electrochemical aging method that allows for increasing the Pd concentration at the surface of Au-Pd NPs by means of diffusion of Pd atoms from the particle-core to the shell. The method involves an electrochemical aging treatment in alkaline KOH media for which the choice of suitable upper vertex potential proved to be particularly very important. Au-Pd NPs synthesized by means of liquid-phase laser-ablation method [5] were used in this study, typically ranging in diameter between 14.5 nm to 22.6 nm and composition between Au/Pd: 20/80 to 80/20 ratios. The particle diameter remained homogeneous across the whole composition range, thanks to the size-selectivity of laser-ablation synthesis of alloy molar fraction series, in line with the literature [5]. This allows for excluding any size-effects on the electrochemical behaviour of alloy nanoparticles. The nominal Au/Pd compositions initially fed to the laser appeared to be well preserved down to single-nanoparticle level as confirmed by detailed analyses of the SEM/EDX and XPS spectroscopic data. Formation of Au/Pd solid-solution was also apparent from the estimation of the lattice-parameters using X-ray diffraction (XRD) that varied linearly in accordance with the change in Pd alloy content. The cyclic voltammograms recorded in 0.1M N2-saturated KOH revealed features characteristic of both Au and Pd surfaces, e.g., the reduction peaks at 0.98 V and 0.55 V vs RHE (respectively), which was reflective of a mixed Au and Pd surface-structure exposed to the electrochemical treatments. Importantly, both the peak-positions and the integrated surface-charge shifted in correspondence with the variable Pd content in the alloys, thus serving as the initial markers of the surface-state before further electrochemical treatments. Marked differences could be noted between the electrochemical behaviours in acid and the alkaline media, as well as the potential range and the number of cycles involved ( Figure 1 ). The initial H-desorption/adsorption peaks (A, B) and the PdO reduction peaks apparent at the onset of aging in 0.5M H2SO4 gradually disappeared with subsequent cycling (C1), along with the concomitant rise in the Au oxide reduction peaks (D1), indicative of gradually dissolution of Pd. Importantly, the lost Pd surface surprisingly regenerated (C2) with subsequent aging in 0.1M KOH media, particularly at sweeping potentials extending to very positive values. The regenerated Pd-rich surface is attributed to preferential diffusion of Pd from particle cores- to the surface aided by surface-reconstruction via a ‘place-exchange’ between adsorbed-oxygen and Pd. Detailed analyses of the XPS Pd-3d3/2 and Au-4f7/2 edges and the respective STEM-EDX elemental profiles are in good agreement with the changes of surface-structures proposed from the cyclic voltammetry measurements. All the alloys were simultaneously tested for oxygen reduction reaction (ORR). [1] Gasteiger, H. A., et al. (2005). Applied Catalysis B: Environmental, 56(1-2), 9-35. [2] Xu, J. B., et al. (2010). International Journal of Hydrogen Energy, 35(13), 6490-6500. [3] Sasaki, K., et al. (2010). Angewandte Chemie International Edition, 49(46), 8602-8607. [4] Rand, D. A. J., et al. (1972). Journal of Electroanalytical Chemistry and Interfacial Electrochemistry, 35(1), 209-218. [5] Reichenberger, S., et al. (2019). ChemCatChem, 11, 4489-4518. Figure 1

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.219
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

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207