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Record W2341610062 · doi:10.1149/ma2016-01/34/1648

Gold-Platinum Nanostructures Formed By Thermal Dewetting

2016· article· en· W2341610062 on OpenAlexaffabout
Annie Hoang, Corie Horwood, Viola Birss

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDewettingMaterials scienceBimetallic stripNanotechnologyFabricationNanoparticleOxideNanostructureLithographySputteringSurface energyThin filmCrystallinityMetalChemical engineeringOptoelectronicsComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Introduction Bimetallic core-shell nanoparticles, including Au-Pt nanoparticles (NPs), exhibit interesting electrocatalytic properties for fuel cell reactions. 1 For this application, the ability to control the size of the NPs, as well as their composition and surface crystallinity, has been shown to be important to enhance the utilization efficiency of the catalysts. 2 NP arrays have been previously achieved by fabrication methods such as “top-down” or “bottom-up” approaches, which typically involve lithography and self-assembly, respectively. Top-down methods are often costly and time consuming, while bottom-up methods suffer from poor long range (> µm) order. The present study has focused on the formation of bimetallic nanostructures on Ta templates, where the large surface energy difference between a metallic thin film (Au and Pt) and the air-formed oxide on the Ta surface cause the dewetting of a sputter-coated metallic film to form NPs. This approach has been previously used to form Au NPs of controllable size, with a linear relationship observed between the metal film thickness prior to dewetting and the NP diameter. 3 Here, we have attempted to form useful Au/Pt nanostructures and the electrochemistry of these materials, formed using a range of fabrication conditions, will be discussed in detail. Methods and Results Solid-state dewetting of thin metal films on oxide substrates is a known method of fabricating metal NP arrays over relatively large dimensions (e.g., cm 2 ) without requiring costly lithography processes. 4,5 Recent work in our group has demonstrated the ability to form ordered Au NP arrays on Ta templates, which are covered by a thin, air-formed Ta oxide film. This was achieved by the sputter-deposition of a thin film (3-4 nm) of Au, followed by thermal annealing at 450 o C for 30 minutes. 4 This method was then adapted to form Au-Pt nanostructures, where two metal films (3-4 nm each of Au and Pt) were sequentially sputtered (Au then Pt, or Pt then Au) on chemically polished Ta templates, and then thermally annealed at 450 o C or 600 o C for 90 minutes. These Au-Pt nanostructures were characterized by FESEM (field emission scanning electron microscopy) to determine the extent of dewetting. It was observed that higher annealing temperatures of 600 o C (well below the melting point of both Au and Pt) were needed to further dewet the thin metal films (Figure 1 (a) and (b)), as heating at 450 o C was only able to partially dewet these Au-Pt films (Figure 1 (c) and (d)). The electrochemical behaviour of these bimetallic nanostructures was investigated by cyclic voltammetry (CV) in 0.5 M H 2 SO 4 solution and then compared to the response from the individual Au vs. Pt thin films. The CVs show that the bimetallic thin films (before annealing) exhibit characteristics of both metals, indicating that the second sputter-coated metal does not form a conformal coating on the first sputter-coated film. After annealing at 450 o C, the CVs exhibit only Au characteristics, regardless of the deposition sequence. This suggests that, regardless of the order of sputter-coating, Au is coating the Pt structures after thermal annealing (i.e., these are Pt@Au nanostructures), in contrast to the Pt enrichment observed at the surface of Au@Pt core-shell NPs, formed by the electrochemical reduction of ionic precursors in solution. The characteristics of the nanostructures were shown to be optimized by varying the fabrication conditions (film thickness and annealing conditions), which also aided in understanding the mechanism of dewetting of these thin bimetallic films. Acknowledgements We gratefully acknowledge financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC). References Luo, J.; Maye, M.M.; Kariuki, N.N.; Wang, L.; Njoki, P.; Lin, Y.; Schadt, M.; Naslund, H.R.; Zhong, C.J. Catal. Today. 2005, 17 , 291-297. Ataee-Esfahani, H.; Wang, L.; Nemoto, Y.; Yamauchi, Y. Chem. Mater. 2010 , 22 , 6310-6318. Kojima, Y.; Kato, T. Nanotechnology . 2008 , 19 , 255605. El-Sayed, H. A.; Molero, H. M.; Birss, V. I. Nanotechnology. 2012 , 23 , 435602. Wang, D.; Schaff, P. J.Mater.Sci: Mater Electron. 2011, 22, 1067-1070. 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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.001

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 head0.011
GPT teacher head0.222
Teacher spread0.210 · 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; both teacher heads agree on what is shown here.

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".

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Citations0
Published2016
Admission routes2
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