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The impact of fabrication conditions on the quality of Au nanoparticle arrays on dimpled Ta templates

2012· article· en· W1995345316 on OpenAlexafffund
Hany A. El‐Sayed, Hebert Molero, Viola Birss

Bibliographic record

VenueNanotechnology · 2012
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsMaterials scienceFabricationDewettingDimpleNanotechnologyNanoparticleAnodizingDeposition (geology)Scanning electron microscopeTemplateThin filmOptoelectronicsComposite material

Abstract

fetched live from OpenAlex

Highly ordered dimpled Ta (DT) nanotemplates, prepared by electrochemical anodization of Ta, were recently reported to be ideally suited for the fabrication of a Au nanoparticle (NP) array using a Au thin film dewetting method. Here, we provide guidance and understanding of the effect of the DT fabrication and Au film deposition steps on the characteristics of the resulting NP array. Specifically, the optimum anodization time, voltage and solution composition are established, and the thickness of the sputter-deposited metal film is shown to be a very important parameter in achieving the desired single Au NP per dimple. The resulting high quality Au NP arrays are demonstrated to be electrochemically addressable, with the total Au surface area, measured electrochemically for large-scale samples, agreeing with the calculated area, based on scanning electron microscope determination of average particle shape and distribution. As the NP formation process proceeds via confined thin film dewetting, the protocol developed here should be applicable to the formation of NP arrays of a range of other metals and alloys.

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 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 score0.218
Threshold uncertainty score0.241

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 head0.031
GPT teacher head0.327
Teacher spread0.295 · 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.

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

Citations18
Published2012
Admission routes2
Has abstractyes

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