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Record W2054040552 · doi:10.1021/nn501864h

Large-Area, Freestanding, Single-Layer Graphene–Gold: A Hybrid Plasmonic Nanostructure

2014· article· en· W2054040552 on OpenAlexafffund
Ganjigunte R. S. Iyer, Jian Wang, Garth Wells, Srinivasan Guruvenket, Scott Payne, Michael P. Bradley, Ferenc Borondics

Bibliographic record

VenueACS Nano · 2014
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of SaskatchewanCanadian Light Source (Canada)
FundersCanadian Institutes of Health ResearchNorth Dakota State University
KeywordsGrapheneMaterials sciencePlasmonNanotechnologyRaman spectroscopyNanostructureFabricationGraphene nanoribbonsSubstrate (aquarium)Nanoscopic scaleGraphene foamOptoelectronicsOptics

Abstract

fetched live from OpenAlex

Graphene-based plasmonic devices have recently drawn great attention. However, practical limitations in fabrication and device architectures prevent studies from being carried out on the intrinsic properties of graphene and their change by plasmonic structures. The influence of a quasi-infinite object (i.e., the substrate) on graphene, being a single sheet of carbon atoms, and the plasmonic device is overwhelming. To address this and put the intrinsic properties of the graphene-plasmonic nanostructures in focus, we fabricate large-area, freestanding, single-layer graphene-gold (LFG-Au) sandwich structures and Au nanoparticle decorated graphene (formed via thermal treatment) hybrid plasmonic nanostructures. We observed two distinct plasmonic enhancement routes of graphene unique to each structure via surface-enhanced Raman spectroscopy. The localized electronic structure variation in the LFG due to graphene-Au interaction at the nanoscale is mapped using scanning transmission X-ray microscopy. The measurements show an optical density of ∼0.007, which is the smallest experimentally determined for single-layer graphene thus far. Our results on freestanding graphene-Au plasmonic structures provide great insight for the rational design and future fabrication of graphene plasmonic hybrid nanostructures.

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 score0.058
Threshold uncertainty score0.800

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)0.0010.000

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 head0.017
GPT teacher head0.222
Teacher spread0.206 · 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

Citations47
Published2014
Admission routes2
Has abstractyes

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