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Record W4403534469 · doi:10.1021/acsnano.4c08441

Charge Transfer Plasmonics in Bespoke Graphene/α-RuCl<sub>3</sub> Cavities

2024· article· en· W4403534469 on OpenAlexaff
Rocco A. Vitalone, Bjarke S. Jessen, Ran Jing, Daniel J. Rizzo, Suheng Xu, Valerie Hsieh, Matthew Cothrine, David Mandrus, Lukas Wehmeier, G. L. Carr, Valentina Bisogni, Cory R. Dean, James Hone, Mengkun Liu, Michael I. Weinstein, M. M. Fogler, D. N. Basov

Bibliographic record

VenueACS Nano · 2024
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsToronto Metropolitan University
FundersBrookhaven National LaboratoryDivision of Mathematical SciencesOak Ridge National LaboratoryBasic Energy SciencesSimons Foundation
KeywordsGraphenePlasmonMaterials scienceOptoelectronicsScatteringHeterojunctionSurface plasmon polaritonGraphene nanoribbonsTerahertz radiationNanotechnologyOpticsSurface plasmonPhysics

Abstract

fetched live from OpenAlex

Surface plasmon polaritons (SPPs) provide a window into the nano-optical, electrodynamic response of their host material and its dielectric environment. Graphene/α-RuCl 3 serves as an ideal model system for imaging SPPs since the large work function difference between these two layers facilitates charge transfer that hole dopes graphene with n ∼ 10 13 cm –2 free carriers. In this work, we study the emergent THz response of graphene/α-RuCl 3 heterostructures using our home-built cryogenic scanning near-field optical microscope. Using phase-resolved imaging, we clearly observe long wavelength, heavily damped THz SPPs in a series of variable-size graphene cavities. From this, we extract the plasmonic wavelength and scattering rate in the graphene/α-RuCl 3 heterostructures. We determine that the measured plasmon wavelength and electronic scattering rate match our heterostructures’ theoretically predicted values. Our results demonstrate that shaping graphene into bespoke cavity structures enables observation and quantification of SPPs in heavily doped graphene that are largely not addressable with other experimental techniques. Moreover, the manifest lack of metallicity observed in the adjacent doped α-RuCl 3 layer provides significant constraints on the nature of the interfacial charge transfer in this 2D heterostructure.

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 score0.046
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.218
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.

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

Citations9
Published2024
Admission routes1
Has abstractyes

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