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Record W2133915919 · doi:10.1103/physrevb.85.201411

Emergence of plasmaronic structure in the near-field optical response of graphene

2012· article· en· W2133915919 on OpenAlexaff
J. P. Ćarbotte, J. P. F. LeBlanc, E. J. Nicol

Bibliographic record

VenuePhysical Review B · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of GuelphMcMaster UniversityCanadian Institute for Advanced Research
FundersNational Science Foundation
KeywordsPhysicsQuasiparticleGrapheneElectronCondensed matter physicsDirac fermionFermi energyMomentum (technical analysis)PlasmonAtomic physicsQuantum mechanicsSuperconductivity

Abstract

fetched live from OpenAlex

The finite momentum optical response $\ensuremath{\sigma}(\mathbit{q},\ensuremath{\omega})$ of graphene can be probed with the innovative technique of infrared nanoscopy where midinfrared radiation is confined by an atomic force microscope cantilever tip. In contrast to conventional $q\ensuremath{\sim}0$ optical absorption which primarily involves Dirac fermions with momentum near the Fermi momentum $k\ensuremath{\sim}{k}_{F}$, for finite $q$, $\ensuremath{\sigma}(\mathbit{q},\ensuremath{\omega})$ has the potential to provide information on many-body renormalizations and collective phenomena which have been found at small $k<{k}_{F}$ near the Dirac point in electron-doped graphene. For electron-electron interactions, the low-energy excitation spectrum characterizing the incoherent part of the quasiparticle spectral function of Dirac electrons with $k\ensuremath{\sim}{k}_{F}$ consists of a flat, small amplitude background which scales with chemical potential and Fermi momentum. However, probing of the states with $k$ near $k=0$ will reveal plasmarons, a collective state of a charge carrier and a plasmon. These collective modes in graphene have recently been seen in angle-resolved photoemission spectroscopy and here we describe how they manifest in near-field optics.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.045
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.023
GPT teacher head0.354
Teacher spread0.332 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

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