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Record W3200471867 · doi:10.1063/5.0058911

Interaction of charged particles with a graphene monolayer modeled as a set of electronic oscillators

2021· article· en· W3200471867 on OpenAlexafffund
Silvina Seguí, J.L. Gervasoni, Z. L. Mišković, N. R. Arista

Bibliographic record

VenueJournal of Applied Physics · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsUniversity of Waterloo
FundersInstituto Balseiro, Universidad Nacional de CuyoNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsGrapheneTerahertz radiationTrajectoryPhysicsPlasmonElectronCharged particleDielectricResonance (particle physics)Condensed matter physicsComputational physicsAtomic physicsOpticsQuantum mechanicsIon

Abstract

fetched live from OpenAlex

We assess the applicability of the oscillator model to evaluate the energy loss of a fast charged particle incident on graphene. We study the cases of a parallel and perpendicular trajectory of the particle. We focus on two frequency regimes for graphene’s electron response: the optical regime, which is dominated by two types of oscillators with non-dispersing frequencies in the ultraviolet regime, and the terahertz (THz) regime, which is dominated by a strongly dispersing sheet plasmon mode in doped graphene. In the latter regime, we invoke the kinematic resonance condition for a parallel trajectory, and we propose a method for averaging the energy loss for a perpendicular trajectory. We show that the oscillator model provides analytical expressions, which give results in generally good agreement with a dielectric-response approach to the same problem, even in the THz regime.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2021
Admission routes2
Has abstractyes

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