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Record W2020811264 · doi:10.1103/physreva.73.013815

Surface-plasmon-based electron acceleration

2006· article· en· W2020811264 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Review A · 2006
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPhysicsElectronAtomic physicsSurface plasmonPlasmonKinetic energyElectromagnetic fieldElectric fieldMaxwell's equationsFemtosecondAccelerationSurface plasmon polaritonComputational physicsClassical mechanicsQuantum mechanicsLaser

Abstract

fetched live from OpenAlex

In this paper, we describe a surface-plasmon-based electron acceleration model, the results of which were supported by our recent experimental observations [S. E. Irvine et al., Phys. Rev. Lett. 93, 184801 (2004)]. The model incorporates femtosecond electromagnetic field dynamics and nonlinear electron photoemission characteristics of metallic surfaces. To account for the electromagnetic field structure in space and time, we numerically solve Maxwell's equations in two dimensions. Photoelectron emission is treated quasiclassically in accordance with empirical multiphoton statistics, whereas electron dynamics and energy gain are governed by the Lorentz force. Various aspects of the acceleration mechanism are discussed including surface plasmon coupling and evanescent decay, kinetic energy spectra, angular distributions, angle-resolved energy spectra, and the dependence of maximum energy on the surface electric field.

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.

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 score0.020
Threshold uncertainty score0.518

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 head0.010
GPT teacher head0.260
Teacher spread0.251 · 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