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Record W2586377448 · doi:10.1021/acsphotonics.7b00103

Momentum-Resolved Electron Energy Loss Spectroscopy for Mapping the Photonic Density of States

2017· article· en· W2586377448 on OpenAlexafffund
Prashant Shekhar, Marek Malac, Vaibhav Gaind, Neda Dalili, A. Meldrum

Bibliographic record

VenueACS Photonics · 2017
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology FuturesNational Science Foundation
KeywordsElectron energy loss spectroscopyPhysicsPlasmonElectronPolaritonWave vectorMomentum (technical analysis)PhotonicsSpectroscopyCondensed matter physicsPosition and momentum spaceOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Strong nanoscale light–matter interaction is often accompanied by ultraconfined photonic modes and large momentum polaritons existing far beyond the light cone. A direct probe of such phenomena is difficult due to the momentum mismatch of these modes with free space light, however, fast electron probes can reveal the fundamental quantum and spatially dispersive behavior of these excitations. Here, we use momentum-resolved electron energy loss spectroscopy ( q -EELS) in a transmission electron microscope to explore the optical response of plasmonic thin films including momentum transfer up to wavevectors ( q ) significantly exceeding the light line wave vector. We show close agreement between experimental q -EELS maps, theoretical simulations of fast electrons passing through thin films and the momentum-resolved photonic density of states ( q -PDOS) dispersion. Although a direct link between q -EELS and the q -PDOS exists for an infinite medium, here we show fundamental differences between q -EELS measurements and the q -PDOS that must be taken into consideration for realistic finite structures with no translational invariance along the direction of electron motion. Our work paves the way for using q -EELS as the preeminent tool for mapping the q -PDOS of exotic phenomena with large momenta (high- q ) such as hyperbolic polaritons and spatially dispersive plasmons.

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 score0.199
Threshold uncertainty score0.680

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 science0.0010.000
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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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

Citations33
Published2017
Admission routes2
Has abstractyes

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