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Record W2015844957 · doi:10.1364/oe.21.012145

Plasmon assisted thermal modulation in nanoparticles

2013· article· en· W2015844957 on OpenAlexaff
Aude L. Lereu, R. H. Farahi, Laurène Tétard, Stéfan Enoch, Thomas Thundat, Ali Passian

Bibliographic record

VenueOptics Express · 2013
Typearticle
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials sciencePlasmonSurface plasmonNanoparticleNanotechnologyOptoelectronicsModulation (music)NanolithographyLocalized surface plasmonDielectricThermalSurface plasmon polaritonFabrication

Abstract

fetched live from OpenAlex

Single-particle interactions hold the promise of nanometer-scale devices in areas such as data communications and storage, nanolithography, waveguides, renewable energy and therapeutics. We propose that the collective electronic properties possessed by noble metal nanoparticles may be exploited for device actuation via the unapparent mechanism of plasmon-assisted heat generation and flux. The temperature dependence of the dielectric function and the thermal transport properties of the particles play the central role in the feasibility of the thermally-actuated system, however the behavior of these thermoplasmonic processes is unclear. We experimentally and computationally analyzed modulation via thermoplasmonic processes on a test system of gold (Au) nano-islands. Modulation and energy transport in discontinuous domains exhibited quantitatively different characteristics compared to thin films. The results have implications for all surface plasmon based nano-devices where inevitable small-scale thermal processes are present.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.204
Teacher spread0.192 · 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 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
Published2013
Admission routes1
Has abstractyes

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