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Record W2604474003 · doi:10.1021/acs.nanolett.7b00180

Switchable Metal–Insulator Phase Transition Metamaterials

2017· article· en· W2604474003 on OpenAlexafffund
Ghazal Hajisalem, Mohammadreza Sanadgol Nezami, Reuven Gordon

Bibliographic record

VenueNano Letters · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMetamaterialMetal–insulator transitionMaterials sciencePhase transitionInsulator (electricity)NanotechnologyPhase (matter)OptoelectronicsMetalCondensed matter physicsChemistryPhysicsMetallurgy

Abstract

fetched live from OpenAlex

We investigate the switching of a gap plasmon tunnel junction between conducting and insulating states. Hysteresis is observed in the second and the third harmonic generation power dependence, which arises by thermally induced disorder ("melting") of a two-carbon self-assembled monolayer between an ultraflat gold surface and metal nanoparticles. The hysteresis is observed for a variety of nanoparticle sizes, but not for larger tunnel junctions where there is no appreciable tunneling. By combining quantum corrected finite-difference time-domain simulations with nonlinear scattering theory, we calculate the changes in the harmonic generation between the tunneling and the insulating states, and good agreement is found with the experiments. This paves the way to a new class of metal-insulator phase transition switchable metamaterials, which may provide next-generation information processing technologies.

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 score0.000
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)0.0000.000

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 head0.031
GPT teacher head0.303
Teacher spread0.272 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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