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Record W2101817388 · doi:10.1038/srep07083

Planar integrated metasurfaces for highly-collimated terahertz quantum cascade lasers

2014· article· en· W2101817388 on OpenAlexaff
Lianhe Li, E. Dupont, Saeed Fathololoumi, Z. R. Wasilewski, Dayan Ban, Hou Kun Liang, Ying Zhang, S. F. Yu, A. G. Davies, E. H. Linfield, Hui Chun Liu, Qi Jie Wang

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of WaterlooNational Research Council Canada
FundersEngineering and Physical Sciences Research CouncilMinistry of Education, IndiaMinistry of Education - SingaporeWolfson FoundationRoyal Society
KeywordsTerahertz radiationOptoelectronicsCollimated lightPlanarLaserOpticsCascadeMaterials scienceWaveguidePlasmonPhotonicsPhysicsComputer science

Abstract

fetched live from OpenAlex

We report planar integration of tapered terahertz (THz) frequency quantum cascade lasers (QCLs) with metasurface waveguides that are designed to be spoof surface plasmon (SSP) out-couplers by introducing periodically arranged SSP scatterers. The resulting surface-emitting THz beam profile is highly collimated with a divergence as narrow as ~4° × 10°, which indicates a good waveguiding property of the metasurface waveguide. In addition, the low background THz power implies a high coupling efficiency for the THz radiation from the laser cavity to the metasurface structure. Furthermore, since all the structures are in-plane, this scheme provides a promising platform where well-established surface plasmon/metasurface techniques can be employed to engineer the emitted beam of THz QCLs controllably and flexibly. More importantly, an integrated active THz photonic circuit for sensing and communication applications could be constructed by incorporating other optoelectronic devices such as Schottky diode THz mixers, and graphene modulators and photodetectors.

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)0.001
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 score0.361
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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

Citations20
Published2014
Admission routes1
Has abstractyes

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