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Record W4392049757 · doi:10.1364/ao.506094

Multifunctional metamaterial device based on VO<sub>2</sub> and the equivalent diode

2024· article· en· W4392049757 on OpenAlexaff
Zelong Wang, Xin Ke Wang, Junlin Wang, Shengjie Sun, Huizhong Pang, Kaixuan Shi, Xingyu Pei

Bibliographic record

VenueApplied Optics · 2024
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsInstitute of Particle Physics
FundersNatural Science Foundation of Inner MongoliaNational Natural Science Foundation of China
KeywordsOpticsMetamaterialDiodeMaterials scienceOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

This paper proposes a switchable multifunctional metamaterial device operating in the terahertz (THz) band. The device is loaded with an equivalent diode and utilizes vanadium dioxide (VO 2 ). The middle layer of the whole device, a metal layer, divides the device into the I side and the II side. When the diode is ON, the I side can achieve dual-band absorption at 1.975 and 4.345 THz. When the diode is OFF, the I side can achieve single-band absorption at 4.28 THz. In the case of VO 2 being insulating, the II side can achieve linear-to-linear (LTL) polarization conversion at 2.342–4.18 THz. In the case of VO 2 being conductive, the II side can realize linear-to-circular (LTC) polarization conversion at 2.105–3.283 THz. The device provides a new strategy for the subsequent combination of multiple functions. The device can be used in electromagnetic stealth, intelligent applications, radiometers, and sensors and has relatively large application potential in miniaturized multifunctional metamaterials and THz band research.

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 head0.015
GPT teacher head0.233
Teacher spread0.217 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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