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Record W4294204008 · doi:10.1016/j.cja.2022.08.004

Selective thermal emission and infrared camouflage based on layered media

2022· article· en· W4294204008 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChinese Journal of Aeronautics · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of ChinaAgence Nationale de la RechercheAlexander von Humboldt-Stiftung
KeywordsCamouflageInfraredMaterials scienceFabricationOptoelectronicsThermalCoatingOpticsSurvivabilitySubstrate (aquarium)NanotechnologyComputer science

Abstract

fetched live from OpenAlex

Infrared camouflage based on artificial thermal metasurfaces has recently attracted significant attention. By eliminating thermal radiation differences between the object and the background, it is possible to hide a given object from infrared detection. Infrared camouflage is an important element that increases the survivability of aircraft and missiles, by reducing target susceptibility to infrared guided threats. Herein, a simple and practicable design is theoretically presented based on a multilayer film for infrared stealth, with distinctive advantages of scalability, flexible fabrication, and structural simplicity. The multilayer medium consists of silicon substrate, carbon layer and zinc sulfide film, the optical properties of which are determined by transfer matrix method. By locally changing the thickness of the coating film, the spatial tunability and continuity in thermal emission are demonstrated. A continuous change of emissive power is further obtained and consequently implemented to achieve thermal camouflage functionality. In addition, other functionalities, like thermal illusion and thermal coding, are demonstrated by thickness-engineered multilayer films.

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.

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 score0.138
Threshold uncertainty score0.938

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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