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Record W3114953156 · doi:10.18280/acsm.440603

Empirical Study of Solar Absorber Metamaterial Characterization in GHz and THz Regime

2020· article· en· W3114953156 on OpenAlexvenueno aff
Anil Antony Sequeira, Abdul Raheem Ahmed, R A George, Krishnamurthy H. Sachidananda

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMetamaterialTerahertz radiationMaterials scienceMetamaterial absorberOptoelectronicsDetectorBandwidth (computing)OpticsCharacterization (materials science)WavelengthPhysicsComputer scienceTunable metamaterialsNanotechnologyTelecommunications

Abstract

fetched live from OpenAlex

Advanced material such as composite material, metamaterial, nanomaterials and smart materials plays a significant role in degree of performance of any system as compared to conventional material and hence, they are commonly used in diverse applications such as aerospace, medical devices, sensor detection, smart solar application etc. Metamaterial is one of such artificial sub-wavelength materials to exhibit electromagnetic and optical properties that surpass or complement those accessible in nature. In this research paper, three structure of metamaterials are simulated for the solar application as an absorber to increase solar efficiency as well as to increase negative refractive index to represent wave propagation in different directions. From this study it can be concluded that all the three materials have reached maximum point of absorption in a narrow bandwidth and it is possible to obtain transverse magnetic wave if the materials are stacked. These materials can be used as frequency detector for THz applications.

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)0.002
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 score0.323
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.082
GPT teacher head0.321
Teacher spread0.240 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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