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Record W3155501808 · doi:10.1364/oe.422991

High-volume rapid prototyping technique for terahertz metallic metasurfaces

2021· article· en· W3155501808 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOptics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesNational Science Foundation
KeywordsTerahertz radiationRapid prototypingPolarizerStereolithographyMaterials scienceBeam splitterLithography3D printingOpticsTerahertz spectroscopy and technologyOptoelectronicsComputer scienceLaser

Abstract

fetched live from OpenAlex

Terahertz technology has greatly benefited from the recent development and generalization of prototyping technologies such as 3D printing and laser machining. These techniques can be used to rapidly fabricate optical devices for applications in sensing, imaging and communications. In this paper, we introduce hot stamping, a simple inexpensive and rapid technique to form 2D metallic patterns that are suitable for many terahertz devices. We fabricate several example devices to illustrate the versatility of the technique, including metasurfaces made of arrays of split-ring resonators with resonances up to 550 GHz. We also fabricate a wire-grid polarizer for use as a polarizing beam splitter. The simplicity and low cost of this technique can help in rapid prototyping and realization of future terahertz devices.

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)0.000
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: Methods · Consensus signal: Methods
Teacher disagreement score0.343
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

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 head0.026
GPT teacher head0.237
Teacher spread0.212 · 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