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Record W4376134915 · doi:10.1364/ao.489529

THz Bragg structures fabricated with additive manufacturing

2023· article· en· W4376134915 on OpenAlexafffund
C. Harrison Brodie, Isaac Spotts, Christopher M. Collier

Bibliographic record

VenueApplied Optics · 2023
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsTerahertz radiationMaterials scienceFabricationOpticsPhotonicsFiber Bragg gratingOptoelectronicsPhysicsWavelength

Abstract

fetched live from OpenAlex

The advancement of THz science and technology is desirable to facilitate the application of THz technologies in many sectors. Specialized THz photonic elements for these applications require desirable absorption and refractive characteristics in the THz regime. THz photonic elements can be created with additive manufacturing, and specifically 3D printing, forgoing the need for complex fabrication procedures and methodologies. Such THz photonic elements include periodic Bragg structures, which are capable of filtering specific THz frequencies. The authors present a THz Bragg structure fabricated with 3D printing via fused filament fabrication. The THz Bragg structure is made from high-impact polystyrene filament material, which is characterized in this paper with THz time-domain spectroscopy. The geometry and theoretical operation of the THz Bragg structure is investigated with finite-difference time-domain electromagnetic simulations. The THz Bragg structure is evaluated using a THz experimental test bed. There is agreement between the theoretical and the experimental filtering placement within the frequency domain for the THz Bragg structure. The capability of tunable frequency filtering of the presented THz Bragg structure, fabricated with 3D printing, is established and facilitates future advancements in applications of THz science and technology.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.454

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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