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Record W1977470020 · doi:10.1109/iceaa.2013.6632343

FDTD-Compatible broadband surface impedance boundary conditions for graphene

2013· article· en· W1977470020 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrapheneFinite-difference time-domain methodBoundary value problemMaterials scienceElectrical impedanceSurface conductivityBroadbandConductivityComputer scienceOpticsNanotechnologyPhysicsMathematical analysisMathematicsTelecommunicationsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Graphene is a material that has been the focus of much academic interest for its unique material properties. As understanding of graphene improves and fabrication of graphene based devices matures, there is a growing need for electromagnetic simulations of graphene to aid device design. A finite-difference time domain (FDTD) model of graphene is useful for characterizing relevant geometries over a wide range of frequencies, yet limited by the excessive computational resources needed to model this essentially two-dimensional lossy, dispersive medium. A natural alternative is the use of a broadband surface impedance boundary condition (SIBC) that includes both the inter and the intraband conductivity of graphene. This SIBC is developed using a vector-fitting extracted rational function expansion of graphene's surface conductivity, mapped into the time-domain and implemented as a system of field update equations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.999

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)0.0020.000

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 head0.013
GPT teacher head0.274
Teacher spread0.261 · 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