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Record W3105459186

Nonlinear optics of graphene and other 2D materials in layered structures

2018· article· en· W3105459186 on OpenAlexfundno aff

Bibliographic record

VenueVUBIR (Vrije Universiteit Brussel) · 2018
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsnot available
FundersVrije Universiteit BrusselChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaFonds Wetenschappelijk OnderzoekNational Natural Science Foundation of China
KeywordsNonlinear systemNonlinear opticsGrapheneParametric statisticsSecond-harmonic generationHigh harmonic generationElectric fieldNonlinear opticalHarmonicSIGNAL (programming language)OpticsField (mathematics)PhysicsMaterials scienceStatistical physicsComputer scienceNanotechnologyMathematicsAcousticsQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

We present a theoretical framework for nonlinear optics of graphene and other 2D materials in layered structures. We derive a key equation to find the effective electric field and the sheet current density in the 2D material for given incident light beams. Our approach takes into account the effect of the surrounding environment and characterizes its contribution as a structure factor. We apply our approach to two experimental setups, and discuss the structure factors for several nonlinear optical processes including second harmonic generation, third harmonic generation, and parametric frequency conversion. Our systematic study gives a strict extraction method for the nonlinear coefficients, and provides new insights in how layered structures influence the nonlinear signal observed from 2D materials.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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 designTheoretical or conceptual
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

Citations23
Published2018
Admission routes1
Has abstractyes

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