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Record W2967188913 · doi:10.1088/1361-648x/ab3c3c

Photoinduced polarization enhancement on biased bilayer graphene in the Landau level regime

2019· article· en· W2967188913 on OpenAlexaff
Alexander López, Bertrand Berche, John Schliemann, Francisco Mireles, Benjamín Santos

Bibliographic record

VenueJournal of Physics Condensed Matter · 2019
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoCorporación Ecuatoriana para el Desarrollo de la Investigación y la AcademiaCentre National de la Recherche ScientifiqueUniversité de Lorraine
KeywordsLandau quantizationPolarization (electrochemistry)Condensed matter physicsBilayer grapheneMonochromatic colorPhysicsGrapheneQuantization (signal processing)BilayerMaterials scienceOpticsQuantum mechanicsChemistryMembraneMagnetic field

Abstract

fetched live from OpenAlex

We investigate the charge carrier dynamics in bilayer graphene subject to monochromatic laser irradiation within the Landau level quantization regime. Even though the radiation field does not lift the energy degeneracy of the lowest Landau levels (LLs), it nevertheless has a strong effect on the photoinduced pseudospin polarization response for higher LLs ([Formula: see text]). Our results show that the photoinduced bandgaps lead to a finite response of the averaged pseudospin polarization with nontrivial oscillating behavior. It is shown that the contribution from these higher LL transitions turns out to be crucial to achieve an enhanced photoinduced polarization in radiated bilayer graphene. The experimental feasibility of our findings is also discussed.

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)0.001
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 score0.025
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.040
GPT teacher head0.287
Teacher spread0.247 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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