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Graphene in inhomogeneous magnetic fields: bound, quasi-bound and scattering states

2011· article· en· W2063589852 on OpenAlexaff
M. Ramezani Masir, P. Vasilopoulos, F. M. Peeters

Bibliographic record

VenueJournal of Physics Condensed Matter · 2011
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsConcordia University
Fundersnot available
KeywordsCondensed matter physicsMagnetic fieldPhysicsLandau quantizationScatteringBound stateElectronFermi energyGrapheneAngular momentumQuantum dotQuantum mechanics

Abstract

fetched live from OpenAlex

The electron states in graphene-based magnetic dot and magnetic ring structures and combinations of both are investigated. The corresponding spectra are studied as a function of the radii, the strengths of the inhomogeneous magnetic field and of a uniform background field, the strength of an electrostatic barrier and the angular momentum quantum number. In the absence of an external magnetic field we have only long-lived quasi-bound and scattering states and we assess their influence on the density of states. In addition, we consider elastic electron scattering by a magnetic dot, whose average B vanishes, and show that the Hall and longitudinal resistivities, as a function of the Fermi energy, exhibit a pronounced oscillatory structure due to the presence of quasi-bound states. Depending on the dot parameters this oscillatory structure differs substantially for energies below and above the first Landau level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2011
Admission routes1
Has abstractyes

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