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Record W4313537319 · doi:10.1088/1402-4896/acb094

Spin-dependent transmission in curved graphene superlattice

2023· article· en· W4313537319 on OpenAlex
Jaouad El‐hassouny, Ahmed Jellal, El Houssine Atmani

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

VenuePhysica Scripta · 2023
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsCanadian Quantum Research Center
Fundersnot available
KeywordsGrapheneSuperlatticeCondensed matter physicsSpin (aerodynamics)Transmission (telecommunications)Quantum tunnellingReflection (computer programming)PhysicsMaterials scienceQuantum mechanicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Abstract We investigate spin-dependent transmission in a curved graphene superlattice of N cells where each one is made up of four regions. The first is concave, and the third is convex, two arcs of circles separated by a distance d from flat graphene sheets. The tunneling analysis allows us to determine all transmission and reflection channels associated with our system. As a result, we show that the number of cells acts by decreasing the transmissions with the same spin. We predict a solid spin-filtering effect when d and N are sufficiently large. Finally, it is determined that the degree and duration of suppression of the transmissions with the same spin over a range of energy are controllable using d .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.038
GPT teacher head0.314
Teacher spread0.275 · 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