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Record W2529398822 · doi:10.1088/2053-1591/3/10/105004

Towards the reality of spin field effect transistor utilizing a graphene channel with spin-splitting

2016· article· en· W2529398822 on OpenAlex
Yihang Yang, Lin Li, Ying Liu, Guo‐Xing Miao

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials Research Express · 2016
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Waterloo
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsCondensed matter physicsGrapheneSpin (aerodynamics)PhysicsSpin Hall effectMagnetic fieldFerromagnetismElectronExchange interactionSpin transistorDirac fermionSpin polarizationMaterials scienceQuantum mechanics

Abstract

fetched live from OpenAlex

We propose a spin field effect transistor using a graphene nanoribbon as the channel. The control and manipulation of the electron spin in the channel modulate the spin-polarized current. The modulation is carried out by the magnetic exchange field which arises from the electron exchange interaction with ferromagnetic gate and quantum confinement effect. Numerical estimation indicates that a substantial magnetic exchange field can generate a phase difference on the order of π within a timeframe far below the spin lifetime and timescale between successive collisions, which ensures both the spin coherence and ballistic conduction during the electron transport. A graphene ribbon with armchair boundaries has the desired Dirac point and metallic character. This Dirac-like dispersion relation, together with negligible spin–orbit coupling, makes large on-off ratio feasible even in the presence of thermal dispersion.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 science0.0010.000
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 head0.082
GPT teacher head0.373
Teacher spread0.291 · 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