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Record W1617416753 · doi:10.1109/led.2015.2472297

A Theoretical Investigation of Orientation-Dependent Transport in Monolayer MoS<sub>2</sub> Transistors at the Ballistic Limit

2015· article· en· W1617416753 on OpenAlexafffund
Fei Liu, Yijiao Wang, Xiaoyan Liu, Jian Wang, Hong Guo

Bibliographic record

VenueIEEE Electron Device Letters · 2015
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsZigzagMonolayerOrientation (vector space)Materials scienceTransistorCondensed matter physicsConduction bandBallistic conductionPhysicsCrystallographyNanotechnologyChemistryQuantum mechanicsGeometryMathematicsVoltage

Abstract

fetched live from OpenAlex

Device performance of monolayer MoS2transistors is investigated by atomistic simulations within the non-equilibrium Green's function formalism. A strong dependence of quantum transport on MoS2 orientation is predicted. To a large extent, the orientation dependence is due to subband transport properties and the atomistic structure along the transport direction. A bandgap is found in the conduction band along armchair direction (AD), which plays a major role for the orientation-dependent transport. At the same time, different atomic arrangements along AD and zigzag direction have different depletion region lengths, which also contribute to the orientation-dependent transport. Orientation dependence of drain current exists in MoS2FETs having different gate lengths.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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 designSimulation or modeling
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

Citations25
Published2015
Admission routes2
Has abstractyes

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