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Record W2167582967 · doi:10.1021/nl801256p

Field Dependent Transport Properties in InAs Nanowire Field Effect Transistors

2008· article· en· W2167582967 on OpenAlexaff
Shadi A. Dayeh, Darija Susac, K. L. Kavanagh, Edward T. Yu, Deli Wang

Bibliographic record

VenueNano Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsSimon Fraser University
FundersOffice of Naval Research
KeywordsNanowireTransconductanceMaterials scienceField-effect transistorCondensed matter physicsField dependenceScatteringElectron mobilityConductanceTransistorOptoelectronicsTransmission electron microscopyIndium arsenidePhonon scatteringPhononGallium arsenideNanotechnologyOpticsMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

We present detailed studies of the field dependent transport properties of InAs nanowire field-effect transistors. Transconductance dependence on both vertical and lateral fields is discussed. Velocity-field plots are constructed from a large set of output and transfer curves that show negative differential conductance behavior and marked mobility degradation at high injection fields. Two dimensional electrothermal simulations at current densities similar to those measured in the InAs NWFET devices indicate that a significant temperature rise occurs in the channel due to enhanced phonon scattering that leads to the observed mobility degradation. Scanning transmission electron microscopy measurements on devices operated at high current densities reveal arsenic vaporization and crystal deformation in the subject nanowires.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.000
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 head0.012
GPT teacher head0.192
Teacher spread0.179 · 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 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

Citations32
Published2008
Admission routes1
Has abstractyes

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