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Record W1982093035 · doi:10.1063/1.3533941

Influence of transferred-electron effect on drain-current characteristics of AlGaN/GaN heterostructure field-effect transistors

2011· article· en· W1982093035 on OpenAlexaff
Maziar Moradi, Pouya Valizadeh

Bibliographic record

VenueJournal of Applied Physics · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsConcordia University
Fundersnot available
KeywordsVelocity overshootOhmic contactSaturation velocityHeterojunctionVelocity saturationDrift velocityMaterials scienceOptoelectronicsTransistorElectronSemiconductorWide-bandgap semiconductorCondensed matter physicsField-effect transistorCurrent (fluid)Overshoot (microwave communication)Band gapMOSFETVoltagePhysicsElectrical engineeringNanotechnology

Abstract

fetched live from OpenAlex

An analytical model, with incorporation of transferred-electron effect, for drain-current characteristics of AlGaN/GaN heterostructure field-effect transistors (HFETs) is presented. The transferred-electron effect is often neglected in modeling the drain-current of III-V HFETs. The broad steady-state electron drift-velocity overshoot of GaN in comparison to other direct semiconductors such as GaAs and InP, in addition to the larger difference between the peak and saturation drift-velocity, and the wider band gap of this semiconductor suggest the importance of the incorporation of transferred-electron effect (i.e., steady-state drift-velocity overshoot) in modeling the drain-current of these devices. Simulation results are compared with the results of the adoption of a saturating drift transport model, which has been recently used in modeling the drain-current of these devices. Comparisons between the two models demonstrate the importance of the consideration of transferred-electron effect, especially as the Ohmic contact quality is improved.

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 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 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 score0.017
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.232
Teacher spread0.223 · 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 teacher head, 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

Citations11
Published2011
Admission routes1
Has abstractyes

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