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Record W2963965558 · doi:10.1109/ted.2019.2926742

Self-Heating and Equivalent Channel Temperature in Short Gate Length GaN HEMTs

2019· article· en· W2963965558 on OpenAlexafffund
Xuesong Chen, Slim Boumaiza, Lan Wei

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceOptoelectronicsTransistorChannel (broadcasting)Wide-bandgap semiconductorTemperature measurementThermalField-effect transistorLogic gateGallium nitrideElectronic engineeringElectrical engineeringVoltageEngineeringNanotechnologyLayer (electronics)PhysicsThermodynamics

Abstract

fetched live from OpenAlex

In this paper, we study the self-heating mechanism and its impact on electrical performance of short gate length GaN high electron mobility transistors (HEMTs) based on electrothermal TCAD simulations. We propose an equivalent channel temperature to quantify the current degradation due to self-heating and also resolve the discrepancies between temperature measurements through electrical methods and thermal methods in the literature. We then explain the equivalent channel temperature's behavior using the temperature- and field-dependent electron transport theory for short gate length HEMTs. The implications and guidelines to the various aspects of device design are also discussed.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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

Citations66
Published2019
Admission routes2
Has abstractyes

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