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Record W2896398530 · doi:10.1109/essderc.2018.8486912

Temperature monitoring of short-gate length AlGaN/GaN HEMT via an integrated sensor

2018· preprint· en· W2896398530 on OpenAlexaff
Flavien Cozette, Marie Lesecq, Nicolas Defrance, Michel Rousseau, Jean-Claude de Jaeger, Adrien Cutivet, Hassan Maher

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsHigh-electron-mobility transistorMaterials scienceTransistorResistive touchscreenOptoelectronicsTemperature measurementGallium nitrideCutoff frequencyThermal resistanceWide-bandgap semiconductorPower (physics)ThermalElectrical engineeringVoltageEngineeringPhysicsNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

This paper describes a new method to measure AlGaN/GaN High Electron Mobility Transistors (HEMTs) operating temperature in devices dedicated to RF application. A resistive nickel temperature sensor is integrated into HEMT active area. The technological process development permits to integrate the sensor close to the transistor hot spot providing HEMT temperature under operation. A maximal temperature of 68°C is extracted for a dissipated power of 3.5 W/ mm corresponding to a thermal resistance of 10.6 Kmm/W. This new method shows the capability to monitor component self-heating in real time and to predict its failure. Furthermore, it is shown that the sensor has no influence on DC HEMT electrical behavior and its impact on current and power cutoff frequencies is negligible.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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