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Record W2075196297 · doi:10.1109/16.906457

Performance predictions for n-p-n Al/sub x/Ga/sub 1-x/N/GaN HBTs

2001· article· en· W2075196297 on OpenAlexaff
D.L. Pulfrey, Sasan Fathpour

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCutoff frequencyCutoffMaterials scienceDopantOptoelectronicsBase (topology)Realization (probability)DopingLimit (mathematics)Carrier lifetimePhysicsComputational physicsMathematicsSiliconMathematical analysisStatistics

Abstract

fetched live from OpenAlex

Predictions of the attainable current gain and cut-off frequency of n-p-n Al/sub x/Ga/sub 1-x/N/GaN HBTs are made using compact models. This analytical approach allows the minority-carrier lifetime in the base to be readily identified as a critical parameter in the determination of the gain. For realistic values of lifetime, room-temperature gains in the region of 200-2000 should be attainable, with a graded-base being necessary for highest performance. Gains around 100 are predicted for operation at 600 K. Design of the base is shown to be also important in attaining high cutoff frequencies: a value around 30 GHz would appear to be the upper limit, and its realization would need a graded-base device. Spontaneous polarization is shown to be unlikely to have a major impact on device performance. On the other hand, incomplete ionization of the base dopant is shown to be an important factor.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations16
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Electron DevicesSame topicGaN-based semiconductor devices and materialsFrench-language works237,207