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Record W2099689722 · doi:10.1109/16.960389

InP/GaAsSb/InP double HBTs: a new alternative for InP-based DHBTs

2001· article· en· W2099689722 on OpenAlexaff
C. R. Bolognesi, Miroslav Dvořák, Pauline Yeo, Xinji Xu, S. P. Watkins

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCutoff frequencyMaterials scienceOptoelectronicsBipolar junction transistorHeterojunction bipolar transistorIndium phosphideMetalorganic vapour phase epitaxyGallium arsenideHeterojunctionOscillation (cell signaling)Indium gallium arsenideVoltageTransistorElectrical engineeringEpitaxyChemistryNanotechnology

Abstract

fetched live from OpenAlex

We report on the physical operation and performance of MOCVD-grown abrupt heterojunction InP/GaAs/sub 0.51/Sb/sub 0.49//InP double heterojunction bipolar transistors (DHBTs). In particular, the effect of the InP collector thickness on the breakdown voltage and on the current gain cutoff frequency is assessed and a f/sub T/ of 106 GHz is reported for a DHBT with a 400 /spl Aring/ base and a 2000 /spl Aring/ InP collector with a BV/sub CEO/ of 8 V. We show that InP/GaAsSb/InP DHBTs are characterized by a weak variation of f/sub T/ as a function of temperature. Finally, we also demonstrate that high maximum oscillation frequencies f/sub MAX/>f/sub T/ can be achieved in scaled high-speed InP/GaAsSb/InP DHBTs, and provide estimates of the maximum cutoff frequencies achievable for this emergent but promising material system. Recent results on improved structures validate our performance predictions with cutoff frequencies well beyond 200 GHz.

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 score0.004

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 head0.025
GPT teacher head0.296
Teacher spread0.270 · 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

Citations73
Published2001
Admission routes1
Has abstractyes

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