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Record W2082892578 · doi:10.1116/1.582255

Growth of high-performance GaN modulation-doped field-effect transistors by ammonia-molecular-beam epitaxy

2000· article· en· W2082892578 on OpenAlexaff
H. Tang, J. B. Webb, J. A. Bardwell, T.W. MacElwee

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsNortel (Canada)Institute for Microstructural Sciences
Fundersnot available
KeywordsTransconductanceMaterials scienceMolecular beam epitaxyOptoelectronicsDopingSapphireElectron mobilityBarrier layerField-effect transistorHigh-electron-mobility transistorEpitaxyLayer (electronics)TransistorOpticsNanotechnologyLaserElectrical engineering

Abstract

fetched live from OpenAlex

The growth of AlGaN/GaN modulation-doped field-effect transistors (MODFETs) by ammonia-molecular-beam epitaxy on sapphire substrates is reported. C-doped GaN (2 μm thick) was used as the insulating buffer layer in the device structures. The MODFET structure was completed by the subsequent growth of 2000 Å of undoped GaN as the channel layer and 130 Å of AlxGa1−xN(0.1⩽x⩽0.3) as the donor barrier layer. Sheet carrier densities of up to 2×1013 cm−2 with mobility of ∼1000 cm2/V s have been achieved even without doping the AlxGa1−xN barrier, indicating a large piezoelectric effect and excellent interface quality. The MODFET layers grown exhibited a unique surface morphology showing very flat plateaus with rms roughness of 0.8 nm on the plateaus and rms roughness of 8 nm over a larger area. A 100-μm-wide device with a 1 μm gate length exhibited a maximum dc current drive of 0.9 A/mm, a peak transconductance of 160 mS/mm, a current gain cutoff frequency of 15.6 GHz, and a maximum oscillation frequency of 49.4 GHz. The high dc and rf performance is attributed to the high two-dimensional electron mobility, high sheet charge density, and insulating property of the C-doped GaN buffer.

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)0.001
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 score0.028
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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

Citations10
Published2000
Admission routes1
Has abstractyes

Explore more

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