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Record W2319527475 · doi:10.1149/1.2357227

The Effect of Surface Cleaning on Current Collapse in AlGaN/GaN HEMTs

2006· article· en· W2319527475 on OpenAlexaff
J. A. Bardwell, R. McKinnon, C. Storey, Haipeng Tang, G. I. Sproule, Daniel Roth, Rongzhu Wang

Bibliographic record

VenueECS Transactions · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsNational Research Council CanadaInstitute for Microstructural Sciences
Fundersnot available
KeywordsPassivationMaterials scienceSilicon nitrideAuger electron spectroscopyOptoelectronicsWaferNitrideSiliconGallium nitrideWide-bandgap semiconductorLayer (electronics)Composite material

Abstract

fetched live from OpenAlex

The phenomenon of current collapse is a limiting factor in the performance of AlGaN/GaN high electron mobility transistors (HEMTs), and can be ameliorated by the deposition of a silicon nitride passivation film on the surface. The effect of three types of surface cleaning prior to the application of a silicon nitride passivation layer are studied. The best results were obtained when the wafers were cleaned using an air plasma descum followed by an HCl dip prior to the deposition of the silicon nitride passivation. Auger electron spectroscopy depth profiling indicated that the degree of collapse was correlated with the amount of residual carbon contamination at the silicon nitride/AlGaN interface.

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 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 score0.227
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

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