MétaCan
Menu
Back to cohort
Record W3004655901 · doi:10.1088/1361-6641/ab73ea

Increasing threshold voltage and reducing leakage of AlGaN/GaN HEMTs using dual-layer SiN <i> <sub>x</sub> </i> stressors

2020· article· en· W3004655901 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSemiconductor Science and Technology · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of British Columbia
FundersGuangdong Science and Technology Department
KeywordsMaterials scienceOptoelectronicsThreshold voltageLayer (electronics)Stress (linguistics)VoltageWide-bandgap semiconductorStressorHigh-electron-mobility transistorElectric fieldTransistorElectrical engineeringNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Abstract In this work, AlGaN/GaN HEMTs with dual-layer SiN x stressors (composed of a low-stress layer and a high-stress layer) were investigated. The low-stress padding layer solved the surface damage problem which was caused during the deposition of the high-stress SiN x and provided a good passivated interface. The HEMTs with the dual-layer stressors showed a 1 V increase in the threshold voltage ( V th ) with comparable DC and RF amplification performance to the baseline devices. Moreover, the off-current ( I off ) was shown to be reduced by one to three orders of magnitude in the strained devices. The reduction in the off-currents was a result of the lower electric field in AlGaN, which suppressed the gate injection current. These improvements using the dual-layer stressor scheme supports strain engineering as an effective approach in the pursuit of the normally-off operation of AlGaN/GaN HEMTs.

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.

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)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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