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Record W2051846029 · doi:10.1063/1.3211292

Negative capacitance in GaN∕AlGaN heterojunction dual-band detectors

2009· article· en· W2051846029 on OpenAlexaff
Laura E. Byrum, Gamini Ariyawansa, R. C. Jayasinghe, N. Dietz, A. G. U. Perera, S. G. Matsik, Ian T. Ferguson, A. Bezinger, H. C. Liu

Bibliographic record

VenueJournal of Applied Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsHeterojunctionImpurityShallow donorMaterials scienceCapacitanceVacancy defectOptoelectronicsRelaxation (psychology)Common emitterCondensed matter physicsAnalytical Chemistry (journal)Atomic physicsChemistryDopingPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

A study of trap states in n+-GaN∕AlGaN heterostructures using electrical, thermal, and optical analyses is reported. Capacitance-voltage-frequency measurements showed negative capacitance and dispersion, indicating interface trap states. Infrared spectra identified three impurity related absorption centers attributed to shallow Si-donor (pinned to the AlGaN barrier), N-vacancy/C-donor, and deep Si-donor (pinned to the GaN emitter) impurities with corresponding activation energies of 30.8±0.2, 125±1, and 140±2meV, respectively. The shallow Si-donor impurity had a relaxation time of 155±9μs, while the C-donor/N-vacancy and deep Si-donor impurities appear to behave as a single trap state with a relaxation time of 1.77±0.05μs. Multiple analysis techniques allowed the determination of the activation energies of these impurity related centers and the study of the effects of trap states on the electrical behavior of the detector.

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)0.0000.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

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