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Record W2265856181 · doi:10.1021/acs.nanolett.5b04215

Monolithically Integrated Metal/Semiconductor Tunnel Junction Nanowire Light-Emitting Diodes

2016· article· en· W2265856181 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNano Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOptoelectronicsMaterials scienceLight-emitting diodeNanowireHeterojunctionTunnel junctionDiodeSemiconductorNitrideElectrical junctionQuantum tunnellingNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

We have demonstrated for the first time an n(++)-GaN/Al/p(++)-GaN backward diode, wherein an epitaxial Al layer serves as the tunnel junction. The resulting p-contact free InGaN/GaN nanowire light-emitting diodes (LEDs) exhibited a low turn-on voltage (∼2.9 V), reduced resistance, and enhanced power, compared to nanowire LEDs without the use of Al tunnel junction or with the incorporation of an n(++)-GaN/p(++)-GaN tunnel junction. This unique Al tunnel junction overcomes some of the critical issues related to conventional GaN-based tunnel junction designs, including stress relaxation, wide depletion region, and light absorption, and holds tremendous promise for realizing low-resistivity, high-brightness III-nitride nanowire LEDs in the visible and deep ultraviolet spectral range. Moreover, the demonstration of monolithic integration of metal and semiconductor nanowire heterojunctions provides a seamless platform for realizing a broad range of multifunctional nanoscale electronic and photonic devices.

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 categoriesInsufficient payload (model declined to judge)
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 score0.041
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
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.223
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