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Record W2770698054 · doi:10.1088/1361-6641/aa9b57

Electrical characterization of Si/InN nanowire heterojunctions

2017· article· en· W2770698054 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

VenueSemiconductor Science and Technology · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill UniversitySimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaForschungszentrum JülichCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsNanowireHeterojunctionMaterials scienceDopingRectificationOptoelectronicsDopantScanning electron microscopeBand gapCondensed matter physicsVoltage

Abstract

fetched live from OpenAlex

Abstract We report on the electrical properties of undoped, Si-doped and Mg-doped InN nanowires measured directly on degenerate n-type and p-type Si substrates. The transport was measured with a nanoprobe technique inside a scanning electron microscope. The resulting average current density versus voltage characteristics are weakly rectifying for InN grown on n + –Si with similar ratios for all InN dopant types. On p + –Si, Mg-doped InN nanowires show a strong rectification behavior with opposite voltage polarity compared to n + –Si, while undoped and Si-doped nanowires show nearly symmetric transport. These characteristics are analyzed in terms of the properties of broken gap band offsets at the Si/InN heterojunction.

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 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 score0.033
Threshold uncertainty score0.425

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 studies0.0010.001
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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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