MétaCan
Menu
Back to cohort
Record W1983815769 · doi:10.1021/nl4030819

p-Type InN Nanowires

2013· article· en· W1983815769 on OpenAlexaff
Songrui Zhao, Binh Huy Le, D. P. Liu, X. D. Liu, Md Golam Kibria, Thomas Szkopek, Hong Guo, Zetian Mi

Bibliographic record

VenueNano Letters · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsNanowireDopingMaterials scienceDopantPhotoluminescenceAcceptorOptoelectronicsField-effect transistorCondensed matter physicsNanotechnologyTransistorPhysics

Abstract

fetched live from OpenAlex

In this Letter, we demonstrate that with the merit of nanowire structure and a self-catalytic growth process p-type InN can be realized for the first time by "direct" magnesium (Mg) doping. The presence of Mg acceptor energy levels in InN is confirmed by photoluminescence experiments, and a direct evidence of p-type conduction is demonstrated unambiguously by studying the transfer characteristics of InN nanowire field effect transistors. Moreover, the near-surface Fermi-level of InN can be tuned from nearly intrinsic to p-type degenerate by controlling Mg dopant incorporation, which is in contrast to the commonly observed electron accumulation on the grown surfaces of Mg-doped InN films. First-principle calculation using the VASP electronic package further shows that the p-type surface formed on Mg-doped InN nanowires is highly stable energetically.

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 score0.002

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)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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

Citations107
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueNano LettersSame topicGaN-based semiconductor devices and materialsFrench-language works237,207