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Record W2023802889 · doi:10.1063/1.4759368

p-type doping of GaAs nanowires using carbon

2012· article· en· W2023802889 on OpenAlexaff
O. Salehzadeh, X. Zhang, Byron D. Gates, K. L. Kavanagh, S. P. Watkins

Bibliographic record

VenueJournal of Applied Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials scienceNanowireDopingElectrical resistivity and conductivityField electron emissionOptoelectronicsField emission microscopyField-effect transistorEpitaxyAnalytical Chemistry (journal)NanotechnologyTransistorElectronChemistryOpticsLayer (electronics)

Abstract

fetched live from OpenAlex

We report on the electrical properties of Au-catalyzed C-doped GaAs nanowires (NWs) grown by metal organic vapor phase epitaxy. Transport measurements were carried out using a tungsten nanoprobe inside a scanning electron microscope by contacting to the Au catalyst particle of individual nanowires. The doping level could be varied from approximately (4 ± 1) × 1016 cm−3 to (1.0 ± 0.3) × 1019 cm−3 by varying the molar flow of the gas phase carbon precursor, as well as the group V to group III precursor ratio. It was found that the current transport mechanism switches from generation-recombination to tunnelling field emission by increasing the doping level to 1 × 1019 cm−3. Based on a diameter-dependent analysis of the apparent resistivity of the C-doped NWs, we propose that C incorporates into GaAs NWs through the triple boundary at the Au/NW interface. The p-type conductivity of the C-doped NWs was inferred by observing a rectification at negative bias (applied to the Au electrode) and confirmed by back-gating measurements performed on field effect transistor 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.

How this classification was reachedexpand

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 score0.018
Threshold uncertainty score0.286

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)0.0000.000

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 head0.028
GPT teacher head0.242
Teacher spread0.215 · 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 teacher head, 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

Citations16
Published2012
Admission routes1
Has abstractyes

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