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Record W2003616314 · doi:10.1039/b903539g

Optical and structural characterization of blue-emitting Mg2+- and Zn2+-doped GaN nanoparticles

2009· article· en· W2003616314 on OpenAlexafffund
Venkataramanan Mahalingam, Enrico Bovero, Prabhakaran Munusamy, Frank C. J. M. van Veggel, Rui Wang, A. J. Steckl

Bibliographic record

VenueJournal of Materials Chemistry · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of VictoriaArmy Research OfficeUniversity of Cincinnati
KeywordsPhotoluminescenceRaman spectroscopyMaterials scienceZincDopingAnalytical Chemistry (journal)DopantSpectroscopyZinc nitrateDiffractionNanoparticleGalliumGallium nitrideNanotechnologyChemistryOptoelectronicsOptics

Abstract

fetched live from OpenAlex

We show blue photoluminescence (∼425 nm) from both Mg2+- and Zn2+-doped GaN nanoparticles. The effect of the doping concentration of these ions on the structural and optical properties was systematically studied using X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), photoluminescence (PL) and Raman spectroscopy. Starting from nitrate salts of gallium, zinc and magnesium we observed the formation of Mg2+- and Zn2+-doped Ga2O3 accompanied by Ga2O3. During the thermal cycle for the formation of GaN some of the zinc evaporates because of its relatively low boiling point. The PL intensity is proportional to the final concentration of the dopant ion in the final product and a weaker band is observable at a higher energy corresponding to the undoped GaN. Raman spectroscopic analysis confirms the distortion of the GaN lattice due to the incorporation of Mg2+ and Zn2+.

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 score0.010
Threshold uncertainty score0.392

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Citations9
Published2009
Admission routes2
Has abstractyes

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