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Record W2049707734 · doi:10.1002/pssa.201100102

InN grown by migration enhanced afterglow (MEAglow)

2011· article· en· W2049707734 on OpenAlex
Kenneth Butcher, Dimiter Alexandrov, Penka Terziyska, Vasil Georgiev, Dimka Georgieva, Peter W. Binsted

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

Venuephysica status solidi (a) · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFull width at half maximumSapphireAfterglowMaterials scienceRoot mean squareDiffractionAnalytical Chemistry (journal)Atomic force microscopyThin filmSurface roughnessEpitaxyChemical vapor depositionSurface finishOptoelectronicsOpticsNanotechnologyChemistryComposite materialLayer (electronics)LaserPhysics

Abstract

fetched live from OpenAlex

Abstract InN thin films were grown by a new technique, migration enhanced afterglow (MEAglow), a chemical vapour deposition (CVD) form of migration enhanced epitaxy (MEE). Here we describe the apparatus used for this form of film deposition, which includes a scalable hollow cathode nitrogen plasma source. Initial film growth results for InN are also presented including atomic force microscopy (AFM) images that indicate step flow growth with samples having root mean square (RMS) surface roughness of as little as 0.103 nm in some circumstances for film growth on sapphire substrates. X‐ray diffraction (XRD) results are also provided for samples with a full width half maximum (FWHM) of the (0002) ω ‐2 θ peak of as little as 290 arcsec. Low pressure conditions that can result in damage to the InN during growth are described.

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 score0.016
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 head0.016
GPT teacher head0.238
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