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Record W2052376573 · doi:10.1063/1.2199457

Si (111) substrates as highly effective pseudomasks for selective growth of GaN material and devices by ammonia-molecular-beam epitaxy

2006· article· en· W2052376573 on OpenAlex
H. Tang, S. Haffouz, J. A. Bardwell

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.

Bibliographic record

VenueApplied Physics Letters · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsMolecular beam epitaxyMaterials scienceOptoelectronicsSiliconNucleationEpitaxySubstrate (aquarium)SapphireFabricationNanotechnologyLayer (electronics)Wide-bandgap semiconductorChemistryOpticsLaser

Abstract

fetched live from OpenAlex

The unique property of Si (111) as effective pseudomask substrate for selective growth of GaN by ammonia-molecular-beam epitaxy is reported. The critical nucleation temperature of GaN on Si (111) surface is found to be as low as 700°C, much lower than that on sapphire or AlN surface. As a result, selective growth of GaN is possible by ammonia-molecular-beam epitaxy on Si (111) substrates using a patterned AlN buffer layer. The wide range of growth temperatures (700–900°C) available for selective growth is a critical advantage for control and optimization of the facet characteristics of the selectively grown GaN patterns as required for potential fabrication of site-specific GaN or InGaN quantum dots. The demonstrated ease of selective growth of GaN on silicon has also implications in potential on-chip integration of GaN devices with silicon 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.

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 categoriesMeta-epidemiology (narrow)
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 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)0.0000.000

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 head0.003
GPT teacher head0.202
Teacher spread0.198 · 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