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Record W2054108503 · doi:10.1116/1.1500747

Tunable emission from InAs quantum dots on InP nanotemplates

2002· article· en· W2054108503 on OpenAlex

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

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsQuantum dotLaser linewidthPhotoluminescenceMaterials scienceMolecular beam epitaxyNucleationChemical beam epitaxyOptoelectronicsRidgeWavelengthEpitaxyNanotechnologyOpticsLaserChemistryPhysicsLayer (electronics)

Abstract

fetched live from OpenAlex

Selective area chemical beam epitaxy is used to fabricate submicron [100]-oriented InP ridges with well-defined, defect-free (011) sidefacets and (001) tops. Following the deposition of two monolayers of InAs on such nanotemplates and subsequent capping with InP, photoluminescence spectra show for wider ridges strong emission from a thin InAs quantum well and, as the ridge width is reduced, a gradual appearance of a quantum dot emission at lower energy. The method allows continuous tuning on a given sample in a single growth run of both the quantum dot density and the emission wavelength. The result is a consequence of adatom diffusion from the ridge sidefacets onto the top (001) facet, which increases the amount of InAs beyond the critical thickness for three-dimensional nucleation to occur. Compared with growth on planar InP(001) substrates, InAs self-assembled quantum dots grown on these nanotemplates are more uniform as revealed by a twofold reduction in emission linewidth at 4 K.

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)0.001
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 score0.378
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.236
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