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Record W1982437366 · doi:10.1116/1.1495504

Magneto–photoluminescence study of intermixed self-assembled InAs/GaAs quantum dots

2002· article· en· W1982437366 on OpenAlexaff
S. Ménard, J. Beerens, David L. Morris, Vincent Aimez, Jacques Beauvais, S. Fafard

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 SciencesUniversité de Sherbrooke
Fundersnot available
KeywordsPhotoluminescenceQuantum dotWetting layerMaterials scienceAnnealing (glass)Condensed matter physicsMagnetic fieldOptoelectronicsMolecular physicsChemistryPhysics

Abstract

fetched live from OpenAlex

The electronic structure of InAs/GaAs self-assembled quantum dots and the carrier capture dynamics in these dots have been studied by magneto–photoluminescence at low temperature (5 K). We report results obtained on a series of samples processed by rapid thermal annealing. This intermixing procedure led to a significant narrowing of the inhomogeneous photoluminescence emission bands related to the various dot shell states, as compared to results obtained on unprocessed samples, which in turn improved the conditions for the observation of the Fock–Darwin energy levels structure as a function of the magnetic field, up to 15 T. We also observed that the ratio of the wetting layer emission intensity over the integrated intensity of the quantum dot emission bands increases nonlinearly with the magnetic field. This nonlinear behavior, which is more apparent at low photocarrier density, suggests that transport properties contribute to limit the carrier capture by the dots.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2002
Admission routes1
Has abstractyes

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Same venueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and PhenomenaSame topicSemiconductor Quantum Structures and DevicesFrench-language works237,207