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Record W2057332379 · doi:10.1063/1.1323997

Laser-induced InAs/GaAs quantum dot intermixing

2000· article· en· W2057332379 on OpenAlexaff
Jan J. Dubowski, Claudine Nì. Allen, S. Fafard

Bibliographic record

VenueApplied Physics Letters · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsQuantum dotPhotoluminescenceWetting layerMaterials scienceLaserOptoelectronicsExcited stateAnnealing (glass)Ground stateQuantum dot laserBand gapBlueshiftGallium arsenidePhotonicsCondensed matter physicsSemiconductor laser theoryOpticsSemiconductorAtomic physicsPhysics

Abstract

fetched live from OpenAlex

Laser annealing of InAs/GaAs quantum-dot (QD) microstructures has been investigated for selective area tuning of their electronic shell structure. Extensive blueshifts of the QD excited states were observed following 20–40 s laser irradiation. In the most extreme case, we were able to shift the position of the ground state transition by 298 meV, i.e., to the spectral region where the photoluminescence signal originates from the as-grown InAs wetting layer. A reduction from ∼50 to 8 meV of the full width at half maximum of the PL peak corresponding to this transition indicates a drastic change in the structural characteristics of the investigated QD ensemble. The attractive feature of the laser-QD-intermixing technique is that it offers the possibility of obtaining targeted blueshifts and inter-sublevel energy spacing on the lateral scale required in the fabrication of QD-based integrated optoelectronic devices and, possibly, photonic band gap crystals.

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 head0.014
GPT teacher head0.235
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

Citations56
Published2000
Admission routes1
Has abstractyes

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