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Record W2079051775 · doi:10.1063/1.4862230

Theoretical studies of optical gain tuning by hydrostatic pressure in GaInNAs/GaAs quantum wells

2014· article· en· W2079051775 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Applied Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydrostatic pressureQuantum wellCondensed matter physicsGallium arsenideElectronMaterials scienceElectronic band structureConduction bandOptoelectronicsHydrostatic equilibriumChemistryPhysicsOpticsLaser

Abstract

fetched live from OpenAlex

In order to describe theoretically the tuning of the optical gain by hydrostatic pressure in GaInNAs/GaAs quantum wells (QWs), the optical gain calculations within kp approach were developed and applied for N-containing and N-free QWs. The electronic band structure and the optical gain for GaInNAs/GaAs QW were calculated within the 10-band kp model which takes into account the interaction of electron levels in the QW with the nitrogen resonant level in GaInNAs. It has been shown that this interaction increases with the hydrostatic pressure and as a result the optical gain for GaInNAs/GaAs QW decreases by about 40% and 80% for transverse electric and transverse magnetic modes, respectively, for the hydrostatic pressure change from 0 to 40 kilobars. Such an effect is not observed for N-free QWs where the dispersion of electron and hole energies remains unchanged with the hydrostatic pressure. This is due to the fact that the conduction and valence band potentials in GaInAs/GaAs QW scale linearly with the hydrostatic pressure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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