MétaCan
Menu
Back to cohort
Record W4403842802 · doi:10.1063/5.0227725

Quantitative photothermal investigation of nonradiative recombination parameters in GaAs/InAs(QD)/GaAs quantum dot structures using a three-layer laser beam deflection model

2024· article· en· W4403842802 on OpenAlexaff
S. Bouagila, S. Ilahi, M. Baïra, Andreas Mandelis, N. Yacoubi

Bibliographic record

VenueJournal of Applied Physics · 2024
Typearticle
Languageen
FieldEngineering
TopicChalcogenide Semiconductor Thin Films
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQuantum dotPhotothermal therapyGallium arsenideMaterials scienceOptoelectronicsDeflection (physics)Layer (electronics)Laser beamsRecombinationLaserQuantum wellPhotothermal spectroscopyMolecular beam epitaxyOpticsChemistryPhysicsNanotechnology

Abstract

fetched live from OpenAlex

In this paper, we developed a theoretical model for the photothermal deflection technique in order to investigate the electronic parameters of three-layer semiconductor structures. This model is based on the resolution of thermal and photogenerated carrier diffusion-wave equations in different media. Theoretical results show that the amplitude and phase of the photothermal deflection signal is very sensitive to the nonradiative recombination parameters. The theoretical model is applied to one layer of InAs quantum dots (QDs) inserted in GaAs matrix InAs/GaAs QDs in order to investigate the QD density effects on nonradiative recombination parameters in InAs through fitting the theoretical photothermal beam deflection signal to the experimental data. It was found that the minority carrier lifetime and the electronic diffusivity decrease as functions of increasing InAs QD density. This result is also related to the decrease in the mobility from 21.58 to 4.17 (±12.9%) cm2/V s and the minority carrier diffusion length from 0.62 (±5.8%) to 0.14 (±10%) μm, respectively. Furthermore, both interface recombination velocities S2/3 of GaAs/InAs (QDs) and S1/2 of InAs (QDs)/GaAs increase from 477.7 (±6.2%) to 806.5 (±4%) cm/s and from 75 (±7.8%) to 148.1 (±5.5%) cm/s, respectively.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.057
GPT teacher head0.278
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied PhysicsSame topicChalcogenide Semiconductor Thin FilmsFrench-language works237,207