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Record W3013273782 · doi:10.1063/1.5132965

Self-assembled InAs/InGaAsP/InP quantum dots: Intraband relaxation impacted by ultrathin GaP sublayer

2020· article· en· W3013273782 on OpenAlexafffund
Fujuan Huang, Yiling Xiong, Xiupu Zhang

Bibliographic record

VenueJournal of Applied Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCondensed matter physicsQuantum dotMaterials scienceRelaxation (psychology)PhononBand gapMonolayerAugerExcited stateOptoelectronicsNanotechnologyAtomic physicsPhysics

Abstract

fetched live from OpenAlex

The influence of an ultrathin GaP (or GaAs) sublayer on the nonradiative intraband relaxation in InAs/InGaAsP/InP quantum dots (QDs) is investigated. It is found that, based on our studies, the QDs with some heights (e.g., 1.5 nm) and GaP sublayer thicknesses (e.g., 1.03 monolayers) present the first excited state (ES) with higher state degeneracy with respect to ground state (GS), which suggests that the Auger relaxation is triggered more easily. We also find that the energy difference of the ES and GS decreases with increasing sublayer thickness, which suggests that the electron–phonon interaction is affected. This work further presents a study of intraband relaxation for an InAs/InP QD with a GaP or GaAs sublayer. It is found that there is a critical thickness of the GaP sublayer: When the sublayer is less than the critical thickness, the intraband relaxation is only determined by one-longitudinal optical (LO) phonon or two-LO phonons, which is dependent on QD heights. However, with the GaAs sublayer, QDs do not have the above feature. This finding may be helpful for designing and optimizing high-speed QD devices.

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 categoriesMeta-epidemiology (narrow)
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 score0.108
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.015
GPT teacher head0.242
Teacher spread0.226 · 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.

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

Citations5
Published2020
Admission routes2
Has abstractyes

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