MétaCan
Menu
Back to cohort
Record W2019754098 · doi:10.1063/1.4817758

Strain analysis of highly scalable single InAs/InP quantum dots in a stress-sensitive environment

2013· article· en· W2019754098 on OpenAlexaff
Khaled Mnaymneh, Dan Dalacu, Philip J. Poole, Robin L. Williams

Bibliographic record

VenueApplied Physics Letters · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsQuantum dotPseudopotentialScalabilityQuantumStress (linguistics)OptoelectronicsMaterials scienceSuperlatticePhotonNanoscopic scaleRenormalizationNanotechnologyPhysicsCondensed matter physicsComputer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

We perform an experimental and computational study of the effects of external stress and intermixing on single site-selected InAs/InP quantum dots in a highly scalable stress-sensitive environment. While such effects are well known for their ability to tune emission spectra, little is known on how they influence emission shell spacing, electron-hole effective mass renormalization, and the physical size of the embedded quantum dot, which are all important parameters affecting the intended functionality. We show excellent agreement between experiment and finite-element solutions of the coupled Navier and Schrödinger equations, including recent atomistic pseudopotential calculations in the literature. These results indicate that using single self-assembled quantum dots in highly scalable, stress-sensitive settings as active elements in future bottom-up nanosystems offers greater versatility to not only quantum information systems where they serve as scalable single-photon sources but also to ultra-sensing capabilities in future nano-electro-mechanical architectures.

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 score0.185
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
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicSemiconductor Quantum Structures and DevicesFrench-language works237,207