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Band structures of laterally coupled quantum dots, accounting for electromechanical effects

2010· article· en· W2026191609 on OpenAlexafffund
Sanjay Prabhakar, Roderick Melnik, Sunil Patil

Bibliographic record

VenueJournal of Physics Conference Series · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuantum dotWetting layerPhotonicsOptoelectronicsSemiconductorBand gapQuantum tunnellingPiezoelectricitySuperposition principleMaterials scienceNanotechnologyPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

In a series of recent papers we demonstrated that coupled electro-mechanical effects can lead to pronounced contributions in band structure calculations of low dimensional semiconductor nanostructures (LDSNs) such as quantum dots, wires, and even wells. Some such effects are essentially nonlinear. Both strain and piezoelectric effects have been used as tuning parameters for the optical response of LDSNs in photonics, band gap engineering and other applications. However, these effects have been largely neglected in literature while laterally coupled quantum dots (QDs) have been studied. The superposition of electron wave functions in these QDs become important in the design of optoelectronic devices as well in tayloring properties of QDs in other applications areas. At the same time, laterally grown QDs coupled with electric and mechanical fields are becoming increasingly important in many applications of LDSN-based systems, in particular where the tunneling of electron wave function through wetting layer (WL) becomes important and the distance between the dots is treated as a tuning parameter. Indeed, as electric and elastic effects are often significant in LDSNs, it is reasonable to expect that the separation between the QDs may also be used as a tuning parameter in the application of logic devices, for example, OR gates, AND gates and others. In this contribution, by using the fully coupled model of electroelasticity, we build on our previous results while analyzing the influence of these effects on optoelectronic properties of QDs. Results are reported for III-V type semiconductors with a major focus given to GaN/AlN based QD systems.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 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

Citations0
Published2010
Admission routes2
Has abstractyes

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