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Record W1438728302 · doi:10.12693/aphyspola.121.85

Coupled Multiphysics Models for the Analysis οf the Conduction and Valence Band Eigenenergies in Cylindrical Quantum Dots

2012· article· en· W1438728302 on OpenAlexafffund
Sanjay Prabhakar, Eduard Takhtamirov, Roderick Melnik

Bibliographic record

VenueActa Physica Polonica A · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMultiphysicsConduction bandValence bandValence (chemistry)Quantum dotPhysicsCondensed matter physicsThermal conductionQuantumQuantum mechanicsMaterials scienceStatistical physicsBand gapThermodynamicsElectronFinite element method

Abstract

fetched live from OpenAlex

We develop a mathematical model for the analysis of conduction and valence band eigenenergy in quantum dots.We apply the model to study the band structure calculations of low dimensional semiconductor nanostructures such as wurtzite AlN/GaN quantum dots in cylindrical coordinates in presence of applied magnetic field along z-direction.We use a finite element method to solve the resulting model and to obtain eigenvalues and wave functions of cylindrical quantum dots.We provide details of the methodology of solution and appropriate boundary conditions.A special attention is given to the case of applied magnetic field along z-direction, we found localized eigenstates and wave functions in the conduction and valence bands for which our results open new possibilities for the design of the optoelectronics devices where the combination of electron-hole pairs can be used as tuning parameters.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.030
GPT teacher head0.285
Teacher spread0.254 · 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

Citations4
Published2012
Admission routes2
Has abstractyes

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