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Coupled Effects in Quantum Dot Nanostructures with Nonlinear Strain and\n Bridging Modelling Scales

2007· preprint· en· W4298338620 on OpenAlexfundno aff
Roderick Melnik, D. Roy Mahapatra

Bibliographic record

VenuearXiv (Cornell University) · 2007
Typepreprint
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPiezoelectricityNonlinear systemContext (archaeology)Statistical physicsBridging (networking)QuantumQuantum dotStrain engineeringEnergy minimizationPhysicsComputer scienceCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We demonstrate that the conventional application of linear models to the\nanalysis of optoelectromechanical properties of nanostructures in bandstructure\nengineering could be inadequate. The focus of the present paper is on a model\nbased on the coupled Schrodinger-Poisson system where we account consistently\nfor the piezoelectric effect and analyze the influence of different nonlinear\nterms in strain components. The examples given in this paper show that the\npiezoelectric effect contributions are essential and have to be accounted for\nwith fully coupled models. While in structural applications of piezoelectric\nmaterials at larger scales, the minimization of the full electromechanical\nenergy is now a routine in many engineering applications, in bandstructure\nengineering conventional approaches are still based on linear models with\nminimization of uncoupled, purely elastic energy functionals with respect to\ndisplacements. Generalizations of the existing models for bandstructure\ncalculations are presented in this paper in the context of coupled effects.\n

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.171
Teacher spread0.145 · 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 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
Published2007
Admission routes1
Has abstractyes

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