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Record W2064079290 · doi:10.1016/j.proeng.2009.06.025

Defects-enhanced flexoelectricity in nanostructures

2009· article· en· W2064079290 on OpenAlexaff
Roderick Melnik

Bibliographic record

VenueProcedia Engineering · 2009
Typearticle
Languageen
FieldMaterials Science
TopicNonlocal and gradient elasticity in micro/nano structures
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFlexoelectricityNanostructureMaterials scienceElectric fieldFinite element methodField (mathematics)NanotechnologySemiconductorCondensed matter physicsPhysicsDielectricOptoelectronicsThermodynamicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Recent studies show that low dimensional nanostructures may exhibit nonlocal electromechanical effects such as flexoelectricity. Despite the recent progress in nanostructure growth techniques imperfections such as defects are practically unavoidable. These imperfections may enhance flexoelectric effects. Therefore, the main goal of this paper is to analyze the effects of these imperfections on linear electromechanical properties and on flexoelectricity. The constitutive relations for the adiabatically insulated reversible system are derived from the total differential of the general thermodynamic Gibbs potential. The mechanical and electrical balance equations coupled through the constitutive equations are then solved with finite element method for the defective nanostructures. We focus in our study on GaN-based nanostructures which are important in electronic and optoelectronic applications. They exhibit higher magnitudes of electric field compared to other semiconductors in similar contexts. Our results are presented for GaN quantum dots embedded in an AlN matrix.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.192
Teacher spread0.189 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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