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Record W2792785881 · doi:10.1088/1361-665x/aab92e

A phase field approach for the fully coupled thermo-electro-mechanical dynamics of nanoscale ferroelectric actuators

2018· article· en· W2792785881 on OpenAlexaff
Dan Wang, Haoyuan Du, Linxiang Wang, Roderick Melnik

Bibliographic record

VenueSmart Materials and Structures · 2018
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsWilfrid Laurier University
FundersNational Natural Science Foundation of China
KeywordsFerroelectricityActuatorMaterials sciencePhase boundaryBoundary value problemContext (archaeology)Nanoscopic scaleThermalElectric fieldField (mathematics)VoltagePhase (matter)MechanicsMechanical engineeringCondensed matter physicsNanotechnologyOptoelectronicsEngineeringPhysicsElectrical engineeringThermodynamicsDielectric

Abstract

fetched live from OpenAlex

Abstract The fully coupled thermo-electro-mechanical properties of nanoscale ferroelectric actuators are investigated by a phase field model. Firstly, the thermal effect is incorporated into the commonly-used phase field model for ferroelectric materials in a thermodynamic consistent way and the governing equation for the temperature field is derived. Afterwards, the modified model is numerically implemented to study a selected prototype of the ferroelectric actuators, where strain associated with electric field-induced non-180° domain switching is employed. The temperature variation and energy flow in the actuation process are presented, which enhances our understanding of the working mechanism of the actuators. Furthermore, the influences of the input voltage frequency and the thermal boundary condition on the temperature variation are demonstrated and carefully discussed in the context of thermal management for real applications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.257
Teacher spread0.245 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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