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Record W4405798036 · doi:10.1002/adfm.202417618

Ultrahigh Piezoelectricity in Truss‐Based Ferroelectric Ceramics Metamaterials

2024· article· en· W4405798036 on OpenAlexafffund
Jiahao Shi, Kang Ju, Haoyu Chen, Valérie Orsat, Agus P. Sasmito, Ali Ahmadi, Abdolhamid Akbarzadeh

Bibliographic record

VenueAdvanced Functional Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsÉcole de Technologie SupérieureUniversité de MontréalMcGill University
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMaterials sciencePiezoelectricityFerroelectricityPyroelectricityFigure of meritDielectricCeramicMetamaterialTrussEnergy harvestingComposite materialOptoelectronicsEnergy (signal processing)Structural engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Conventional porous ferroelectric materials sacrifice their piezoelectric constants for improving various figures of merit due to a rapidly decreased dielectric constant. Here, novel truss‐based ferroelectric metamaterials that simultaneously offer ultrahigh piezoelectric constants and ultralow dielectric constants, originating from the unique combination of truss loading states and polarization direction, are discovered. The homogenization method alongside an analytical model is proposed to predict and elucidate their extraordinary properties, while a customized ferroceramic additive manufacturing platform is resorted to fabricate them. Unlike porous ferroelectrics, ultrahigh piezoelectric constants at low relative densities ( ρ r ≈0.1) are attained. For example, with appropriate scaling, the experimental values of d 31 , d 33 , and d 42 for a ferroelectric octet truss with ρ r = 0.1, can reach 849, −659, and 836 pC N −1 , respectively, which are 3.14, 6, and 2 times higher than the counterpart of bulk BaTiO 3 ceramics. Combined with the ultralow dielectric constant, extremely high ferroelectric figures of merit, e.g., piezoelectric voltage constant of 11.098 Vm N −1 , piezoelectric energy harvesting figure of merit 9422 × 10 −12 m 2 N −1 , and pyroelectric voltage sensitivity of 56.7 × 10 −3 m 2 C −1 , are also observed. The multifunctional ferroelectric metamaterials open new avenues for their applications in self‐powered ultrasensitive accelerometers, high‐performance noncontact sensors, and wearable input devices.

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), Insufficient 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 score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.213
Teacher spread0.201 · 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

Citations22
Published2024
Admission routes2
Has abstractyes

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