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Record W4409744666 · doi:10.1021/acs.nanolett.5c01586

Topology-Dependent Enhancement of Pyroelectric Property in Nanoarchitected GaN Metamaterials

2025· article· en· W4409744666 on OpenAlexafffund
Jun Cai, Benyamin Shahryari, Alireza Seyedkanani, Agus P. Sasmito, Abdolhamid Akbarzadeh

Bibliographic record

VenueNano Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMcGill University
KeywordsMetamaterialMaterials scienceProperty (philosophy)PyroelectricityOptoelectronicsTopology (electrical circuits)Condensed matter physicsNanotechnologyEngineering physicsPhysicsDielectricFerroelectricityElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

. This study investigates the pyroelectric properties of nanoarchitected gallium nitride (GaN) metamaterials with distinctive topologies, i.e., body-centered cube, octet truss, gyroid, and spinodoid, using molecular dynamics simulations. Our findings reveal a topology-dependent enhancement in the pyroelectric coefficient, primarily affected by the piezoelectric stress constant and thermal expansion coefficient. We demonstrate that decreasing the relative density further enhances the pyroelectric coefficient due to an increased surface-to-volume ratio that enhances the surface effects. Finally, we compute the pyroelectric figures of merit for thermal energy harvesting application, highlighting the superior pyroelectric performance of nanoarchitected GaN metamaterials compared to bulk GaN and GaN nanowires. These results underscore the potential of nanoscale topology engineering in the field of pyroelectricity for realizing next-generation nanogenerators, thermal imaging devices, and self-powered nanosensors.

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 categoriesnone
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 score0.003
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2025
Admission routes2
Has abstractyes

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