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Record W4388942386 · doi:10.3390/cryst13121626

Piezoelectric Elements with PVDF–TrFE/MWCNT-Aligned Composite Nanowires for Energy Harvesting Applications

2023· article· en· W4388942386 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystals · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsLakehead University
FundersLakehead University
KeywordsMaterials sciencePiezoelectricityComposite materialCarbon nanotubeComposite numberPiezoelectric coefficient

Abstract

fetched live from OpenAlex

A self-sustainable power supply function with flexibility, mechanical stability, and lightweight quality is among the required properties for pressure sensors and other low-power-consuming electronics and wearable devices. In this work, a poly(vinylidene fluoride-trifluoroethylene)/multi-walled carbon nanotube (P(VDF–TrFE)/MWCNT) composite was prepared to increase the electrical conductivity of the piezoelectric polymer and, thus, improve its electrical power generation capabilities. It was soaked by injection molding through an anodic aluminum oxide membrane to align vertically with the dipoles and exclude the possibility of dipole moment quenching. The composite membrane-type element exhibited an excellent piezoelectric coefficient d33 of 42 pC/N at a frequency of 50 Hz and an applied force intensity of 10 N, while the sensitivity was ~375 µV/g, which is favorable for self-powered pressure sensor application. The resulting composite element was utilized to generate the piezoelectric signal and to investigate the dependence of the electromechanical behavior on the surface roughness, morphology, and contact interface resistance.

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.

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: none
Teacher disagreement score0.645
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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