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Record W1968102654 · doi:10.1109/tnano.2014.2316536

Flexible Fibrous Piezoelectric Sensors on Printed Silver Electrodes

2014· article· en· W1968102654 on OpenAlex
Ho Yeon Son, Jae Sung Park, Jonathan Huang, Jiseok Kim, Yoon Sung Nam, Woo Soo Kim

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.

Bibliographic record

VenueIEEE Transactions on Nanotechnology · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials sciencePiezoelectricityElectrodePolingNanofiberElectrospinningNanogeneratorFabricationOptoelectronicsSurface roughnessComposite materialBendingPrinted circuit boardNanotechnologyPolymerElectrical engineeringDielectric

Abstract

fetched live from OpenAlex

Here, we report a facile fabrication of flexible piezoelectric sensors based on highly aligned poly(vinylidene fluoride) (PVDF) nanofibers and printed silver electrodes without any additional poling processes. One-dimensional (1-D) piezoelectric PVDF nanofibers are directly produced onto stamped and sprayed interdigitated electrodes by electrospinning. We studied here the effect of contact area between nanofibers and electrodes by controlling the surface roughness of electrode. PVDF sensors show increased piezoelectric responses with larger actual contact area of the interdigitated electrodes. The measured output voltage under periodic bending stress is up to about 1 V. It is expected that this facile method to fabricate the PVDF sensors can be used to integrate the energy harvesters into flexible and stretchable functional electronic 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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.529
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.008
GPT teacher head0.209
Teacher spread0.200 · 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