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0-3 Barium Titanate-PDMS Flexible Film for Tactile Sensing

2020· article· en· W3038866031 on OpenAlexaff
Kiran Kumar Sappati, Sharmistha Bhadra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceBarium titanateDielectricPiezoelectricityComposite materialModulusComposite numberAnalytical Chemistry (journal)OptoelectronicsOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Lead free BaTiO3-PDMS piezoelectric composite thin films are fabricated with simple process. Composite films are prepared by dispersing 20, 30, 40, and 50 wt% of BaTiO3in cross-linked PDMS matrix. Corona poling of the films is performed to improve the piezoelectric properties of the films. Piezoelectric properties of the films are studied by measuring the charge developed across the thickness of the film under a compressive force. A 50 wt% poled BaTiO3-PDMS film has shown a piezoelectric charge constant of 178 pC/N and achieves a dielectric constant of 4.59. Tensile tests indicate that these films are very soft and flexible with low Young’s modulus. A 50 wt % poled BaTiO3-PDMS film film has shown a Young’s modulus 3.92 Mpa. The film generates charge across the film proportional to the finger pressure applied on them. Thus it demonstrates effectiveness for tactile sensing. As a tactile sensor a 50 wt% poled film shows a sensitivity of 38.34 kPa−1. High charge response for tiny forces makes the composite a good candidate for tactile sensing applications such as robotic skin and touch pads.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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)0.0050.002

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 head0.027
GPT teacher head0.228
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 source (direct Gemma or distilled Codex), 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

Citations9
Published2020
Admission routes1
Has abstractyes

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