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Development of a Fully-Printed Flexible Polystyrene-Based Temperature Sensor with Anti-Humid Property

2023· article· en· W4386214674 on OpenAlexafffund
Ahmad Al Shboul, Ankur Gohel, Mohsen Ketabi, Ricardo Izquierdo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolystyreneAtmospheric temperature rangeMaterials sciencePhysicsThermodynamicsPolymerComposite material

Abstract

fetched live from OpenAlex

We present a simple temperature sensing method based on a polystyrene (PS) and graphite (Gt) flakes nanocomposite. The conductive bridge formed by the Gt flakes, in conjunction with the elasticity of the PS with temperature, enables temperature sensing over a wide temperature range. The nanocomposite's hydrophobic nature ensures remarkable stability and resistance to changes in environmental humidity. Our experiments demonstrate that PS-based sensor stability is exceptional across a wide range of environmental humidity, from 10% to 80% RH, with high sensitivity (+0.37%$\ ^\circ \mathrm{C}^{-1})$for temperature sensing between$20\ ^\circ\mathrm{C}$and$80\ ^\circ\mathrm{C}$, fast response time in seconds, and high detection resolution to$3\ ^\circ\mathrm{C}$change. These promising results indicate that the fully printed, flexible temperature sensor is a promising candidate for applications requiring flexible and accurate temperature sensing capabilities.

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 score0.001
Threshold uncertainty score0.003

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.222
Teacher spread0.203 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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