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Record W4406748740 · doi:10.1021/acsomega.4c09548

Fully Printed Flexible Polystyrene/Graphite-Based Temperature Sensor with Excellent Properties for Potential Smart Applications

2025· article· en· W4406748740 on OpenAlexafffund
Ahmad Al Shboul, Mohsen Ketabi, Jenner H. L. Ngai, Daniella Skaf, Simon Rondeau‐Gagné, Ricardo Izquierdo

Bibliographic record

VenueACS Omega · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of WindsorNational Research Council CanadaÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsPolystyreneGraphiteMaterials scienceNanotechnologyExpanded polystyreneComposite materialPolymer

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide This study presents an innovative temperature sensor based on a thermistor nanocomposite of graphite (Gt) and polystyrene (PS). The sensor exhibited notable thermal stability and film integrity, offering two distinct linear response regions within the tested temperature range of −10 to 60 °C. It demonstrated a sensitivity of 0.125% °C –1 between −10 and 10 °C, followed by another linear response with a sensitivity of 0.41% °C –1 from 20 to 60 °C. Furthermore, it exhibited a response/recovery time of 0.97/1.3 min at a heating/cooling rate of 60 °C min –1 . The sensor maintained minimal baseline drift even when subjected to varying humidity levels. We assessed its mechanical flexibility and stability for hundreds of bending cycles at a bending angle of 30°, adapting to dynamic environmental conditions. The sensor’s thermomechanical test (response to mechanical stress under temperature fluctuations) underscored its adaptability over a temperature range of −10 to 60 °C. Notably, it displayed excellent chemical stability, maintaining consistent performance when subjected to harsh environmental conditions like exposure to corrosive gases and prolonged immersion in tap water. Real-world tests demonstrated its practical utility, including precise temperature measurements in solid objects and breath temperature monitoring. These findings suggest promising applications in healthcare, environmental monitoring, and various IoT applications.

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 score0.175
Threshold uncertainty score0.689

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 head0.009
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

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

Citations14
Published2025
Admission routes2
Has abstractyes

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