MétaCan
Menu
Back to cohort
Record W4292859016 · doi:10.3390/mi13091376

Potentiometric pH Sensor Based on Flexible Screen-Printable Polyaniline Composite for Textile-Based Microfluidic Applications

2022· article· en· W4292859016 on OpenAlexafffund
Yohan Laffitte, Bonnie L. Gray

Bibliographic record

VenueMicromachines · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolyanilineScreen printingMicrofluidicsMaterials sciencePotentiometric titrationSubstrate (aquarium)Composite numberTextileChemiresistorBiosensorElectrodeNanotechnologypH meterOptoelectronicsComposite materialChemistryPolymerPolymerization

Abstract

fetched live from OpenAlex

Skin pH can be used for monitoring infections in a healing wound, the onset of dermatitis, and hydration in sports medicine, but many challenges exist in integrating conventional sensing materials into wearable platforms. We present the development of a flexible, textile-based, screen-printed electrode system for biosensing applications, and demonstrate flexible polyaniline (PANI) composite-based potentiometric sensors on a textile substrate for real-time pH measurement. The pH response of the optimized PANI/dodecylbenzene sulfonic acid/screen-printing ink composite is compared to electropolymerized and drop-cast PANI sensors via open circuit potential measurements. High sensitivity was observed for all sensors between pH 3-10, with a composite based on PANI emeraldine base, demonstrating sufficient response time and a linear sensitivity of -27.9 mV/pH. This exceeded prior flexible screen-printed pH sensors in which all parts of the sensor, including the pH sensing material, are screen-printed. Even better sensitivity was observed for a PANI emeraldine salt composite (-42.6 mV/pH), although the response was less linear. Furthermore, the sensor was integrated into a screen-printed microfluidic channel demonstrating sample isolation during measurement for wearable, micro cloth-based analytical devices. This is the first fully screen-printed flexible PANI composite pH sensor demonstrated on a textile substrate that can additionally be integrated with textile-based microfluidic channels.

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 categoriesMeta-epidemiology (narrow)
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 score0.507
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
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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.

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

Citations27
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueMicromachinesSame topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207