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Record W2897129956 · doi:10.1007/s40243-018-0137-5

Stretchable current collectors based on carbon embedded in a poly (acrylamide)/poly (N,N-methylenebisacrylamide) hydrogel modified with Nafion 117®

2018· article· en· W2897129956 on OpenAlexafffund
Mariusz Radtke, Anna Ignaszak

Bibliographic record

VenueMaterials for Renewable and Sustainable Energy · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of New Brunswick
FundersNew Brunswick Innovation Foundation
KeywordsNafionMaterials scienceSelf-healing hydrogelsChemical engineeringAcrylamideAqueous solutionPolymer chemistryPolymerizationCarbon fibersGrapheneConductivityPolypyrroleCarbon nanotubeElectrodeCuring (chemistry)MonomerComposite materialPolymerComposite numberElectrochemistryOrganic chemistryNanotechnologyChemistry

Abstract

fetched live from OpenAlex

In this study, we optimized the dispersion of hydrophobic carbons within ionically conductive hydrogels composed of a poly (acrylamide)-pAAm/poly (N,N-methylenebisacrylamide)-pMBAA modified with Nafion 117®. The carbon-embedded hydrogel films were prepared by in situ UV polymerization of aqueous suspension containing KCl, acrylamide and N,N-methylenebisacrylamide monomers, the multi-walled-carbon nanotubes, graphene, single-walled carbon nanohorns, and their composites with polypyrrole. These electrodes were translucent, stretchable, ionically and electronically conductive at low carbon content. In addition, they were very flexible, reaching a stretch up to 1475.57% of their initial length. Mechanical characteristics and conductivity were measured at their maximum hydration, corresponding to water uptake of 47.20% after 5 days of curing in humidity chamber. Hydrogels with dispersed carbon demonstrated both ionic and electronic conductivity in hydrated state and electronic conductivity alone when the electrode was dry. Nafion 117® acted as a surfactant and played a significant role in the improvement of carbon distribution within the hydrogel due to the hydrophobic–hydrophilic interaction between hydrogel, Nafion and the carbon. This was further correlated with changes in zeta potential at the carbon–hydrogel interface upon addition of Nafion, measured using a rotating disk electrode voltammetry.

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)0.001
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: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.219
Teacher spread0.211 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

Explore more

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