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Record W2370363223 · doi:10.1149/ma2014-02/21/1244

Direct Imaging of Nanoscale Morphology of Perfluorosulfonic Acid Ionomers

2014· article· en· W2370363223 on OpenAlexaffabout
Devproshad K. Paul, Yuquan Zou, Jing Li, Kunal Karan

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)University of Calgary
Fundersnot available
KeywordsIonomerCrystalliteMaterials scienceNanostructureIonic bondingPhase (matter)FluorocarbonAmorphous solidNafionChemical engineeringSmall-angle X-ray scatteringNanotechnologyChemistryComposite materialCrystallographyScatteringOpticsIonOrganic chemistryPhysical chemistryPolymerPhysicsCopolymerElectrochemistry

Abstract

fetched live from OpenAlex

Understanding the nanostructure and morphology of perfluorosulfonic acid (PFSA) ionomer and its correlation to functional properties are extremely important for designing new ionomer materials. A number of structural models of ionomer (mainly Nafion ® ) have been proposed based on x-ray scattering data to explain the impact of morphology on its water swelling and transport properties. One of the earliest models is cluster network model where spherical ionic clusters, connected by a narrow channel are embedded by amorphous fluorocarbon matrix. 1 Alternatively, Gebel and coworkers have proposed fibrillar model, which consists of fluorocarbon crystallites surrounded by ionic groups. 2 Most recently, parallel water channel model is proposed by Schmidt-Rohr et al. where large fluorocarbon crystallites consists the parallel channel that are decorated with the sulfonate group inside. 3 The common element to these models is a phase separated morphology – fluorocarbon phase and ionic cluster phase. However, disagreement regarding the shape, size and behaviour of the phases remain. To resolve the controversy, direct imaging technique such as electron microscope have been employed but never been successful to resolve the real nanostructure and morphology. In our approach, we have employed transmittance electron microscope (TEM) to directly image the well-defined crystalline phase (fluorocarbon matrix) and amorphous phase (ionic cluster). The ionomer film was prepared on the spongy carbon film supported by Cu grid adopting self-assembly method 4,5 . Both free-standing and carbon-supported films ranging in thickness of around 4 to 50 nm were generated and investigated by the instrument Tecnai TF20 G2 FEG-TEM (FEI, Hillsboro, Oregon, USA) at 200kV acceleration voltage. The image was captured by Gatan UltraScan 4000 CCD (Gatan, Pleasanton, California, USA) at 2048x2048 pixels. Although a number of research papers have discussed the crystalline phase in ionomer structure but found it challenging to image because of the high degree of disorderdness of the ionomer materials. Therefore, researchers mostly relied on SAXS/SANS data to depict the structural morphology. Hence, it is very exciting to present images where the crystalline phase is clearly evident by direct TEM imaging of Nafion ® ionomer Nanofilm without any chemical modification and treatment (Figure 1). The highly ordered crystalline phase consists of a number of lamellae that are surrounded by the amorphous phase. The crystalline phase varies from 4 to 6 nm in size. The d spacing of those lamellae was calculated to be 0.37 nm. This particular structure of ionomer is consistent with the Fibrillar model proposed by Gebel et al . 2 where the majority of hydrophobic, Teflon-like phase stay in the high density crystalline region and amorphous phase consist of ionic domains (Figure 2). These results may help resolve the debate around ionomer structure model. It is also interesting to see that the crystalline phase is evident regardless of equivalent weight of ionomers whereas the size, shape and extent of the crystalline phase depends on the equivalent weight. We plan to discuss the thermal annealing and dispersion effect on the morphological change of the ionomer in the nanofilms. The morphology of supported film comparing with freestanding nanofilm also will be discussed. Acknowledgements Financial Early Researcher Awards (Ontario Ministry of Research and Innovation) and Natural Sciences and Engineering Research Council of Canada (NSERC), MITACS Elevate PDF Fellowship (Devproshad K. Paul), Automotive Fuel Cell Cooperation (AFCC). References 1. W. Y. Hsu and T. D. Gierke, Macromolecules, 1982 , 15, 101. 2. L. Rubatat, G. Gebel, and O. Diat, Macromolecules , 2004 , 37,7772-7783 3. K. Schmidt-Roh and Q. Chen, Nat. Mater, 2008 , 7, 75-83. 4 . D. K. Paul, K. Karan, J. Giorgi, A. Docoslis and J. Pearce, Macromolecules 2013 , 46 (9), 3461–3475 5. D. K. Paul, A. Fraser, J. Pearce and K. Karan, ECS Trans . 2011 , 41 (1), 1393-1406.

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 score0.257
Threshold uncertainty score0.488

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 head0.005
GPT teacher head0.191
Teacher spread0.185 · 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".

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Citations1
Published2014
Admission routes2
Has abstractyes

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