(Invited) Further Excursions into the Probing of Internal and Interfacial Structure of Ionomer Thin Films
Bibliographic record
Abstract
The critical importance of catalyst layer ionomer in numerous transport phenomena (proton conduction, oxygen and water transport) and also in catalyst utilization at multiple length scales is well acknowledged [1]. Thickness-dependent properties such as proton conductivity, water uptake, swelling and water diffusivity have now confirmed that ionomer thin films possess properties significantly different than those of the bulk ionomer materials [2]. Previous work from our group, both independent and collaborative, confirmed suppression of proton conductivity in thin films [3], wettability changes with film thickness and thermal annealing [4], influence of substrate on internal structure [5] and water uptake [6], similarity of T2-relaxations in proton NMR of thin and thick films [7] and recent discovery of temperature-dependent vibrational mode of Nafion ionomer [8]. Tremendous progress made on the topic of ionomer thin films over the past decade has been summarily presented in a recent review [2]. However, many aspects of ionomer thin film structure and properties still remain unknown. For example, despite the confirmation of strong thickness-dependence of ionomer properties for film below 50 nm thickness, one question continues to elude us: what is the critical thickness below which ionic domains cannot be sustained? In a quest to answer this question, we have employed high-resolution electron microscopy to deduce the presence/absence of ionic domains in 4-30nm thin films. There is indication of a critical thickness below which domains are evidently not present. Recent neutron reflectometry measurements from our group have focussed on the quantification of interfacial water (Pt/ionomer interface) and water in the bulk phase of the ionomer thin films on platinum substrate. The results acquired to date indicate that both interfacial and bulk water are dependent on the ionomer molecular structure. Complementing these measurements with GISAXS, ellipsometry, QCM and impedance spectroscopy – a clearer picture of the ionomer structure-property is emerging. The talk will share these new results and discuss the implications of the findings on fuel cell behaviour. Reference: Karan, Current Opin. Electrochem . 5 (1), (2017) 27-35. Kusoglu, A.Z. Weber Chem Rev , 117 (3) (2017), 987-1104 K. Paul, R. McCreery, K. Karan, J Electrochem So c, 161 (14) (2014), F1395-F1402 K. Paul, H.K.K. Shim, J.B. Giorgi, K. Karan, J Polym Sci Part B: Polym Phys , 54 (13) (2016), 1267-1277 Kusoglu, D. Kushner, D.K. Paul, K. Karan, M.A. Hickner, A.Z. Weber, Adv Funct Mater , 24 (2014), 4763-4774 K. Shim, D.K. Paul, K. Karan, Macromolecules , 48 (22) (2015), 8394-8397 NE De Almeida, DK Paul, K Karan, GR Goward, J Phys Chem C 119 (3), (2015) 1280-1285 VO Kollath, K Karan, Physical Chemistry Chemical Physics 18 (37), (2016) 26144-26150
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".