Cross-correlated humidity-dependent structural evolution of Nafion thin films confined on a platinum substrate
Bibliographic record
Abstract
Nanometer thin films of Nafion ionomer interfaced with platinum form the functional electrodes in many electrochemical devices including fuel cells and electrolyzers. To impart facile proton conduction in a Nafion ionomer, sufficient hydration of the Nafion ionomer is necessary to create a percolating network of water-filled nanometer-sized hydrophilic domains that manifest as macroscopic swelling. This hydration behavior of the ionomer thin films is poorly understood especially for films confined on electrochemically relevant Pt substrates. In this work, we present the evolution of hydration-dependent microscopic hydrophilic domains and macroscopic expansion of a 55 nm thin Nafion film on a Pt substrate. The cross-correlation among the film macro-expansion from ellipsometry, the micro-expansion from GISAXS, and the water distribution from neutron reflectometry (NR) explains the observed non-affine behavior of the film which can be attributed to the randomly and spatially non-uniform distribution of water domains. A correlation between the macroscopic factor (ε/τ) for protonic conductivity, and the domain size and swelling is presented for the first time. In addition, interfacial water between Pt and the ionomer interface is estimated at 75% and 84% RH, and an increase in domain size with RH is discussed to explain the increased activity and oxygen diffusivity with RH.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".