Effects of dielectric saturation and ionic screening on the proton self-diffusion coefficients in perfluorosulfonic acid membranes
Bibliographic record
Abstract
Proton transport in perfluorosulfonic acid (PFSA) membranes is investigated through a statistical mechanical model that includes the effects of the interaction of the tethered sulfonate groups with both the water and solvated protons. We first derive a potential that describes the electrostatic field due to the dissociated sulfonic acid groups by extending the work of Gronbech-Jensen et al. [ Mol. Phys. 92, 941 (1997)] to a finite array of point charges. A highly convergent series is obtained which includes the effects of screening due to the protons. We then investigate the effects of both dielectric saturation and two distinct formulations of ionic screening on the proton self-diffusion coefficient in Nafion membranes over a range of water contents. Our computations show that the two phenomena (i.e., dielectric saturation and ionic screening) under constant temperature conditions result in canceling affects. Our calculations provide a radial dependence of the proton mobility suggesting that the dominant self-diffusion occurs in the central region of the pores, well separated from the sulfonate groups. Through comparison of our calculated diffusion coefficients with the experimental values we derived a slightly smaller average separation distance of the hydronium ion from the sulfonate ions than suggested by either electronic structure calculations or multistate empirical valence bond molecular-dynamics simulations.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".