Radically Coarse-Grained Approach to the Modeling of Chemical Degradation in Fuel Cell Ionomers
Bibliographic record
Abstract
We present a kinetic model of chemical degradation in perfluorosulfonic acid ionomer membranes. It accounts for pathways of radical formation along with mechanisms of ionomer degradation through radical attack. Simplifications in the set of model equations leads to analytical expressions for the concentration of hydroxyl radicals as a function of initial concentrations of iron ions and hydrogen peroxide. The coarse-grained ionomer degradation model distinguishes units that correspond to ionomer head groups, trunk segments of ionomer side chains, and backbone segments between two side chains. A set of differential equations is formulated to describe changes in concentrations of these units. The model is used to study the impact of different degradation mechanisms and ionomer chemistries on fluorine loss and change in ion exchange capacity. Comparison of the model with experimental degradation data for Nafion and Aquivion membranes allows rate constants of degradation processes to be determined. Results of these analyses are discussed in view of strategies to mitigate chemical degradation of ionomer membranes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".