External Reinforcement of Hydrocarbon Membrane By Combining Toughened Catalyst Layers and Interlocking Interfaces for High Mechanical Robustness of PEMFC
Bibliographic record
Abstract
For decades, in polymer electrolyte membrane fuel cell (PEMFC) field, hydrocarbon (HC) membranes have been constantly studied to replace perfluorinated sulfonic acid membranes owing to their low cost and high fuel efficiency. However, adopting HC membranes to practical PEMFCs has been not successful due to their poor mechanical stability which causes a mechanical failure with generating pin-hole under repeated volume expansion/shrinkage during cell operation. Conventionally, the problem has been addressed by inserting a porous mechanical supporter in HC membrane which is denoted as ‘internal reinforcement’. However, the introduction of the inert support decreases proton conduction and increases membrane cost. Here we present an external reinforcement of HC membrane as a new strategy to enhance mechanical durability of HC membrane. It features the incorporation of mechanically tough porous fibrous network into catalyst layers and the strong connection of HC membrane and the toughened catalyst layers with introducing an interlocking interface. The mechanically toughened catalyst layers and interfaces can effectively mitigate the volume change of HC membrane, lowing the membrane failure. Under an accelerated humidity cycling test, the externally reinforced HC membrane exhibits an enhanced durability compared to un-reinforced counterpart. Furthermore, contrary to the internal reinforcement, the external reinforcement strategy does not cause any loss of proton conductivity of HC membrane. Therefore, the external reinforcement coupled with toughed catalyst layers and interfaces can provide an effective way to enhance durability with preserving the proton conductivity of pristine HC membrane.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".