The Control and Effect of Pore Size Distribution in AEMFC Catalyst Layers
Bibliographic record
Abstract
Catalyst ink for anion-exchange catalyst coated membranes based on FuMA-Tech FAA-3 membranes and ionomer typically requires high-boiling solvents. Here, we investigate the disproportionate effect of even small quantities of high-boiling solvent in the catalyst ink on the catalyst layer microstructure. High porosity in the mesoporous regime, 20–100 nm, is found to be an essential characteristic of effective anion-exchange catalyst layers for increasing membrane hydroxide ion conductivity and reducing mass-transport losses. High porosity in the nanoporous regime (<20 nm pore diameter) facilitates improvements in the kinetic region of polarization curves at the expense of mass-transport losses. New strategies are introduced to improve the control of distribution of pore sizes in the catalyst layer and to increase the mesoporosity. Beginning-of-life power densities for O2/H2 anion exchange membrane fuel cells (AEMFCs), under zero backpressure, were accordingly increased from 276 to 428 mW·cm−2, placing it among the highest AEMFC power densities reported in the literature under the conditions studied, representing a significant improvement over previously reported performances for FAA-3. The study highlights a need to develop anion-exchange solid polymer ionomers soluble in low-boiling solvents for preparing catalyst inks, and a more rigorous evaluation of porosimetry data and catalyst layer preparation methods for AEMFCs.
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".