Factors influencing electrochemical properties and performance of hydrocarbon based ionomer PEMFC catalyst layers
Bibliographic record
Abstract
This work investigated the properties of catalyst layers for proton exchange membrane fuel cells (PEMFC) that contained sulfonated poly(ether ether ketone) (SPEEK). A series of SPEEK polymers were prepared with varying ion exchange capacity (IEC) to test their oxygen mass transport properties, electrochemical kinetic parameters, proton conductivity, and water sorption characteristics. A simple method to fabricate catalyst layers containing SPEEK and polytetrafluoroethylene (PTFE) was developed. Catalyst layers were analyzed using scanning electron microscopy (SEM), mercury porosimetry and contact angle determination. Electrochemical characterization in an operating fuel cell was performed using current-potential polarization, cyclic voltammetry, and electrochemical impedance spectroscopy. Electrochemical oxygen reduction in SPEEK membranes was examined in a solid-state electrochemical cell, which allowed determination of oxygen mass transport properties and kinetic parameters. The oxygen diffusion coefficient and permeability was found to increase with increasing ion exchange capacity (IEC), while the solubility of oxygen correspondingly decreased, these trends are due to an increase in water content with increasing IEC. In comparison to perfluorinated electrolytes, such as Nafion®, SPEEK exhibited a lower permeability of oxygen due to a considerably lower solubility of oxygen.A decrease in fuel cell performance was observed when SPEEK was employed in the cathode catalyst layer as the proton conducting medium. The fuel cell current density showed a strong dependence on the method of fabrication of the catalyst layer and the content of SPEEK. Compared to Nafion®-based catalyst layers, SPEEK catalyst layers were found to suffer from low electrochemically active surface area (ESA) and low ionic conductivity. The weight content of SPEEK electrolyte was found to strongly influence the mass transport limited current density.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".