Investigation of Transport Mechanisms for Sulfonated Silica-Based Fuel Cell Electrode Structures
Bibliographic record
Abstract
Ceramic carbon electrodes (CCEs) have demonstrated their ability to function as proton exchange membrane fuel cell electrodes under low relative humidity (RH) conditions.Small quantities of sulfonated silane in the catalyst layer produced electrodes with high surface area, porosity, and water retention which improved catalytic activity and proton conductivity.The purpose of this work was to investigate the mechanisms that facilitate enhanced performance of CCE electrodes under different RH conditions.Differences in transport phenomena related to membrane, electrode, and reactant concentration components were measured and compared for standard Nafion-based and CCE cathode catalyst layers using oxygen, air, helox (21% O 2 in He), and 4% O 2 in N 2 .Membrane electrode assemblies were characterized via cyclic voltammetry and electrochemical impedance spectroscopy.CCE cathodes displayed decreased resistance related protonic and electronic transport when relative humidity was lowered, and both types of electrodes suffered limitations due to oxygen transport losses where the oxygen also undergoes reduction in the catalyst layer.Remarkably, at 20% RH there was no change in performance at lower oxygen concentrations or mass transport loss observed for the CCE cathodes, indicating that the overall oxygen transport (through the gas diffusion layer and ionomer) is enhanced using this type of electrode structure.
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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 | 0.001 |
| 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 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".