Direct Propane Fuel Cell Anode with Interdigitated Flow Fields: Two-Dimensional Model
Bibliographic record
Abstract
The first two-dimensional model of a direct propane fuel cell (DPFC) anode was developed and used to investigate materials and operating conditions that resulted in improved DPFC anode performance. The software used, FreeFEM++, is open source and is based on the finite element method. The anode catalyst layer (ACL) was composed of three phases. One solid phase was the platinum catalyst supported on porous carbon (an electron conductor). The second solid phase consisted of solid zirconium phosphate (a proton conductor at 150 °C). The gas phase was located within the pores of the carbon and between the solid particles. Operation at 150 °C allowed the propane gas phase concentration to be in direct contact with the catalyst at the entrance to the ACL. This was an important advantage compared to previous DPFC operations at conditions where aqueous liquids are present (PEMFC at temperatures less than 100 °C and direct propane PAFC). When aqueous liquids surround the catalyst, the propane concentration in contact with the catalyst at the ACL entrance is much smaller because the solubility of propane in aqueous liquids is small. The one-third improvement in the anode overpotential was attributed to this difference. By using interdigitated flow fields with the propane feed in one set of channels and the carbon dioxide product in another set of channels, there was no mixing of the two so that the maximum propane concentration was always present at the entrance to the ACL. The residence time could be chosen, by adjusting the distance between the feed and the product channels (length of land plus channel), to obtain large values of conversion and large values of fuel utilization. It was shown that the larger pressure drops often associated with interdigitated flow fields compared to conventional serpentine flow fields were diminished by increasing the thickness of the catalyst layer. In addition, the thicker catalyst layer permitted the Pt catalyst to be spread over a greater thickness of carbon catalyst support, thereby ensuring better catalyst dispersion and improved catalyst performance.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".