Measurements of Permeability and Effective in-Plane Gas Diffusivity of Gas Diffusion Media Under Compression
Bibliographic record
Abstract
Mass transport is one of the key factors limiting the performance of polymer electrolyte membrane fuel cells (PEMFC). Mass transport in the gas diffusion layers occurs mainly by molecular diffusion. However, convection might also become important under some circumstances. For example, in serpentine fuel cells, convection might be important at the channel bends [1]. Knudsen diffusion might also have a small role for cases where, due to high PTFE loading and high compression, the average pore size in the GDL is reduced. An experimental set up based on a diffusion bridge has been developed to determine the in-plane permeability and effective molecular diffusivity of gas diffusion layers used in PEMFC both uncompressed and under compression. In order to estimate in-plane permeability, nitrogen is introduced in one channel and passed through the porous sample and the pressure drop is measured. In order to measure in-plane diffusivity, nitrogen and oxygen are passed in separate channels connected only by the porous media. The oxygen concentration is measured in the nitrogen channel using an oxygen sensor. Further, by applying a pressure differential between the channels the ratio of convection and diffusion is modified. In order to estimate in-plane permeability and effective molecular diffusivity from the experiments, several one-dimensional mass transport models are implemented. In this study, a combined Fick’s and Darcy’s model, and the modified binary friction models are implemented and used to estimate the permeability and effective oxygen diffusivity [2]. The experimentally measured pressure drop and the oxygen concentration at different flow rates and differential pressures are used to estimate the in-plane permeability and oxygen effective diffusivity using least square parameter estimation. Using the procedure described above, the effect of compression and PTFE loading on in-plane permeability and effective molecular diffusivity are studied. GDL Toray 090 samples with different PTFE loading, i.e. 0, 10, 20 and 40%, are tested at 4 different compression levels corresponding to a thickness of 250, 225, 200 and 175 μm. Results show that in-plane permeability varies in the range of 2.33 × 10−11 - 0.2 × 10−11 m2 , and in-plane diffusibility (ratio of effective diffusivity to molecular diffusivity) varies in the range of 0.72 – 0.18 for the selected range of compression and GDL samples. Figure 1 shows the GDL permeability for the samples with different PTFE loading at different levels of compression. Figure 2 shows the combined Fick’s and Darcy’s law model fit into the experimental data for a Toray 090 GDL sample at various levels of differential pressure between the oxygen and nitrogen channel at different levels of compression. Figure 3 shows the diffusibility for samples with different PTFE loading at different levels of compression. Results show that in-plane permeability reduces with compression and amount of PTFE in porous media while in-plane diffusivity decreases with compression due to decreasing porosity and decreases with increasing PTFE content. References [1] J. Phroah, Journal of Power Sources, 144, pp. 7782, (2005). [2] L. M. Pant, S. K. Mitra, M. Secanell, International Journal of Heat and Mass Transfer, 58, pp. 70–79, (2013).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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.
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