Identifying Water Saturation of Various Layers in PEMFCs through EIS and X-ray Radiography
Bibliographic record
Abstract
Polymer electrolyte membrane fuel cells (PEMFCs) are a growing technology that makes use of electrochemical energy for many practical applications. Energy is converted from electrochemical to electrical and thermal energy through the process of oxygen-reduction and hydrogen-oxidation, with water as a by-product. The performance of the fuel cell is heavily influenced by the mass transport capabilities of the water produced through this electrochemical reaction [1]. In order to understand the performance of specific fuel cell builds, it is important to develop a diagnostic tool which offers an accurate depiction of the amount of liquid water in the fuel cell during operation. Two of these diagnostic tools are electronic impedance spectroscopy (EIS) and synchrotron X-ray radiography. For this study, X-ray radiography was performed at the Biomedical Imaging and Therapy Bending Magnet (05B1-1) beamline at the Canadian Light Source Inc. (Saskatoon, Canada). In order to quantify the amount of liquid water in a PEMFC during operation, X-ray radiography was applied in the through-plane direction of the cell. Using the Beer-Lambert law, the processed images allowed for the liquid water to become visible in the anode and cathode flow channels, the anode and cathode gas diffusion layers (GDLs), the microporous layers (MPLs), as well as the membrane electrode assembly (MEA) [2]. EIS was used as a non-invasive diagnostic tool in quantifying the equivalent resistances of the fuel cell. This study aims to quantify the water saturation of various layers of the fuel cell during EIS measurements, and demonstrate the role of the water saturation of each layer to the overall mass transport resistance of the fuel cell, measured through EIS. The fuel cells analyzed have varying MPL thicknesses, as well as fuel cells without MPLs, at increasing constant current densities. Nyquist plots will be discussed with relation to amount of liquid water visualized. Figure Captions Figure 1. Subtracted in-plane image of the fuel cell with 150 μm-thick MPL. The image only shows 3 flow channels of 20. Figure 2. Nyquist plot of the fuel cell observed simultaneously with x-ray radiography 1.0 A/cm2. Figure 3. Water thickness profile plot at 1.0 A/cm2, from the image in Figure 1. Labeled from left to right: Anode GDL, Anode MPL, MEA, Cathode MPL and Cathode GDL. References [1] D. Malevich, E. Halliop, B. Peppley, J. Pharoah, and K. Karan, Journal of the Electrochemical Society 156 (2) B216 – B224 (2009) [2] J. Hinebaugh, J. Lee, and A. Bazylak, Journal of Electrochemical Society 159 (12) F826-F830 (2012)
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".