Development of a Miniaturized Cell for <i>in-Situ</i> X-Ray Computed Tomographic Visualization of Membrane Degradation in PEM Water Electrolyzers
Bibliographic record
Abstract
Membrane failure is a serious safety concern that influences the operational lifetime and hydrogen production cost of the proton exchange membrane (PEM) water electrolyzer. The membrane degradation is nuanced, and the causes are multifaceted. A two-phase flow of oxygen and water is induced at the anode under a high operating current density (2-3 A cm-2). The oxygen gas crossover from the anode to the cathode occurs by convection or diffusion 1,2. The oxygen reacts at Pt active sites at the cathode and forms H2O2, which, in the presence of metal ion contaminants, forms harmful radicals that attack the side-chain of the perfluorosulfonic acid (PFSA) ionomer membrane, leading to membrane thinning via an unzipping reaction 3,4. The oxygen permeability through the membrane increases owing to membrane thinning and membrane degradation, which leads to the formation of a combustible gas mixture, causing electrolyzer shutdown. Moreover, the physical and electrochemical interface between the porous transport layer (PTL) and the catalyst-coated membrane (CCM) plays a crucial role in governing the stability of the membrane. A poorly designed PTL-CCM interface induces high ohmic and activation overpotential owing to oxygen accumulation, which in turn leads to poor reactant access by masking of catalyst reaction sites and local overheating accelerating the interface degradation. The condition further aggravates catalyst agglomeration and delamination from the membrane, resulting in local hotspot formation and possibly exacerbating local membrane degradation 5–8. The 2D visualization using a scanning electron microscope (SEM) is insufficient to capture the multifaceted cause of membrane degradation. In-situ X-ray computed tomography (XCT) is a non-destructive technique that serves as a 3D visualization tool to improve the fundamental understanding of membrane degradation 9,10. The present study aims to develop a miniaturized cell for a PEM water electrolyzer for simultaneous in-situ XCT visualization of the membrane, catalyst layers, and PTLs. The conventional PEM water electrolyzer hardware comprises a titanium bipolar plate, which attenuates X-rays, rendering it unsuitable for XCT visualization. The miniaturized cell hardware is additively manufactured and encompasses the flow fields. A platinized titanium mesh is used as a current collector that allows XCT imaging of PEM water electrolyzer components in the miniaturized cell. In-situ XCT imaging facilitates the root cause diagnosis for membrane degradation via membrane thinning and oxygen gas crossover. The beginning-of-life (BOL) performance of the miniaturized cell is evaluated at 60 °C. The commercially fabricated CCM (Ion Power Inc.) consisted of a Nafion 115 membrane with catalyst loading of 0.5 mg cm-2 Pt/C (40 wt% Pt) at cathode and 1 mg cm-2 at IrOx anode. The diffusion layers comprised a 250 µm thick platinized titanium PTL (Bekaert) at the anode and 410 µm thick carbon cloth with a microporous layer (FuelCellStore) at the cathode. A polarization curve and galvanostatic electrochemical impedance spectroscopy (GEIS) are obtained at 60 °C to determine the BOL performance of the miniaturized cell (Figure 1). Stressors for degradation are imposed to obtain a degradation mechanism of the membrane, which is based on the intertwining relationship between the membrane’s chemical/mechanical aspects and the PTL-CCM interface using the XCT visualization. Electrochemical characterizations are performed to evaluate the beginning-of-life (BOL) and end-of-life (EOL) performance of the PEM water electrolyzers, which is correlated against the observed membrane degradation mechanisms. Acknowledgments The research was supported by the National Research Council, Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, Western Economic Diversification Canada, Pacific Economic Development Canada, and Canada Research Chairs. References P. Trinke, B. Bensmann, and R. Hanke-Rauschenbach, Electrochem commun, 82, 98–102 (2017). M. Schalenbach, M. Carmo, D. L. Fritz, J. Mergel, and D. Stolten, Int J Hydrogen Energy, 38, 14921–14933 (2013). T. Sugawara, N. Kawashima, and T. N. Murakami, J Power Sources, 196, 2615–2620 (2011). T. Xie and C. A. Hayden, Polymer (Guildf), 48, 5497–5506 (2007). A. Bazarah et al., Int J Hydrogen Energy, 47, 35976–35989 (2022). D. Kulkarni et al., Appl Catal B, 308 (2022). J. T. Lang et al., Chem Rev (2022). C. Liu et al., J Electrochem Soc, 170, 034508 (2023). Y. Chen et al., J Electrochem Soc, 170, 114526 (2023). N. Kumar et al., J Electrochem Soc, 171, 074513 (2024). Figure 1
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".