Contact and Performance of Low Anode Loading CCMs for PEM Water Electrolysis at Different Clamping Pressures
Bibliographic record
Abstract
Reducing the anodic loading of the catalyst-coated membrane (CCM) is necessary for upscaling low-cost PEM electrolyzers. Various studies show that good cell performance is attainable with low-loading CCMs. 1 For this, effective electrical contact between the anodic porous transport layer and CCM is necessary to increase CCM utilization, as electric in-plane conduction inside the catalyst layer is reduced. 2, 3 The cell clamping pressure and mechanical pressure distribution affect the electric contact between the anodic porous transport layer and the catalyst layer. 4 The impact of the cell clamping pressure on low-loading CCMs is shown in this work. Anodic loadings of the CCM, varied down to 0.11 mg/cm², are electrochemically characterized, with particular emphasis on the effects of varying clamping pressure. Also, different porous transport layers and flow fields are applied to study the impact of the cell setup on the overall cell performance. The clamping pressure is gradually increased from 1 MPa to 6 MPa and post mortem SEM images are recorded. A 2D CCM model is used to explain the results from the electrochemical characterization. Both kinetic and ohmic losses are affected by the IrOx-loading. The exchange current density varies with the loading but appears to be relatively insensitive to the clamping pressure. The HFR, on the other hand, appears to be higher and more sensitive to the clamping pressure with decreased loadings (Fig. 1a). Increased HFR values can be explained by inhomogeneous CCM utilization, mostly due to low electric in-plane aCL conductivity. References [1] C. Wang, K. Lee, C. P. Liu, D. Kulkarni, P. Atanassov, X. Peng and I. V. Zenyuk, International Materials Reviews, 69 (1), 3–18 (2024). [2] E. Padgett, G. Bender, A. Haug, K. Lewinski, F. Sun, H. Yu, D. A. Cullen, A. J. Steinbach and S. M. Alia, J. Electrochem. Soc., 170 (8), 84512 (2023). [3] M. F. Ernst, V. Meier, M. Kornherr and H. A. Gasteiger, J. Electrochem. Soc., 171 (7), 74511 (2024). [4] A. Martin, P. Trinke, M. Stähler, A. Stähler, F. Scheepers, B. Bensmann, M. Carmo, W. Lehnert and R. Hanke-Rauschenbach, J. Electrochem. Soc., 169 (1), 14502 (2022). The authors gratefully acknowledge funding by BMBF in the framework of project DERIEL, FKZ 03HY122G, and NEO-PEM-KLX, FKZ 03SF0762A, as well as André Koch and the Solar Energy Research Hamelin (ISFH) for recording the SEM images. 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".