Abstract
The development of novel platinum group metal (PGM)-free catalysts is a challenging task, particularly when coupled with the integration into a cathode catalyst layer (CCL). The optimization of such PGM-free electrode structures is often non-linear and iterative, making it a demanding task due to the high number of parameters that affect performance. To accelerate both materials discovery and electrode development, this work demonstrates the application of a high-resolution segmented cell (SC) with 121 segments of 0.413 cm2 size for combinatorial high-throughput PGM-free catalyst screening and CCL optimization. The approach utilizes three flow-field strips with active areas of 4.45 cm2 each, distributed over 11 segments. Electrodes with identical catalyst material and fabrication method result in reproducible data with typically less than 10% variation between each segment and match in performance with differential single cell data. High throughput testing of combinatorial sample sets, with varied PGM-free electrocatalyst materials or electrode composition, demonstrated the ability to rapidly discern high performing outliers, and establish or confirm trends in electrode optimization. The results indicated significant performance benefits of electrodes with ionomer content of 45 wt% over lower values, and of water rich inks with 82% water content over those with 50%.
Original language | American English |
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Article number | Article No. 227829 |
Number of pages | 12 |
Journal | Journal of Power Sources |
Volume | 452 |
DOIs | |
State | Published - 15 Mar 2020 |
Bibliographical note
Publisher Copyright:© 2020 Elsevier B.V.
NREL Publication Number
- NREL/JA-5900-76033
Keywords
- Combinatorial test
- Conditioning
- Electrode layer
- Non-noble metal catalyst
- Optimization
- Segmented fuel cell