Abstract
Polymer electrolyte water electrolyzer (PEWE) is one of the most appealing options to produce hydrogen and oxygen from renewable resources[1]. Understanding the relationships between porous transport layer (PTL) morphology and oxygen removal is essential to improve the cell performance of PEWE. In order to probe this more fully, operando x-ray computed tomography (CT)[2], machine learning, and LBM simulation[3] were performed on a model electrolyzer at different water flowrates and current densities to determine how these operating conditions alter oxygen transport in the PTLs. X-ray CT was employed to create 3D images (Figure 1A) and visualize oxygen content in the model electrolyzer (Figure 1C and 1D). Machine learning was used to quantify the oxygen content in the electrolyzer geometry, as well as any pathways or patterns the oxygen took as it exited the electrolyzer through the PTL. Computational fluid dynamics (CFD) was used to investigate the characteristics of oxygen transport in the PTL under different operating conditions.
Our work has demonstrated new findings in oxygen transport behavior in the PTL. We report a direct observation of oxygen taking preferential pathways through the PTL regardless of the water flowrate or current density (1-4 A/cm2). The spatially periodic oxygen front has been observed in this study for the first time. Oxygen distribution in the PTL had a periodic behavior with period of 400 μm[4]. CFD model was used to predict oxygen distribution in the PTL showing periodic oxygen front. Observed oxygen distribution is due to low in-plane PTL tortuosity and high porosity enabling merging of oxygen bubbles in the middle of the PTL and also due to aerophobicity of the layer. A conceptual schematic showing transport of oxygen in the PTL is shown in Figure 1B. Once the transport pathway through the thickness of the PTL is established, oxygen bubbles will preferentially follow the pathway and no new pathways will be introduced within the current densities range studied here. These findings should be useful in improving mass transport and enhancing our understanding of processes in PEWE.
References:
[1] U. Babic, M. Suermann, F. N. Büchi, L. Gubler, and T. J. Schmidt, "Critical Review—Identifying Critical Gaps for Polymer Electrolyte Water Electrolysis Development," J. Electrochem. Soc., vol. 164, no. 4, pp. F387–F399, 2017, doi: 10.1149/2.1441704jes.
[2] D. Kulkarni, S. J. Normile, L. G. Connolly, and I. V Zenyuk, " Development of low temperature fuel cell holders for Operando x-ray micro and nano computed tomography to visualize water distribution ," J. Phys. Energy, vol. 2, no. 4, p. 044005, 2020, doi: 10.1088/2515-7655/abb783.
[3] P. Satjaritanun, S. Hirano, I. V. Zenyuk, J. W. Weidner, N. Tippayawong, and S. Shimpalee, "Numerical Study of Electrochemical Kinetics and Mass Transport inside Nano-Structural Catalyst Layer of PEMFC Using Lattice Boltzmann Agglomeration Method," J. Electrochem. Soc., vol. 167, no. 1, p. 013516, 2020, doi: 10.1149/2.0162001jes.
[4] P. Satjaritanun, M. O'Brien, D. Kulkarni, S. Shimpalee, C. Capuano, K. E. Ayers, N. Danilovic, D. Y. Parkinson, and I. V. Zenyuk, "Observation of Preferential Pathways for Oxygen Removal through Porous Transport Layers of Polymer Electrolyte Water Electrolyzers," iScience, vol. 23, no. 12, p. 101783, 2020, doi: 10.1016/j.isci.2020.101783.
Figure 1