Stochastic Generation of Sintered Titanium Powder-Based Porous Transport Layers in Polymer Electrolyte Membrane Electrolyzers and Investigation of Structural Properties

Thursday, 5 October 2017: 14:40
National Harbor 15 (Gaylord National Resort and Convention Center)
J. K. Lee and A. Bazylak (University of Toronto)
One of the factors leading to a decrease in the efficiency of polymer electrolyte membrane (PEM) electrolyzers is the blockage of water transport pathways through the porous transport layer (PTL). The oxygen bubbles generated from the electrochemical reaction at the catalyst layer accumulate in the PTL, impeding the transport pathways and reaction sites for the reactant water (1). An improved understanding of oxygen bubble accumulation and water transport behaviour in porous transport layers is essential to reduce mass transport losses in PEM electrolyzers.


This study presents a method to stochastically generate a PTL composed of sintered titanium (Ti) powders and investigate the transport properties using pore network modeling. A microscale X-ray computed tomography (µ-CT) was performed for a sintered Ti powder PTL sample to obtain a 2D density map. The density map contains material content information, providing higher intensity at the positions with higher material content. With the density map as an input, a stochastic model of the PTL was generated by placing Ti powder particles at positions decided by the density map and a probability function until the model reached the target volume (2). Two critical parameters are considered in this model: the seeding parameter, α, and a filling radius, β. The seeding parameter controls the number of Ti powder “seeds” that act as nucleation sites. The second parameter, the filling radius, allows the model to mimic the morphology of the sintered regions. The structural properties of the stochastic model are investigated by comparing the pore size distribution, throat size distribution, and the porosity profile to the µ-CT reconstruction.


Pore network modeling is an alternative to continuum modeling for simulating transport in porous media. Pore network modeling simplifies the solution of differential equations for mass transport by treating the pore space as a network of pores and narrow throats (3). Using pore network modeling as the analysis tool, the in-plane permeabilities of the µ-CT reconstruction and the stochastic model were compared.


The stochastic modeling of PTLs will facilitate the detailed parametric studies of PTL structural property impacts on transport and provide novel insights into mass transport behavior in PEM electrolyzers.


  1. H. Ito, T. Maeda, A. Nakano, Y. Hasegawa, N. Yokoi, C. M. Hwang, M. Ishida, A. Kato, and T. Yoshida, International journal of hydrogen energy 35(18), 9550-9560 (2010).
  1. A. Ebrahimi Khabbazi, J. Hinebaugh, A. Bazylak, Science Bulletin, 61(8), 601-611(2016).
  2. A. Putz, J. Hinebaugh, M. Aghighi, H. Day, A. Bazylak, and J. T. Gostick, ECS Transactions, 58(1), 79-86 (2013).