Investigation of porous transport layer parameters for proton exchange membrane water electrolysis

TitleInvestigation of porous transport layer parameters for proton exchange membrane water electrolysis
Publication TypePresentation
Year of Publication2019
AuthorsKang Z, Alia SM, Young JL, Bender G
  1. Presentation
  2. Title
    Investigation of porous transport layer parameters for proton exchange membrane water electrolysis
  3. Presenter
    Zhenye Kang
  4. Contributor
    Shaun M. Alia
  5. Contributor
    James L. Young
  6. Contributor
    Guido Bender
  7. Type
  8. Date
  9. Place
    Hilton Atlanta, Atlanta, GA, USA
  10. Meeting Name
    236th ECS Meeting
  11. Date Added
    11/6/2019, 10:47:45 AM
  12. Date Modified
    12/6/2019, 1:28:14 PM

Published on October 17th, 2019 Hydrogen production through proton exchange membrane water electrolysis (PEMWE) is regarded as a very promising technology that offers a highly efficient and robust path to store electrical energy in form of hydrogen and further enables the integration of renewable energy into the electrical grid 1-3. The total cell voltage of a single PEM water electrolyzer cell is composed of the open circuit voltage, activation overpotential, diffusion overpotential, and ohmic loss overpotential 4. The total voltage of the cell can be expressed as Eq(1) 5. V=V_OCV+V_act+V_ohm+V_diff (1) Where V_OCV is the Nernst potential which is also called the reversible voltage and can be calculated from the Nernst equation or Gibbs free energy, V_act is the activation overpotential due to the electrochemical reaction and it represents the overpotential to drive the electron transfer and electrochemical reaction kinetics as described by the Butler-Volmer model, V_ohm is the ohmic overpotential caused by the resistances of the electronic/ionic components and interfacial contact resistances, and V_diff is the diffusion overpotential related to mass transport. Porous transport layers (PTLs) are key components in PEMWE. They facilitate mass transport, thermal and electrical conduction, and are required to sustain a good contact with adjacent components 6-8. It is expected that various PTLs with different structures and wettability exhibit nonidentical performance in PEMWE. In this study, a general model is established to investigate the PTL parameters of four inherently different PTLs, including non-treated Toray paper, PTFE treated Toray paper, sintered titanium particles and Ti felt. SEM images highlighting the structures of these PTL materials are shown in Figure 1. The materials, which differed in thickness, porosity, material and composition were evaluated with identical MEAs over a range of operating conditions for model validation. The resulting data indicate that the hydrophobic additives in the Toray paper will decrease the PEMWE performance due to increased mass transport loss and ohmic loss. Ti felt with similar thickness and porosity as non-treated Toray paper showed slightly reduced performance due to its higher ohmic loss. Sintered Ti particle PTLs exhibit much higher ohmic resistance than Ti felt and nontreated Toray paper, which may be attributed to its significantly larger thickness and/or an increased contact resistance. The experimental data was employed to validate the MATLAB/Simulink model which enables the simulation of the contribution of each overpotential. The model was used to successfully describe the effects of PTFE loading on PEMWE performance, as shown in Figure 2. The hydrophobic treatment resulted, as expected, in detrimental performance effects. The diffusion loss of a 20% PTFE treated Toray paper is significantly higher than that of the nontreated PTLs (Figure 2). The modeling results also indicate that the change of the wettability of the PTLs by hydrophobic additives/agents, impacted not only the diffusion loss significantly, but also affected the ohmic loss and activation loss. This was specifically detrimental to PEMWE cell performance when operating at high current densities. The model that was validated in this study can be used to predict the effects of key PTL parameters and utilized to optimize PEMWE performance.