Lattice Boltzmann Simulation of Transport Phenomena in Nanostructured Cathode Catalyst Layer for Proton Exchange Membrane Fuel Cells

2012 ◽  
Vol 1384 ◽  
Author(s):  
Christopher D. Stiles ◽  
Yongqiang Xue
Keyword(s):  
Mass Transport ◽  
Lattice Boltzmann ◽  
Proton Exchange Membrane ◽  
Catalyst Layer ◽  
Transport Processes ◽  
Proton Exchange ◽  
Pt Catalyst ◽  
Cathode Catalyst ◽  
Cathode Catalyst Layer ◽  
Exchange Membrane

ABSTRACTA multi-component, multiple-relaxation-time (MRT) lattice Boltzmann (LB) model has been employed to study transport processes in the nanostructured cathode catalyst layer of a prototype proton exchange membrane (PEM) fuel cell. The electrode consists of an array of ordered and aligned nanorods that are continuously coated with platinum (Pt). The effect of spacing between the nanorods was studied. Simulation results showed that smaller spacing in nanorods leads to lower utilization of the Pt catalyst due to O2 mass transport limitations. Results from the LB model were found to be in good agreement with the continuum model using the finite element method (FEM) with the same boundary conditions until the systems reached the O2 mass transport limited regions, where the solutions diverged.

Ionomer content effect on charge and gas transport in the cathode catalyst layer of proton-exchange membrane fuel cells

2021 ◽  
Vol 490 ◽  
pp. 229531
Author(s):  
Yurii V. Yakovlev ◽  
Yevheniia V. Lobko ◽  
Maryna Vorokhta ◽  
Jaroslava Nováková ◽  
Michal Mazur ◽  
...  
Keyword(s):  
Fuel Cells ◽  
Proton Exchange Membrane ◽  
Gas Transport ◽  
Catalyst Layer ◽  
Proton Exchange ◽  
Cathode Catalyst ◽  
Cathode Catalyst Layer ◽  
Exchange Membrane

Parametric Analysis of the Cathode Catalyst Layer of Proton Exchange Membrane Fuel Cells Using Artificial Neural Network

2011 ◽  
Author(s):  
N. Khajeh-Hosseini-Dalasm ◽  
S. Ahadian ◽  
K. Fushinobu ◽  
K. Okazaki
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Proton Exchange Membrane ◽  
Structural Parameters ◽  
Catalyst Layer ◽  
Proton Exchange ◽  
Cathode Catalyst ◽  
Cathode Catalyst Layer ◽  
Artificial Neural ◽  
Exchange Membrane

A mathematical model was developed to study the cathode catalyst layer (CL) performance of a proton exchange membrane fuel cell (PEMFC). A number of CL parameters affecting its performance are implemented into the CL agglomerate model. These parameters are: saturation and eight structural parameters, i.e., ionomer film thickness covering the agglomerate, agglomerate radius, platinum and carbon loading, membrane content, gas diffusion layer penetration content and CL thickness. An artificial neural network (ANN) approach along with statistical methods was used for modeling, prediction, and analysis of the CL performance, which is determined by activation over-potential. The ANN was constructed to develop a relationship between the named (input) parameters and activation overpotential. An statistical analysis, namely, analysis of means (ANOM) was performed on the data obtained by the trained ANN and resulted in the main effect of each input parameter, sensitivity factors of structural parameters and their mutual combination.

Sign in / Sign up

Export Citation Format

Share Document