Electrochemical energy conversion devices, such as water
and carbon
dioxide electrolyzers, offer significant advantages in achieving net-zero
emissions and in mitigating further increases in global temperature.
However, their widespread adoption necessitates enhancements in performance
and durability. Microporous layers (MPLs) have been gaining attention
as a promising means to enhance the performance and durability of
membrane-electrode-assembly (MEA) based electrolyzers, but their nontrivial
mechanisms and complexity in fabrication pose challenges for optimizing
the microporous layer structure experimentally. This study introduces
a stochastic model for generating MPLs in application to electrolyzers.
The model produces 3D reconstructions of MPLs, with porosity and particle
size as input parameters, and is capable of generating biased MPLs
by taking the pre-existing 3D reconstruction as an input. The model
applies a dilation and erosion algorithm to replicate sinter-necks
formed in the MPL during the sintering process, and captures their
impact on structural and transport properties. In this work, three
types of MPLs are generated by using the presented model, which include
single-layer MPLs, MPLs with pore formers, and bilayer MPLs. Surface
roughness analysis and pore network simulations on the MPLs highlight
the significance of particle size in the MPL design. Using finer particles
at higher porosities are favored over using larger particles at lower
porosities. Such findings are examples of the valuable insights offered
from the presented stochastic model, and the model will guide seminal
discovery of next-generation MPLs that will greatly progress the shift
toward net-zero electrochemical energy conversion technologies.