Designing Microporous Layers for Electrolyzers Using Stochastic Approach

Area of Science:

• Electrochemical Engineering
• Materials Science

Background:

• Electrochemical energy conversion devices like electrolyzers are crucial for net-zero emissions but require improved performance and durability.
• Microporous layers (MPLs) enhance membrane-electrode-assembly (MEA) based electrolyzers, yet their complex fabrication and mechanisms hinder optimization.
• Experimental optimization of MPL structure is challenging due to intricate fabrication processes and unclear mechanisms.

Purpose of the Study:

• To introduce a novel stochastic model for generating 3D reconstructions of microporous layers (MPLs) for electrolyzers.
• To simulate the impact of MPL structural properties, such as porosity and particle size, on performance.
• To provide insights for designing next-generation MPLs to advance electrochemical energy conversion technologies.

Main Methods:

• Developed a stochastic model to generate 3D MPL reconstructions using porosity and particle size as inputs.
• Incorporated dilation and erosion algorithms to simulate sinter-neck formation during the sintering process.
• Generated and analyzed single-layer, pore-former containing, and bilayer MPLs using the model, followed by surface roughness analysis and pore network simulations.

Main Results:

• The stochastic model successfully generated diverse MPL structures, including single-layer, pore-former containing, and bilayer configurations.
• Surface roughness analysis and pore network simulations revealed that finer particles at higher porosities are superior to larger particles at lower porosities for MPL design.
• The model effectively captured the impact of sinter-necks on structural and transport properties of MPLs.

Conclusions:

• The stochastic model offers a powerful tool for designing and optimizing microporous layers for enhanced electrolyzer performance and durability.
• MPL design principles favoring finer particles and higher porosities are highlighted as critical for improving electrochemical energy conversion.
• This modeling approach is expected to accelerate the discovery of advanced MPLs, contributing to the widespread adoption of net-zero emission technologies.