Turing-Patterned Catalyst-Ionomer Architectures for Enhanced Mass Transport in Anion Exchange Membrane Fuel Cells

Area of Science:

• Materials Science
• Electrochemistry
• Chemical Engineering

Background:

• Anion exchange membrane fuel cells (AEMFCs) are crucial for clean energy, but their catalyst layers (CLs) struggle with stability under varying humidity.
• Conventional CLs have ionomers randomly distributed, causing transport issues and limiting the triple-phase interface effectiveness.

Purpose of the Study:

• To develop a molecular engineering strategy for creating advanced CLs with improved environmental adaptability and performance for AEMFCs.
• To address the limitations of conventional ionomer distribution in CLs for enhanced fuel cell operation.

Main Methods:

• Utilized a molecular engineering strategy involving precisely controlled cross-linking chemistry to construct Turing-patterned ionomer networks.
• Employed advanced microstructural characterization techniques, including transmission electron microscopy (TEM) and atomic force microscopy (AFM).
• Combined theoretical modeling and electrochemical diagnostics to analyze transport properties and performance.

Main Results:

• Successfully formed a pendant-cross-linked architecture with periodic nanochannels (∼8 nm width) exhibiting enhanced ion, water, and O2 transport.
• Demonstrated reduced mass transport resistance and improved single-cell durability compared to conventional CLs.
• Achieved a record-high peak power density of 1.39 W cm⁻² under low relative humidity conditions.

Conclusions:

• The Turing-patterned ionomer network offers a promising solution for enhancing AEMFC operational stability and performance, particularly under low-humidity conditions.
• This engineered CL architecture effectively overcomes transport bottlenecks, paving the way for more efficient and durable AEMFCs.