Understanding how the composition, microstructure, and spatial distribution of the phases in fuel cell catalyst layers (carbon support, metal catalyst, ionomer and pores) affect the fuel cell performance and degradation is of crucial importance. This can only be achieved if the correlation between microstructural and compositional parameters, layer properties and performance are systematically investigated. Even though imaging using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) is typically performed for failure analysis of the catalyst layers to provide information on layer thickness changes, delamination, defects, pin-holes, Pt particles size distribution, etc., there are rarely attempts to systematically quantify microscopy and spectroscopy data and use it to correlate the microstructural and compositional parameters to the layers’ properties and performance. Recently advanced 3D imaging techniques such as electron tomography (ET), focused ion beam scanning electron microscopy (FIB-SEM), X-ray computed tomography (x-CT), and fast scanning transmission electron microscopy with energy dispersive spectroscopy (STEM-EDS) have been employed to provide answers on spatial morphology of the catalyst layers and compositional changes. These techniques show immense promise in providing valuable information from the nano- to macro-scale to understand phenomena underlying fuel cell operation and degradation. Still, utilization of the obtained 3D data sets to provide practical and useful microstructural and compositional parameters requires efforts and further development in data processing, quantification and mathematical analysis.

In this work, we are presenting a comprehensive approach for 2D and 3D imaging and quantification of fuel cell electrodes, at several scales, and the correlation to their properties and performance:

2D imaging and analysis of catalyst layers (beginning of life and end of life) using STEM-EDS will be presented with a novel, practical approach to quantify a number of parameters, such as Pt loading, loss and distribution, ionomer loading and I/C ratio, layer porosity, and oxygen evolution reaction (OER) agglomerate size. The method enables 2D visualization of component distribution at a whole layer scale, as well as at an agglomerate scale. Quantification of changes after degradation of fuel cells offers very valuable learning about possible processes occurring during degradation - information that was not available until now. Challenges with the method and potential development will be presented as well.

3D imaging and quantification of catalyst powders and catalyst layers on multiple scales will be presented, correlatively utilizing ET, FIB-SEM, and x-CT microscopy. Spatial distribution of all phases – Pt catalyst, carbon support, ionomer and pores will be revealed. A number of microstructural parameters will be quantified from the 3D data sets. Direct numerical simulation of the 3D data sets to obtain effective transport properties such as electrical and thermal conductivity, and gas diffusivity will also be reported. The approach shows promise for improved modeling, design and optimization of the fuel cell catalyst layers.

Finally, the talk will conclude with the new capabilities and possible prospects for advanced imaging and quantification for further fuel cell development and commercialization.