The performance of electrochemical devices such as fuel cells or electrolyzers is often dictated by material properties at interfaces . Both fuel cells and electrolyzers contain interfaces between catalysts and Nafion® (DuPont), a proton conducting polymer film. To investigate the relevant interfaces between the Nafion®, catalyst layers and gas diffusion layers, it is essential to conduct 3D-characterization in the near-operando and post-operando state.
Utilizing techniques developed to study biological materials, focused ion beam (FIB) tomography of hydrated fuel cell/electrolyzer components was conducted at cryogenic temperatures using a Quorum Technologies PP3005 cryo-stage in a FIB-SEM. By combining images from several different detectors, such as the secondary electron (SE), energy selective backscattered (ESB), and in-lens detectors, different types of information could be gathered. Advanced image tracking algorithms based on the Kanade–Lucas–Tomasi (KLT) technique  were used in combination with a custom MATLAB code to register, align and crop the stack of images, and create a 3D-reconstruction.
To study materials containing low viscosity liquids like water, a custom transfer arm was also designed and built, thus enabling rapid cryo-fixation and transfer directly to the pre-cooled cryo-stage. Although the resulting tomograms provide a qualitative view of the structure of fuel cell layers, it is also possible to obtain quantitative information. For example, catalyst and pore-size distribution can be determined, as well as pore-connectivity within the catalyst layer. Ideally, the 3D-reconstructions can also be used by researchers in the simulation community as a ‘digital twin’ to simulate critical transport phenomena that dictate cell performance. The implications for improving the performance of electrochemical devices will be presented.
 L. Zielke et al., Three-dimensional morphology of the interface between micro porous layer and catalyst layer in a polymer electrolyte membrane fuel cell. RSC Adv, 6(84):80700-80705, 2016.
 Bruce D. Lucas & Takeo Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision. International Joint Conference on Artificial Intelligence, pages 674–679, 1981.
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