1650
(Invited) Three-Dimensional Analysis of Electrode Structures

Wednesday, 4 October 2017: 14:30
National Harbor 15 (Gaylord National Resort and Convention Center)
K. Artyushkova, M. Hossen (University of New Mexico), A. Serov (Pajarito Powder LLC), P. Atanassov (University of New Mexico), C. Capuano, N. Danilovic, and K. E. Ayers (Proton OnSite)
Chemical integrity and pore structure, and hence, the effectiveness of the electrode structures, must be preserved over electrolyzer lifetime. The visualization and quantification of morphological properties of electrode structures are crucial for the development of active and durable devices as the accessibility of active sites by reactants and removal of products is controlled by morphological properties of electrodes.

A three-dimensional reconstruction of electrodes is effectively investigated using the focused ion beam-secondary electron microscope (FIB/SEM), providing critical information on three-dimensional morphology. In last decade, FIB-SEM tomography has emerged as a valuable tool, providing 3D structures with a spatial resolution between 10 and 1000 nm.

In this talk, several approaches for extracting morphological information from 2D and 3D images and volumes obtained from electrode structures will be discussed. Large area cross-sections milled by ion beam can be analyzed by a statistically large number of 2D images for comparison of electrode structures made from different catalyst-ionomer configurations and for post-test analysis for degradation studies. Three-dimensional volumes of the electrodes can be obtained by FIB-SEM tomography. Finally, FIB lift-out can be used to create thin cross-sections for further high-resolution TEM analysis.

Extracting useful information from the 3D representation of materials has been approached differently in the past. The most common approach for quantifying the pore size distribution of these materials is based on idealizing the void space as a series of connected spheres.1 While these approaches are useful for the estimation of some transport properties, the direct estimation of structural metrics and their spatial variation is overlooked.2

In this talk, an alternative approach based on digital image processing of 2D and 3D imaging data will be presented. Useful information from the 2D and 3D representation of electrodes will be extracted by calculating key structural parameters such as overall roughness, porosity, tortuosity, connectivity, average solid phase size and average pore size.3,4 It is important to evaluate these key parameters at different spatial scales as these may be related to different phenomena contributing to transport. This analysis can be achieved by splitting up original imaging data into two parts, representing high-frequency and low-frequency components, through a filtering procedure.

Figure 1 displays large area SEM images obtained from two electrode samples before and after electrochemical testing, along with average pore size and average solid phase size obtained from processing high-resolution SEM images shown in the inset. Very different changes in morphologies are observed between the two samples. For the first electrode structure, smaller pore sizes and smaller solid phase size were observed after the test. Loss of porosity is also observed due to the collapse of the electrode. For the second electrode, the porosity increased after testing, with growth of the pore size and solid phase size.

1. H. Schulenburg, B. Schwanitz, N. Linse, G. G. Scherer, A. Wokaun, J. Krbanjevic, R. Grothausmann and I. Manke, The Journal of Physical Chemistry C, 2011, 115, 14236-14243.

2. A. Çeçen, E. A. Wargo, A. C. Hanna, D. M. Turner, S. R. Kalidindi and E. C. Kumbur, Journal of The Electrochemical Society, 2012, 159, B299-B307.

3. S. Stariha, K. Artyushkova, M. J. Workman, A. Serov, S. McKinney, B. Halevi and P. Atanassov, Journal of Power Sources, 2016, 326, 43-49.

4. A. Serov, M. J. Workman, K. Artyushkova, P. Atanassov, G. McCool, S. McKinney, H. Romero, B. Halevi and T. Stephenson, Journal of Power Sources, 2016, 327, 557-564.