Quantification of artifacts in scanning electron microscopy tomography: Improving the reliability of calculated transport parameters in energy applications such as fuel cell and battery electrodes

Abstract

Focused ion beam and scanning electron microscopy tomography (FIB-SEMt) is commonly used to extract reactant transport relevant parameters from nano-porous materials in energy applications, such as fuel cells or batteries. Here we present an approach to virtually model the errors in FIB-SEMt which are caused by the FIB cutting distance. The errors are evaluated in terms of connectivity, solid volume fraction (SVF), conductivity, diffusivity, as well as mean grain and pore sizes. For state-of-the-art FIB-SEMt experiments, where a hydrogen fuel cell catalyst layer with 60 nm mean grain size and 40% SVF is sectioned with a cutting distance of 15 nm, the error in our simulation ranges up to 51% (conductivity), whereas other parameters remain largely unaffected (Laplace diffusivity, 4%). We further present a method, employing virtual coarsening and back interpolation, to reduce FIB cutting distance errors in all investigated parameters. Both error evaluation and correction are applicable to sphere based porous materials with relevance for the energy conversion and storage sector such as polymer electrolyte membrane fuel cell catalyst layer (PEMFC CL), battery carbon binder domain (CBD) or supercapacitor electrodes.