Characterization and modeling of nanoporous carbon structures

Abstract

The aim of the work presented here is to optimize nanoporous carbon materials by means of 'virtual material design'. On this length scale (~ 10nm) Focused Ion Beam – Scanning Electron Microscopy Nanotomography (FIB-SEM) is the only imaging technique providing three dimensional geometric information. Yet, for the optimization, the pore space of the materials must be reconstructed from the resulting image data, which was a generally unsolved problem so far.To overcome this problem, a simulation method for FIB-SEM images was developed. The resulting synthetic FIB-SEM images could then be used to test and validate segmentation algorithms. Using simulated image data, a new algorithm for the morphological segmentation of the highly porous structures from FIB-SEM data was developed, enabling the reconstruction of the three dimensional pore space from FIB-SEM images.Two case studies with nanoporous carbons used for energy storage are presented, using the new techniques for the characterization and optimization of electrodes of Li-ion batteries and electric double layer capacitors (EDLC's), respectively. The reconstructed pore space is modeled geometrically by means of stochastic geometry. Finally, the electrical properties of the materials were simulated using both imaged real and modeled structures.