3D Reconstruction of Porous and Poorly Conductive Soft Materials using FIB-SEM Tomography
Licentiate thesis, 2018

Focused ion beam combined with scanning electron microscope (FIB-SEM) is a powerful tool that can be utilised to reveal the internal microstructure of materials. It basically uses ions to make cross-sections with high precision and electrons to image the cross-section surface with high spatial resolution. In addition to revealing the internal microstructure, FIB-SEM can be used to perform a sequential slice and image procedure which, after some data processing, can result in a 3D reconstruction of the microstructure, also denoted as FIB-SEM tomography. Focused ion beam tomography is a well-established procedure since 1987. It has been successfully applied to a variety of well conductive materials. However, to perform FIB-SEM tomography on ion and electron beam sensitive as well as poorly conductive soft materials is still challenging. Some of the common challenges are cross-sectioning artefacts, shadowing-effects and charging. The presence of pores adds additional challenges. Fully dense materials provide a planar cross-section while pores expose surface area beneath the planar cross-section surface as well. The sub-surface pore information and the varying intensity from the sub-surface areas give rise to intensity overlaps which complicates the data processing. Several solutions to overcome these challenges have been reported. Examples are milling and imaging at low beam energies and specimen preparations. However, the ultimate aim is to examine porous and poorly conductive soft materials as close to their original state to avoid introduction of artefacts.    
            The aim of this work was to develop a general protocol for optimisation of FIB-SEM tomography parameters for porous and poorly conductive soft materials.The optimised parameters include the energies and currents of the ion and electron beams, reduction of shadowing-effects, choice of electron detector and selection of method for charge neutralisation. In addition, a new self-learning binarisation algorithm is introduced to enable an automatic separation between pores and matrix. The binary data have been used to visualise the interconnectivity in 3D of individual pore paths through phase separated polymer films. The optimised protocol for FIB-SEM tomography is applicable to a variety of porous and poorly conductive soft materials.      
             The porous and poorly conductive soft materials in these studies were leached phase separated polymer films intended for controlled drug release coatings in pharmaceuticals. The porous microstructure within the films acts as transport path for the drug. In this work, the complex microstructure has been visualised in 3D. In addition, 3D visualisation of the shortest, intermediate and longest paths through the films, based upon tortuosity calculations, have been performed as well.

insulating material

3D

interconnectivity

focused ion beam

tomography

polymer film

scanning electron microscopy

PJ-salen
Opponent: Dr. Anders Palmquist

Author

Cecilia Fager

Chalmers, Physics, Eva Olsson Group

Soft Materials and Coatings for Controlled Drug Release Nanotechnologies in Preventive and Regenerative Medicine an Emerging Big Picture. V. Uskokovic and D. P. Uskokovic C. Fager and E. Olsson Netherlands: Elsevier. 2018, 244-259.

3D Reconstruction of Microstructure Using Optimised FIB-SEM Tomography Parameters for Porous and Poorly Conductive Soft Materials. C. Fager, M. Röding, A. Olsson, C. von Corswant, N. Lorén, A. Särkkä and E. Olsson Manuscript intended for Microscopy and Microanalysis

3D Visualisation of Individual Transport Paths in Controlled Drug Release Films using FIB-SEM Tomography C. Fager, S. E. Barman, M. Röding, A. Olsson, C. von Corswant, N. Lorén, A. Särkkä, H. Rotzén and E. Olsson Manuscript intended for International Journal of Pharmaceutics

Subject Categories

Textile, Rubber and Polymeric Materials

Materials Chemistry

Other Chemistry Topics

Publisher

Chalmers

PJ-salen

Opponent: Dr. Anders Palmquist

More information

Latest update

9/25/2018