Abstract
A novel procedure to optimize the 3D morphological characterization of
nanomaterials by means of high angle annular dark field
scanning‐transmission electron tomography is reported and is
successfully applied to the analysis of a metal‐ and halogen‐free
ordered mesoporous carbon material. The new method is based on a
selection of the two parameters (μ and β) which are key in the
reconstruction of tomographic series by means of total variation
minimization (TVM). The parameter‐selected TVM reconstructions obtained
using this approach clearly reveal the porous structure of the
carbon‐based material as consisting of a network of parallel, straight
channels of ≈6 nm diameter ordered in a honeycomb‐type arrangement. Such
an unusual structure cannot be retrieved from a TVM 3D reconstruction
using default reconstruction values. Moreover, segmentation and further
quantification of the optimized 3D tomographic reconstruction provide
values for different textural parameters, such as pore size distribution
and specific pore volume that match very closely with those determined
by macroscopic physisorption techniques. The approach developed can be
extended to other reconstruction models in which the final result is
influenced by parameter choice.
Original language | English |
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Article number | 2000070 |
Journal | Particle & Particle Systems Characterization |
Volume | 37 |
Issue number | 6 |
Early online date | 17 May 2020 |
DOIs | |
Publication status | Published - 9 Jun 2020 |
Keywords
- 3D characterization
- Compressed-sensing
- Mesoporous materials
- Parameters selection
- STEM-HAADF electron tomography