Premium
Optimization of STEM‐HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization‐Based Algorithms
Author(s) -
MuñozOcaña Juan M.,
Bouziane Ainouna,
Sakina Farzeen,
Baker Richard T.,
Hungría Ana B.,
Calvino Jose J.,
RodríguezChía Antonio M.,
LópezHaro Miguel
Publication year - 2020
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.202000070
Subject(s) - electron tomography , materials science , algorithm , tomography , biological system , characterization (materials science) , computer science , optics , nanotechnology , scanning transmission electron microscopy , physics , transmission electron microscopy , biology
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.