Quantitative Analysis of Mesoporous Structures by Electron Tomography: A Phantom Study

DOI

Electron tomography (ET) has attracted significant attention for a quantitative analysis of mesoporous materials, especially for complex disordered pore structures, as no priori assumptions on the pore shape is needed, which is normally inevitable when using traditional bulk characterization techniques. However, a reliable quantification of such pore structure from ET highly depends on the fidelity of segmented reconstruction, which can be significantly affected, e.g. by the raw data quality, the limited tilting range, artifacts introduced during alignment and further depends the reconstruction algorithm. Therefore, we systematically investigate the reconstruction reliability of three main-stream algorithms including simultaneous iterative reconstruction technique (SIRT), total variation minimization (TVM) and discrete algebraic reconstruction technique (DART) for mesoporous materials using different imperfect (realistic) tilt-series based on a set of phantom simulations. We found that DART outperforms the other two methods in reliably revealing small pores and narrow channels, especially when the number of projections is strongly constrained. The accurate segmented reconstruction from DART makes it possible to achieve reliable quantification of pores structure, which in turn leads to reliable evaluation of effective diffusion coefficients. We discuss the influence of different acquisition and reconstruction parameters on the reconstructed 3D volume and the quantitative analysis of pore features. We aim to provide a practical guideline for optimizing acquisition and reconstruction parameters and how to evaluate the accuracy when describing the mesoporous structure.

Original raw data and analysis of 2D and 3D reconstruction based on phantoms. Detailed descriptions of the file types and the data are stored in a separate description.txt file.

Identifier
DOI https://doi.org/10.35097/1437
Metadata Access https://www.radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=datacite&identifier=10.35097/1437
Provenance
Creator Huang, Xiaohui; Wang, Di ORCID logo; Kübel, Christian ORCID logo; Hlushkou, Dzmitry; Tallarek, Ulrich
Publisher Karlsruhe Institute of Technology
Contributor RADAR
Publication Year 2023
Rights Open Access; Creative Commons Attribution Non Commercial Share Alike 4.0 International; info:eu-repo/semantics/openAccess; https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
OpenAccess true
Representation
Resource Type Dataset
Format application/x-tar
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences