Development and implementation of robust reconstruction methods for small-angle x-ray scattering tensor tomography
Doctoral thesis, 2024
This thesis details the development of an improved theoretical framework, computational methods, and the implementation of scientific software for small-angle x-ray scattering tensor tomography.
It includes experimental and simulation work to evaluate the robustness of the method under constraints on data acquisition and to validate implications of the theory.
Small-angle x-ray scattering tensor tomography is a promising method for the study of millimeter-sized samples with anisotropic nanostructures at scales ranging from a few to several hundred nanometers.
This is accomplished by reconstructing the reciprocal space map of the sample in a volume-resolved manner.
A thorough account is given of the mathematical model and the algorithms used to carry out reconstructions from experimental data.
The performance of these algorithms is investigated through correlation studies on simulated data, demonstrating that they are robust and perform well compared to alternative approaches.
The thesis details the software package Mumott, the structure and development of which is informed by the advances within this project.
In the case of the experimental correlation study, the robustness of the tensor tomographic reconstruction methods for a typical partial data set is evaluated by comparison to the reconstruction obtained with a full data set.
The full data set was acquired by remounting the sample during acquisition.
This analysis shows that while the incompleteness of data has an appreciable adverse effect on the parts of the reconstruction, many important quantities, such as the principal orientation, mean intensity and relative anisotropy, are relatively robust.
Finally, the thesis includes one application study of the structure of the chameleon tongue, where small-angle x-ray scattering tensor tomography is used to complement other imaging methods in a way that leverages the advances in robustness and the study of complex textures detailed in the thesis.
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It includes experimental and simulation work to evaluate the robustness of the method under constraints on data acquisition and to validate implications of the theory.
Small-angle x-ray scattering tensor tomography is a promising method for the study of millimeter-sized samples with anisotropic nanostructures at scales ranging from a few to several hundred nanometers.
This is accomplished by reconstructing the reciprocal space map of the sample in a volume-resolved manner.
A thorough account is given of the mathematical model and the algorithms used to carry out reconstructions from experimental data.
The performance of these algorithms is investigated through correlation studies on simulated data, demonstrating that they are robust and perform well compared to alternative approaches.
The thesis details the software package Mumott, the structure and development of which is informed by the advances within this project.
In the case of the experimental correlation study, the robustness of the tensor tomographic reconstruction methods for a typical partial data set is evaluated by comparison to the reconstruction obtained with a full data set.
The full data set was acquired by remounting the sample during acquisition.
This analysis shows that while the incompleteness of data has an appreciable adverse effect on the parts of the reconstruction, many important quantities, such as the principal orientation, mean intensity and relative anisotropy, are relatively robust.
Finally, the thesis includes one application study of the structure of the chameleon tongue, where small-angle x-ray scattering tensor tomography is used to complement other imaging methods in a way that leverages the advances in robustness and the study of complex textures detailed in the thesis.
small-angle scattering
integral geometry
hierarchical materials
nanostructure
optimization
diffraction
tensor tomography
visualization
Author
Leonard Nielsen
Chalmers, Physics, E-commons
Included papers
Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures
Acta Crystallographica Section A: Foundations and Advances,;Vol. 79(2023)p. 515-526
Journal article
L. C. Nielsen, T. Tänzer, I. Rodriguez-Fernandez, P. Erhart, and M. Liebi, Investigating the missing wedge problem in small-angle x-ray scattering tensor tomography across real and reciprocal space
Manuscript
J. Avaro, L. C. Nielsen, C. Appel, D. Athansiadou, A. Parilli, F. Orellana, L. Davis, U. Hetzel, and M. Liebi, Structure of the Chameleon Tongue: Enabling one of the fastest movements in biology
Manuscript
L. C. Nielsen, M. Carlsen, S. Wang, A. Baroni, T. Tänzer, M. Liebi, and P. Erhart, Mumott – a Python package for tensor tomography
Manuscript
Popular science description
Swedish
SAXS-tensortomografi är en metod för att i tre dimensioner studera hur nanostrukturen ser ut, på flera längdskalor, inuti prov som är stora nog att se med blotta ögat.
Den har unika fördelar bland annat när det gäller att avgöra bland annat hur fiberliknande strukturer är riktade i tre dimensioner, inuti till exempel skelett och andra biologiska prover. Den har även tillämpningar inom utvecklandet av nya material, till exempel material som efterliknar biologiska vävnader.
Detta arbete handlar om att bättre förstå hur SAXS-tensortomografi fungerar, och att utveckla datorprogram som gör det lättare för forskare att använda tensortomografi och liknande metoder i sitt arbete.
Det ingår även en studie om strukturen inuti en kameleonttunga, som visar på SAXS-tensortomografins unika fördelar.
Den har unika fördelar bland annat när det gäller att avgöra bland annat hur fiberliknande strukturer är riktade i tre dimensioner, inuti till exempel skelett och andra biologiska prover. Den har även tillämpningar inom utvecklandet av nya material, till exempel material som efterliknar biologiska vävnader.
Detta arbete handlar om att bättre förstå hur SAXS-tensortomografi fungerar, och att utveckla datorprogram som gör det lättare för forskare att använda tensortomografi och liknande metoder i sitt arbete.
Det ingår även en studie om strukturen inuti en kameleonttunga, som visar på SAXS-tensortomografins unika fördelar.
English
Small-angle x-ray scattering tensor tomography is a method that allows the study of the nanostructure of samples which are large enough to be seen with the naked eye, in three dimensions.
It has unique advantages in terms of determining how fiber-like structures are oriented in three dimensions, in for example bone or other biological materials. There are also applications in the development of novel materials, especially materials that imitate biological tissues.
This work is about developing a better understanding of small-angle x-ray scattering tensor tomography, as well as the development of software which makes it easier for researchers to use tensor tomography in their own work.
In addition, there is a case study showcasing the application of small-angle x-ray scattering tensor tomography to a sample of chameleon tongue, for the purpose of better understanding its internal structure.
It has unique advantages in terms of determining how fiber-like structures are oriented in three dimensions, in for example bone or other biological materials. There are also applications in the development of novel materials, especially materials that imitate biological tissues.
This work is about developing a better understanding of small-angle x-ray scattering tensor tomography, as well as the development of software which makes it easier for researchers to use tensor tomography in their own work.
In addition, there is a case study showcasing the application of small-angle x-ray scattering tensor tomography to a sample of chameleon tongue, for the purpose of better understanding its internal structure.
Research Project(s)
Multi-Modal Tensor Tomography (MUMOTT)
European Commission (EC) (EC/H2020/949301), 2021-01-01 -- 2025-12-31.
SAXS- and WAXS- tensor tomography: A new tool for the analysis of multi-scale materials
Swedish Research Council (VR) (2018-04144), 2019-01-01 -- 2022-12-31.
Categorizing
Areas of Advance
Nanoscience and Nanotechnology
Materials Science
Infrastructure
C3SE (Chalmers Centre for Computational Science and Engineering)
Chalmers e-Commons
Subject Categories (SSIF 2011)
Medical Image Processing
Condensed Matter Physics
Identifiers
ISBN
978-91-8103-055-6
Other
Series
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5513
Publisher
Chalmers
Public defence
2024-05-30 13:30 -- 16:30
PJ-salen, Fysik Origo, Kemigården 1
Opponent: Lektor Stephen Hall, Lunds Universitet Institutionen för Byggvetenskaper Avdelningen för Hållfasthetslära
Related datasets
mumott – a Python library for the analysis of multi-modal tensor tomography data [dataset]
DOI: 10.5281/zenodo.7919448