Speaker
Description
MUMOTT is an open-source software framework [1] developed for reconstruction of Small-Angle X-ray Scattering Tensor Tomography (SASTT) data, an advanced imaging technique that enables three-dimensional characterization of nanoscale structures in complex materials such as human bone and or composite materials [2]. SASTT acquires measurements from multiple directions to reconstruct a volumetric representation of the sample, with a tensorial description of the scattering within each volume element.
Since the emergence of SASTT, about 10 years ago, our group has developed the software MUMOTT, which enables computationally efficient tomographic reconstruction of the three-dimensional reciprocal space map of each volumetric element (voxel) in a sample [3]. The software is open-source, with different pipelines for different user needs, from straightforward reconstruction workflows to more customizable, advanced analyses, and documented at https://mumott.org/. MUMOTT allows for numerically optimized, high-speed GPU-accelerated reconstructions in addition to platform-agnostic CPU-based methods.
Building on this foundation, my current work focuses on the quantitative analysis of reconstructed datasets. In particular, new algorithms are being developed to extract detailed quantitative orientational information from the tensorial scattering data, enabling deeper insights into the structural organization of materials.
In this poster, we will share key features of MUMOTT, what results can be obtained when using the software and discuss how these results can be interpreted and applied in materials characterization.
[1] Nielsen, L. C., Carlsen, M., Wang, S., Baroni, A., Tänzer, T., Liebi, M. & Erhart, P. (2025). MUMOTT: a Python package for the analysis of multi-modal tensor tomography data. J. Appl. Cryst. 58, 1834-1845.
[2] Liebi, M., Georgiadis, M., Menzel, A., Schneider, P., Kohlbrecher, J., Bunk, O. Guizar-Sicairos, M. (2015) Nanostructure surveys of macroscopic specimens by small-angle scattering tensor tomography. Nature 527, 349–352
[3] Nielsen, L.C., Erhart, P., Guizar-Sicairos, M., Liebi, M. (2023). Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures. Acta Cryst A. 79, 515-526.