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Understanding nanomagnetism from all angles: Developments in magnetic electron tomography



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This thesis aims to develop transmission electron microscopy (TEM) techniques to study magnetic nanomaterials in three dimensions (3D). At the nanoscale, magnetic materials exhibit various intriguing behaviours such as topological protection in skyrmions (which may be used in next-generation computers), vortex states in nanorings (which are being developed to treat cancer), and long-term stability in paleomagnetic samples (which allow researchers to study the formation of planetary bodies in the solar system). Many of these behaviours are intrinsically 3D in nature, and so a 3D characterisation method is required to fully understand them. This thesis explores how magnetic imaging in the TEM can be combined with electron tomography to provide a tool for studying magnetic nanomaterials in 3D.

The thesis begins by introducing the motivation, theory, and background literature relevant to magnetic electron tomography. This is then followed by a detailed study on magnetite nanorings which showcases the types of insights that can be gained through 3D magnetic imaging. Following this, it is demonstrated how prior knowledge about magnetic fields can be used to improve magnetic electron tomography experiments both through improvements to the data acquisition process as well as through changes to the data reconstruction process. At the end of the thesis, the individual strands of prior knowledge, electron tomography, and image analysis are applied independently to different projects in a section which showcases how magnetic electron tomography is intricately interconnected with the development of complementary research fields. Taken together, the content of this thesis contributes towards the maturing of magnetic electron tomography as a powerful technique for understanding magnetic nanomaterials in 3D.





Midgley, Paul
Ringe, Emilie


electron microscopy, tomography, algorithms, nanomagnetism, 3D imaging, TEM, image analysis, nanoscience, inverse reconstruction, compressed sensing


Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge
EPSRC (2123945)
Engineering and Physical Sciences Research Council (EP/L015978/1)