Methoden voor 3D atomaire resolutie reconstructie van nano-samples.

Visualizing nanoparticles at 3D atomic resolution using scanning transmission electron microscopy (STEM) is challenging. Current methods have specific shortcomings: STEM ADF tomography makes it hard to resolve light atoms and distinguish different atom types, and EDX tomography adds element specificity but is too slow and of too low resolution. We aim to resolve this issue by combining multi-tilt, through-focus, STEM imaging using multiple sensor signals: ADF and iDPC. For this purpose, new algorithms need to be developed that combine all information into a single 3D reconstruction, using a combination of physical models and, e.g., machine learning techniques. In this work package, we take advantage of the availability of both iDPC and ADF data as developed in the MSCA ITN Mummering project. First, model-based approaches will be considered to improve the atomic reconstruction by simultaneously reconstructing both datasets as a single atomic reconstruction. The aim of the model-based approach is primarily to exploit the availability of both datasets. Second, deep learning will be considered to take advantage of both datasets by integrating such network in the reconstruction in order to distinguish between different elements.

Keywords:NANOMATERIALS, TOMOGRAPHY

Disciplines:Computational materials science