Feb 27, 2023 

In situ micromechanical testing for understanding deformation mechanisms: from micro pillar compression to high-throughput testing.
Dr. Subin Lee, Institute for Applied Materials, Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen
Micro-mechanical testing inherently results in a stochastic behavior as the sample dimensions diminish close to characteristic lengths, for example, average dislocation spacing. Therefore, it is highly recommended to collect large enough data for statistical analysis. The bottleneck so far mostly has been the sample preparation which is usually done by Ga+ focused-ion beam milling. Alternatively, a femtosecond pulsed laser can fabricate large amounts of samples effectively with its fast milling rate, which is 4 to 5 orders of magnitude higher compared to that of Ga+ focused ion beam. However, the side effects of femtosecond laser ablation on the microstructure of materials have not yet been fully understood. In this talk, we will present the study of the surface structure changes after femtosecond laser patterning. Their effects on the microstructure and mechanical properties of single crystal Cu will be presented.

Room: Vanadium

Mar 1, 2023 

Neuroscience and beyond: What we learned from volume imaging by focused ion beam-scanning EM
Dr. Wiebke Möbius, Max Planck Institute for Multidisciplinary Sciences-City Campus, Göttingen
Visualization of 3D architectures in cells and tissues by volume EM has become a widely applied and important technique in life science. Here we will explain which sample preparation strategies were used and how the 3D data contributed to our understanding in different research projects ranging from cell biology to neuroscience. Our applications cover cryo- as well as room temperature FIB-SEM using the Crossbeam 540. Since our main focus of research is myelin biology, we will also show examples how volume EM became indispensable to understand pathology.

Room: Chromium

Mar 2, 2023

Recent developments in AI powered X-ray Microscopy
Dr. Ben Tordoff, Head of Materials Science, ZEISS Microscopy
Artificial intelligence is finding applications throughout materials science, instrumentation and beyond. The X-Ray microscope is also distinct in its design such that resolution is not a strong function of sample size in contrast to microCT. In this talk, the application of AI to tomographic reconstruction, image denoising and scale bridging of X-Ray microscopy data will be discussed using real world examples to show the benefits encompassing throughput and image quality improvements with profound implications for correlative, multiscale imaging workflows.

Room: Copernicum