Application of Artificial Intelligence inside the Scanning Electron Microscope for Accelerated High-Resolution in-situ Testing (T02#)

• Subject Area: Thermodynamics and Kinetics as well as Properties of Phases and Microstructure of Materials
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 278868966

The aim of microstructural characterisation of damage within TRR 188 is to unravel the physical mechanisms of damage nucleation, evolution and coalescence. Of interest in this context are in particular the dependence of these mechanisms on the loading conditions and path as well the often complex microstructures of advanced alloys with their multiple phases. In the corresponding project within TRR 188 (Project B02), a new method has been developed to allow for the first time an automated analysis of damage mechanisms using panoramic (~1 cm²) scanning electron microscopy images at high resolution. This was achieved using artificial intelligence with convolutional neural networks and applied to post-mortem and in-situ deformation tests as well as uniaxial and biaxial tensile andbending tests.Based on this, the aim of this transfer project is to exploit the potential of the new method further and make it available to TRR 188 and the scientific community by achieving integration into accessible experimental setups. In this project, this will be pursued in three ways: by (1) implementing accelerated in-situ deformation experiments based on initial imaging and subsequent fast tracking of many evolving damage sites, (2) applying the new concepts of super-resolution in artificial intelligence for fast re-imaging of large areas and (3) direct collaboration with a microscope manufacturer to achieve reliable and comfortable integration of the accelerated in-situ experiment.

• DFG Programme: CRC/Transregios (Transfer Project)
• Subproject of: TRR 188: Damage Controlled Forming Processes
• Applicant Institution: Rheinisch-Westfälische Technische Hochschule Aachen
• Business and Industry: Tescan GmbH
• Participating Institution: IU Internationale Hochschule GmbH
• Project Head: Professorin Sandra Korte-Kerzel, Ph.D.