IAS-9 Receives Project Funding through the Helmholtz Imaging Project Call 2023

We are pleased to announce exciting news from our research group "Data Analysis and Machine Learning": we have successfully obtained funding through the Helmholtz Imaging Projects for our project in the field of imaging and data science, called "Deep-learning assisted fast in situ 4D electron microscope imaging" (FAST-EMI). This collaborative initiative, led by two experts from the KIT and Forschungszentrum Jülich (FZJ), namely Prof. Christoph Kirchlechner (Institute for Applied Materials – Mechanics of Materials and Interfaces (IAM-MMI)), and Prof. Stefan Sandfeld (Institute for Advanced Simulation - Materials Data Science and Informatics (IAS-9)), aims to advance our comprehension of the degradation mechanisms affecting functional materials. This will be achieved by integrating advanced electron microscope imaging techniques with deep learning (DL).

The primary focus of the project is to understand the behavior of dislocations, which play a critical role in the degradation of functional materials exposed to mechanical stress. While traditional transmission electron microscopy (TEM) provides invaluable data, it is limited by sample size and in-situ testing capabilities. On the other hand, scanning electron microscopy (SEM) offers a larger specimen chamber and more flexibilities for in situ facilities, however encounters challenges when it comes to effectively capturing dislocations and deformation mechanisms at the micro-/nano-scale.

To overcome these obstacles, our team will develop in situ 4D-STEM-in-SEM imaging, taking full advantage of advanced DL techniques such as feature detection and adaptive scanning. With successful outcomes, we envision the potential expansion of this project into various research domains, encompassing the exploration of degradation mechanisms in the field of energy materials and beyond.

About Helmholtz Imaging Projects

The objective of this call for Helmholtz Imaging Projects is to initiate and facilitate activities that address challenges and methods across research fields and centers; special emphasis for Helmholtz Imaging Projects is laid on developing innovative approaches, which tackle imaging problems. Such projects often are characterized by higher risk and will therefore have demonstration character. Thus, Helmholtz Imaging will provide seed funding for new ideas and aims at collaborative projects with the potential to facilitate collaborations in a larger context.

Helmholtz Imaging Project combines two characteristic goals:

• to promote imaging science by innovative approaches in information & data science and synergies across imaging modalities and applications, and
• to foster cross-disciplinary research interaction and method transfer between applications and research fields (across Helmholtz research fields) and sectors (with industry or other partners).

More information can be found on the webpages of Helmholtz Imaging.