Electrochemical and electrocatalytic processes are of key importance for the transition to a
sustainable energy supply as well as for a wide variety of other technologically relevant …

The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed
an enormous amount of research in the scientific community. It has proven to be a powerful …

Holographic imaging poses the ill posed inverse mapping problem of retrieving complex
amplitude maps from measured diffraction intensity patterns. The existing deep learning …

X-ray diffraction (XRD) is a proven, powerful technique for determining the phase
composition, structure, and microstructural features of crystalline materials. The use of …

Coherent imaging techniques provide an unparalleled multi-scale view of materials across
scientific and technological fields, from structural materials to quantum devices, from …

Multimodal hard X-ray scanning probe microscopy has been extensively used to study
functional materials providing multiple contrast mechanisms. For instance, combining …

With the success of deep learning methods in many image processing tasks, deep learning
approaches have also been introduced to the phase retrieval problem recently. These …

Conventional deep learning-based image reconstruction methods require a large amount of
training data, which can be hard to obtain in practice. Untrained deep learning methods …

Phase retrieval (PR) concerns the recovery of complex phases from complex magnitudes.
We identify the connection between the difficulty level and the number and variety of …

Understanding and interpreting dynamics of functional materials in situ is a grand challenge
in physics and materials science due to the difficulty of experimentally probing materials at …