Abstract
Foams are found worldwide in a huge array of products, ranging from food to polyurethane foam (PU foam). However, the physics underpinning the foam formation process is not yet fully understood. A versatile and popular technique to investigate foam structure is micro X-ray computed tomography (microCT). MicroCT is a powerful, non-destructive technique for producing high quality 3D images of static objects based on a set of X-ray projections. In order to visualize the dynamics, a series of subsequent 3D images is traditionally acquired. This approach assumes the object to remain still during the acquisition of a single 3D image. However, in most dynamic imaging situations, this is only approximately valid. Therefore imaging of a fast dynamic processes such as foam formation is currently limited to synchrotron light sources as they are able to acquire a 3D image in the order of a few seconds. Unfortunately, synchrotron beamtime is very limited and experiments are typically queued for 3 to 12 months. This project will therefore focus on improving the image quality of lab-based microCT experiments of PU foam by developing, multimodal (absorption and phase data) 3D and 4D reconstruction algorithms. The key novelty lies in the use of specific prior knowledge about the foam cell shape and its material properties. On the application side my research will facilitate lab experiments and thereby greatly reduce the experiment cycle time in the industry.
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