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MUltiscale, Multimodal and Multidimensional imaging for EngineeRING

Periodic Reporting for period 2 - MUMMERING (MUltiscale, Multimodal and Multidimensional imaging for EngineeRING)

Reporting period: 2020-01-01 to 2022-06-30

The overarching goal of MUMMERING is to create a research tool that encompasses the wealth of new 3D imaging modalities that are surging forward for applications in materials engineering, and to create a doctoral programme that trains 15 early stage researchers (ESRs) in this tool. This is urgently needed to prevent that massive amounts of valuable 3D imaging data ends on a virtual scrapheap. The challenge of handling and analysing terabytes of 3D data is already limiting the level of scientific insight that is extracted from many data sets. With faster acquisition times and multidimensional modalities, these challenges will soon scale to the petabyte regime. To meet this challenge, we will create an open access, open source platform that transparently and efficiently handles the complete workflow from data acquisition, over reconstruction and segmentation to physical modelling, including temporal models, i.e. 3D “movies”. We consider it essential to reach this final step without compromising scientific standards if 3D imaging is to become a pervasive research tool in the visions for Industry 4.0.
The 15 ESRs have been enrolled in an intensive network-wide doctoral training programme that covers all aspects of 3D imaging and will benefit from a varied track of intersectoral secondments that will challenge and broaden their scope and approach to research. The ESRs will exit the MUMMERING network as highly attractive and employable PhDs with a practical and qualified take on industrial research.

3D imaging technologies, such as X-ray or electron CT enable visualization and quantification of the internal micro-structure of objects. In brief, in 3D computed tomography (CT) an X-ray or electron source is used to acquire projection images from many different angles. Next, a computer reconstructs a 3D volume that can be used for further quantitative analysis and modelling. Probably, X-ray CT is best known from its clinical application in the hospital, but through a variety of other industrial applications CT technology affects our daily lives:
• Materials science and industrial R&D typically use both electron and X-ray CT to probe the structure of materials’ at the micro- to nanometer or even atomic scale. By relating the structure of materials to their mechanical-physical behaviour, materials with optimized performance are engineered. The range of applications of CT is very wide and covers sectors as diverse as chemical (polymer) industry, semi-conductor industry, geology (and oil) research, agrofood industry and advanced manufacturing applications.

Taken together, 3D imaging and analysis is an important aspect of our European knowledge-based economy and enables our industry to stay at the forefront of innovation. Despite the recent advances, 3D imaging is still not the pervasive tool envisaged for wide application in science and industry. However, before 3D imaging is to become a proper scientific tool, instead of just pretty pictures, there are several challenges that we need to overcome:
• Handling of data volume
• Efficient data reduction
• Matching of 3D/4D (temporal evolution) data with appropriate modelling
MUMMERING addresses these by adopting a collaborative and coordinated approach to establish a common and open work-flow that helps each researcher covering the entire process without having to compromise on the scientific level of application.
The main research objective of MUMMERING is to transform 3D/4D imaging from a largely qualitative and exploratory technique to a truly quantitative tool for materials and information science, applicable as a core component in industry 4.0. To achieve the research objective, we urgently need to develop solutions for all steps in an automatized and integrated workflow for analysis.
In the project, we work on addressing the following associated challenges:
• Establishing analysis tools for new contrast modalities for 3D imaging.
• Establish a novel framework for understanding and modelling the relationship between structure and performance or lifetime.
• New data acquisition and reconstruction methods for ultrahigh resolution tomography covering scales from nanometers down to atomic resolution.
• Development of advanced reconstruction and segmentation algorithms that may improve 3D resolution and materials identification.
• Development of instrumentation and software that handles ultrafast 3D data acquisition for structural movies with high temporal resolution. These 3D “movies” i.e. data and matching 4D models showing a temporal evolution of structure will enable unique tests of basic assumptions and support the formulation of new models with a better representation of heterogeneous microstructure.
Highlighted results that have progressed beyond state of the art, includes:

Fast (4D) TEM tomography. One of the main problems in TEM is the inevitable degradation of the sample produced by the electron beam during the acquisition of the tilt-series. In addition, the relatively slow acquisition during conventional electron tomography hampers the investigation of dynamic effects that occur eg during in situ TEM.
To dramatically accelerate the acquisition of tilt series, so-called “fast tomography” was introduced in both TEM and HAADF-STEM modes. The methodology is based on continuously tilting the holder and simultaneously acquiring projection images, while focusing and tracking the particle at the same time.

Multimode tomography. We exploited the flexibility of modern TEM instruments, in which more than one (H)(A)ADF detector is available. Through the simultaneous use of multiple ADF detectors, a reliable 3D reconstruction of both the morphology of the nanoparticles and the twin planes can be achieved in a dose-efficient manner. Moreover, we combined these studies with EDX mapping in 3D.

Time resolved omni-directional scattering tomography. We have demonstrated a dramatic reduction in data acquisition times, from tens of hours to under a second for a complete 3D data set.

An algorithm for 2D segmentation from projection data, has been developed. Currently, we are working on a 3D version of the algorithm, which shows great promise for high robustness to noise, few projections, and limited angles.

A time-lapse correlative multimodal workflow has been developed (including X-ray CT and related volumetric analyses like digital image and volume correlation, mechanical testing, Raman spectroscopy and electron microscopy) to study the fatigue behaviour of unidirectional glass and carbon fibre composites.

We expect to achieve all of the milestones and deliverables foreseen in the project proposal. Many of these go well beyond current state of the art, and furthermore, in several areas, we expect to go beyond even our foreseen project goals. This will have a profound impact on technologies and science relying on 3D analysis in several ways:

1. Our efforts at establishing a fast, accessible analysis workflow that is accessible and intuitive to work with will enable the adaption of 3D analysis by a wider community, both in science and in industry.
2. The extension to multimodal and multiscale data acquisition, analysis and modelling will broaden the scope of applications for 3D analysis.
3. The improvements in speed of acquisition, reconstruction and analysis, will enable new applications in time-resolved studies that could have impact on medical CT, in vivo studies and on materials processing.
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