Engineers will soon be able to X-ray entire manufactured components—not just thumbnail-sized samples—to spot the microscopic defects that cause them to fail. Today, manufacturers can only inspect tiny test-pieces with high-resolution X-ray CT, missing the defects that arise in real, complex parts. An additively manufactured turbine blade, for example, develops different flaws than a simple test cube. This gap makes it impossible to predict how long a component will last or to design manufacturing processes that avoid those flaws. This project builds a new beamline at the European Synchrotron (ESRF) that increases the imaging volume a million-fold while maintaining micrometre resolution. It will let researchers scan entire engineering components, then zoom in on specific defects and watch them grow under mechanical or thermal loads in time-lapse. The same technique will also reveal how defects form during additive manufacturing and battery assembly, and how they trigger rapid failures such as thermal runaway. If successful, the work will feed defect data directly into digital twins of manufacturing processes, enabling smarter, part-specific production. It will also give UK academics and industry access to these capabilities through the National Research Facility for laboratory CT.
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In highly engineered materials, microscale defects can determine failure modes at the compo-nent/system scale. While X-ray CT is unique in being able to image, find, and follow defects non-destructively at the microscale, currently it can only do so for mm sized samples. This currently presents a significant limitation for manufacturing design and safe life prediction where the nature and location of the defects are a direct consequence of the manufacturing process. For example, in additive manufacturing, the defects made when manufacturing a test-piece may be quite different from those in a three dimensionally complex additively manufactured engineering component. Similarly, for composite materials, small-scale samples are commonly not large enough to properly represent all the hierarchical scales that control structural behaviour. This collaboration between the European Research Radiation Facility (ESRF) and the National Research Facility for laboratory CT (NRF) will lead to a million-fold increase in the volume of material that can be X-ray imaged at micrometre resolution through the development and exploitation of a new beamline (BM18). Further, this unparalleled resolution for X-rays at energies up to 400keV enables high Z materials to be probed as well as complex environmental stages. This represents a paradigm shift allowing us to move from defects in sub-scale test-pieces, to those in manufactured components and devices. This will be complemented by a better understanding of how such defects are introduced during manufacture and assembly. It will also allow us to scout and zoom manufactured structures to identify the broader defect distribution and then to follow the evolution of specific defects in a time-lapse manner as a function of mechanical or environmental loads, to learn how they lead to rapid failure in service. This will help to steer the design of smarter manufacturing processes tailored to the individual part geometry/architecture and help to establish a digital twin of additive and composite manufacturing processes. Secondly, we will exploit high frame rate imaging on ID19 exploiting the increased flux available due to the new ESRF-extremely bright source upgrade to study the mechanisms by which defects are introduced during additive manufacture and how defects can lead to very rapid failures, such as thermal runaway in batteries In this project, we will specifically focus on additive manufacturing, composite materials manufacturing and battery manufacturing and the in situ and operando performance and degradation of such manufactured articles, with the capabilities being disseminated and made more widely available to UK academics and industry through the NRF. The collaboration will also lead to the development of new data handling and analysis processes able to handle the very significant uplift in data that will be obtained and will lead to multiple site collaboration on experiments in real-time. This will enable us to work together as a multisite team on projects thereby involving less travelling and off-setting some of the constraints on demanding experiments posed by COVID-19.
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