Printed circuit boards (PCBs) are at the heart of numerous advancements in electronic science and technology, and as such they are expected to work flawlessly and as designed.Errors, no matter how seemingly minor, cannot be tolerated because PCBs are used in many highly technological applications, such as those supporting aerospace, biotechnology, automotive, military and many more industries.There exist many PCB testing protocols, such as in-circuit testing or bare board testing; however, these tests may not detect performance issues that are outside of their testing ranges.So, these PCBs are most often subject to additional optical and internal validation.One technique for visualizing inside PCB materials is X-ray imaging, which can be used to build an understanding of the material's internal structure and any possible defects.Examples of defects that may occur are microcracks, component misalignment, voids and an excess of solder.As PCBs become more densely populated, with hundreds of smaller components and multiple layers of material mixes, a single radiography approach has limitations.In this study, we will highlight the use of the full X-ray energy spectrum by using spectral radiography to discern the individual materials present.With this approach, components in a mixed or multi-layered electronic device become visible.Conventional and spectral x-ray imaging is, of course, not limited to the analysis of PCBs.As an example, a multi-modal conventional and spectral CT study was performed on a smart ring wearable electronic device.Wearable electronic devices are becoming increasingly popular and are packed with different sensors to measure temperature, heart rate, blood oxygen or movement.In addition, these devices need components such as batteries, antennas, or gyroscopes to monitor and transmit data about the person wearing them.Given the unconventional shape of some of these components, it is crucial to assess and understand the internal connections once they are fitted into the final device.The combination of conventional CT and radiography with their spectral counterparts is a powerful way to gain insights into electronic components.Where CT can be seen as the gold standard for non-destructive 3D characterization, spectral CT makes it possible to actually identify gold.By harnessing the multi-energy information from a single spectral radiography acquisition, it is possible to discern within a radiograph the presence of different materials in the x-ray path.An unlimited number of materials can be distinguished from the full spectral information, even without pre-tuning the acquisition parameters as is often required in classical dual-energy approaches.The spectral information allows us to select regions of interest that are eligible to further investigation with high resolution CT imaging closing the failure analysis track and eventually leading to failure free devices.

Micro-CT can be used to study the structure of samples from a centimeter to micrometer scale. One of the main limitations in this, however, is the inability to perform true material identification without prior knowledge, as contrast inside a micro-CT scan is mainly caused by the atomic number of the sample. Also density, used x-ray energy, the x-ray spectrum and the used detector have influence on the achieved grey values and contrast in a dataset. We present integration of an energy-sensitive spectral detector inside laboratory-based micro-CT scanners: the TESCAN PolyDET TM .

The Witwatersrand Supergroup in South Africa is not only the best-preserved sequence of Archean sedimentary rocks but also hosts the largest gold deposit on earth, yet discovered. The gold is situated in quartz-pebble conglomerates and is generally associated with a wide variety of minerals, including pyrite (FeS 2 ), uraninite (UO 2 ), pyrobitumen, base metal sulfides and phyllosilicates [1]. Despite extensive research over the past 100 years, the origin of the gold is still debated with two models receiving most of the attention: the modified paleoplacer model and the hydrothermal models [2]. The modified paleoplacer model assumes that detrital gold was transported into the host rock by fluvial processes, followed by a short-range mobilization (micrometer-to meter scale) by hydrothermal fluids that infiltrated the host rock [2]. In the hydrothermal model, gold was introduced into the host rock by postdepositional hydrothermal fluids from an external source [2]. To find new evidence for the origin of gold, we present new high-resolution 3-dimensional (3D) data based on the combination of X-ray computed micro tomography (micro-CT) and spectral X-ray computed micro tomography (Sp-CT

We present a new approach to 3-dimensional chemical imaging based on X-ray computed micro tomography (CT), which enables the analysis of the internal elemental chemistry. The method uses a conventional laboratory-based CT scanner equipped with a semiconductor detector (CdTe). Based on the X-ray absorption spectra, elements in a sample can be distinguished by their specific K-edge energy. The capabilities and performance of this new approach are illustrated with different experiments, i.e. single pure element particle measurements, element differentiation in mixtures, and mineral differentiation in a natural rock sample. The results show that the method can distinguish elements with K-edges in the range of 20 to 160 keV, this corresponds to an element range from Ag to U. Furthermore, the spectral information allows a distinction between materials, which show little variation in contrast in the reconstructed CT image.

Image-based analytical tools in geosciences are indispensable for the characterization of minerals, but most of them are limited to the surface of a polished plane in a sample and lack 3D information. X-ray micro computed tomography (micro CT) provides the missing 3D information of the microstructures inside samples. However, a major drawback of micro CT in the characterization of minerals is the lack of chemical information that makes mineral classification challenging. Spectral X-ray micro computed tomography (Sp-CT) is a new and evolving tool in different applications such as medicine, security, material science, and geology. This non-destructive method uses a multi-pixel photon-counting detector (PCD) such as cadmium telluride (CdTe) in combination with a conventional CT scanner (TESCAN CoreTOM) to image a sample and detect its transmitted polychromatic X-ray spectrum. Based on the spectrum, elements in a sample can be identified by an increase in attenuation at specific K-edge energies. Therefore, chemically different particles can be distinguished inside a sample from a single CT scan. The method is able to distinguish elements with K-edges in the range from 25 to 160 keV, which applies to elements with Z > 48 (Sittner et al., 2020). We present results from various sample materials. Different pure elements and element oxides were measured to compare the position of theoretical and measured K-edge energies. All measured K-edge energies are slightly above the theoretical value, but based on the results a correction algorithm could be developed. Furthermore, different monazite grains were investigated, which can be divided into two groups with respect to the content of different RE elements on the basis of the spectrum: La-Ce-rich and La-Ce-poor. In addition, samples from the Au-U Witwatersrand Supergroup demonstrate the potential applications of Sp-CT for geological samples. We measured different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field. Sp-CT can distinguish gold, uraninite and galena grains based on their K-edge energies in the drill core without preparation. Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Van Loo, D., Merkulova, M., Roine, A., & Liipo, J. (2020). Spectral X-ray computed micro tomography: 3-dimensional chemical imaging. X-Ray Spectrometry, September, 1–14.

In tomographic imaging, the traditional process consists of an expert and an operator collecting data, the expert working on the reconstructed slices and drawing conclusions. The quality of reconstructions depends heavily on the quality of the collected data, except that, in the traditional process of imaging, the expert has very little influence over the acquisition parameters, experimental plan or the collected data. It is often the case that the expert has to draw limited conclusions from the reconstructions, or adapt a research question to data available. This method of imaging is static and sequential, and limits the potential of tomography as a research tool. In this paper, we propose a more dynamic process of imaging where experiments are tailored around a sample or the research question; intermediate reconstructions and analysis are available almost instantaneously, and expert has input at any stage of the process (including during acquisition) to improve acquisition or image reconstruction. Through various applications of 2D, 3D and dynamic 3D imaging at the FleX-ray Laboratory, we present the unexpected journey of exploration a research question undergoes, and the surprising benefits it yields.

The use of high resolution, three-dimensional visualization has been receiving growing interest within life sciences, with non-invasive imaging tools becoming more readily accessible. Although initially useful for visualizing mineralized tissues, recent developments are promising for studying soft tissues as well. Especially for micro-CT scanning, several X-ray contrast enhancers are performant in sufficiently contrasting soft tissue organ systems by a different attenuation strength of X-rays. Overall visualization of soft tissue organs has proven to be possible, although the tissue-specific capacities of these enhancers remain unclear. In this study, we tested several contrast agents for their usefulness to discriminate between tissue types and organs, using three model organisms (mouse, zebrafish and Xenopus). Specimens were stained with osmium tetroxide (OsO4), phosphomolybdic acid (PMA) and phosphotungstic acid (PTA), and were scanned using high resolution microtomography. The contrasting potentials between tissue types and organs are described based on volume renderings and virtual sections. In general, PTA and PMA appeared to allow better discrimination. Especially epithelial structures, cell-dense brain regions, liver, lung and blood could be easily distinguished. The PMA yielded the best results, allowing discrimination even at the level of cell layers. Our results show that those staining techniques combined with micro-CT imaging have good potential for use in future research in life sciences.

To preserve the quality of fresh pear fruit after harvest and deliver quality fruit year-round a controlled supply chain and long-term storage are applied. During storage, however, internal disorders can develop due to suboptimal storage conditions that may not cause externally visible symptoms. This makes them impossible to be detected by current commercial quality grading systems in a reliable and non-destructive way. A combination of a Support Vector Machine coupled with a feature extraction algorithm and X-ray Computed Tomography is proposed to successfully detect internal disorders in 'Conference' and 'Cepuna' pear fruit nondestructively. Classifiers were able to distinguish defective from sound fruit with classification accuracies ranging between 90.2 and 95.1% depending on the cultivar and number of used features. Moreover, low false positive and negative rates were obtained, respectively ranging between 0.0 and 6.7%, and 5.7 and 13.3%. Classifiers trained on 'Conference' data were transferred effectively to the 'Cepuna' cultivar, suggesting generalizability to other cultivars as well. With continuing developments in both hardware and software to increase inspection speed and reduce equipment costs, the method can be implemented in industrial applications, e.g., inline translational X-ray CT.

BACKGROUND AND AIMS:Tree rings, as archives of the past and biosensors of the present, offer unique opportunities to study influences of the fluctuating environment over decades to centuries. As such, tree-ring-based wood traits are capital input for global vegetation models. To contribute to earth system sciences, however, sufficient spatial coverage is required of detailed individual-based measurements, necessitating large amounts of data. X-ray computed tomography (CT) scanning is one of the few techniques that can deliver such data sets.METHODS:Increment cores of four different temperate tree species were scanned with a state-of-the-art X-ray CT system at resolutions ranging from 60 μm down to 4.5 μm, with an additional scan at a resolution of 0.8 μm of a splinter-sized sample using a second X-ray CT system to highlight the potential of cell-level scanning. Calibration-free densitometry, based on full scanner simulation of a third X-ray CT system, is illustrated on increment cores of a tropical tree species.KEY RESULTS:We show how multiscale scanning offers unprecedented potential for mapping tree rings and wood traits without sample manipulation and with limited operator intervention. Custom-designed sample holders enable simultaneous scanning of multiple increment cores at resolutions sufficient for tree ring analysis and densitometry as well as single core scanning enabling quantitative wood anatomy, thereby approaching the conventional thin section approach. Standardized X-ray CT volumes are, furthermore, ideal input imagery for automated pipelines with neural-based learning for tree ring detection and measurements of wood traits.CONCLUSIONS:Advanced X-ray CT scanning for high-throughput processing of increment cores is within reach, generating pith-to-bark ring width series, density profiles and wood trait data. This would allow contribution to large-scale monitoring and modelling efforts with sufficient global coverage.

To bridge the gap between lab-based high-resolution X-ray tomography (micro-CT) and synchrotron-based micro-CT, lab-scale accelerator-based or Inverse Compton Scattering (ICS) X-ray sources are a promising technology. In the scope of a large-scale project funded by the European Regional Development Fund (Interreg Grensregio), a new ICS source dubbed Smart*Light is being developed at TU Eindhoven. In this work, we present the advantages of this source compared to existing systems and its potential in industrial X-ray CT.

Urban mining is defined as the process of reclaiming raw materials from spent products, buildings and waste and is often put forward as one of the solutions to fulfill our ever increasing demand for materials in highly urbanized areas. The strong temporal, seasonal and regional variations of this waste and its intrinsic heterogeneity are a source of high insecurity and risk for the waste processing industry and puts high pressure on the applied processing technologies. Processing plants should therefore continuously adapt to changing input variations to warrant optimal material valorisation. However, due to the lack of suitable (continuous and fast) characterisation methods this is often not possible. As a consequence, the input variability translates directly to the output streams. The variable quality of secondary materials strongly decreases market interest in these materials and hampers the transition to a circular economy. Quality assessment is traditionally performed by superficial visual inspection or manual separation of too small and possibly non-representative samples, and is therefore often not reliable. In addition the task is tedious, time-intensive, subjective and rather unpleasant. To meet this need for a rapid, continuous, automatic, objective and reliable characterisation technology, a device, combining different sensor types, was built. The technology will allow to optimize existing and to develop new recycling processes, and assess secondary raw material quality, based on accurate, representative and objective data. Current sensor techniques in waste characterization mainly focus on surface properties, e.g. near-infrared, colour, hyperspectral or X-ray fluorescence. However waste material is often dirty and the surface properties are not representative for the bulk of the material. To overcome this limitation, a technology that sees “through” the material was adopted: X-ray Transmission (XRT). By measuring at two energy levels, called Dual Energy (DE-XRT), it is possible to determine material properties such as the average atom number and density. To accurately interpret the information gathered by DE-XRT, extra information such as the 3D shape and volume of the object is employed. This is measured by 3D laser triangulation (3DLT). 3DLT is a well-known technology in the industry that can measure the geometry of object at high resolution (sub-mm) using a laser and a camera. The combination of these technologies allows to fully characterise a waste stream on the level of individual particles with respect to volume, mass, shape and composition. Using this information, accurate mass balances can be measured. In addition, the material and shape measurement is complemented by an RGB detector, bringing in additional information which can be used to better differentiate the materials using image processing and machine learning algorithms. The development of methods to extract the relevant information from the sensor data is the topic of ongoing research. The technology will allow to optimise existing and to develop new recycling processes, and assess secondary raw material quality, based on accurate, representative and objective data. During the conference, a real demo case will be presented based on mixed construction and demolition waste typically collected by SUEZ in Belgium.

Journal Article Opportunities for Time-resolved Dynamic CT Imaging in the Laboratory Get access Arno Merkle, Arno Merkle TESCAN XRE, Ghent, Belgium Search for other works by this author on: Oxford Academic Google Scholar Marijn Boone, Marijn Boone TESCAN XRE, Ghent, Belgium Search for other works by this author on: Oxford Academic Google Scholar Denis Van Loo, Denis Van Loo TESCAN XRE, Ghent, Belgium Search for other works by this author on: Oxford Academic Google Scholar Jan Dewanckele, Jan Dewanckele TESCAN XRE, Ghent, Belgium Search for other works by this author on: Oxford Academic Google Scholar Frederik Coppens Frederik Coppens TESCAN XRE, Ghent, Belgium Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 380–381, https://doi.org/10.1017/S1431927619002630 Published: 01 August 2019

The illustrations of the late nineteenth-/twentieth-century scientist/artist Ernst Haeckel, as depicted in his book Art Forms in Nature (originally in German as Kunstformen der Natur, 1898–1904), have been at the intersection of art, biology, and mathematics for over a century. Haeckel’s images of radiolaria (microscopic protozoans described as amoeba in glass houses) have influenced various artists for over a century (glass artists Leopold and Rudolph Blaschka; sculptor Henry Moore; architects Rene Binet, Zaha Hadid, Antoni Gaudi, Chris Bosse and Frank Gehry; and designers–filmmakers Charles and Ray Eames). We focus on this history and extend the artistic, biological, and mathematical contributions of this interdisciplinary legacy by going beyond the 3D visual, topological, and geometric analyses of radiolaria to include the nanoscale with graph theory, spatial statistics, and computational geometry. We analyze multiple visualizations of radiolaria generated through Haeckel’s images, light microscopy, scanning electron microscopy, micro- and nanotomography, and three-dimensional computer rendering. Mathematical analyses are conducted using the image analysis package “Ka-me: A Voronoi Image Analyzer.” Further analyses utilize three-dimensional printing, laser etched crystalline glass art, and sculpture. Open sharing of three-dimensional nanotomography of radiolaria and other protozoa through MorphoSource enables new possibilities for artists, architects, paleontologists, structural morphologists, taxonomists, museum curators, and mathematical biologists. Distinctively, newer models of radiolaria fit into a larger context of productive interdisciplinary collaboration that continues Haeckel’s legacy that lay a foundation for new work in biomimetic design and additive manufacturing where artistic and scientific models mutually and robustly generate wonder, beauty, utility, curiosity, insight, environmentalism, theory, and questions.

X-ray interferometry provides a dark-field image, essentially a small-angle X-ray scattering image, of the voids and print defects in an additively manufactured polymer object. The interferometers used were tuned to scattering length 2-5 mu m and configured to measure scattering along both vertical and horizontal directions. The samples studied included Stanford Bunnies, fabricated from acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA), and a quadratic test object fabricated from PLA. The dark-field projection images show orientation dependent X-ray scattering which is due to anisotropic voids and gaps at the filament-to-filament interface in these fused deposition modeling additive manufacturing objects. SEM corroborates the existence of gaps between filaments. The absorption and dark-field volumes are used to correlate printhead trajectory with print defect density. The absorption volume is used to generate perimeter points slice-by-slice, and from these points, the 2D curvature is calculated. There is a slight increase in X-ray scattering, hence print defect density, at regions with high curvature. Two X-ray interferometry techniques were used: stepped-grating and single-shot. As currently developed, stepped-grating has the larger field-of-view examination of an entire test object whilst single-shot has the potential for real-time, in situ measurement of the printing process within 1 mm of the printhead.

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In the waste recycling industry, material separation is of key importance. In this paper, we present a new material identification method, based on dual-energy X-ray radiographic images, developed in the context of waste recycling industry. The algorithm is based on a dual energy technique and allows to estimate the effective atomic number of the sample under investigation. A projection simulator with high accuracy that allows to simulate realistic measurements of a wide range of materials is used. The resulting virtual measurements are then used in an identification tool, which achieves the identification by comparing the virtual and actual measurements. Via this procedure, an extensive range of materials and thicknesses can be analyzed and identified. Finally, an optimization scheme has been developed, which allows the selection of an ideal setting for the scanner, in order to optimize the identification process.

Over the past decade, laboratory based X-ray computed micro-tomography (micro-CT) has given unique insights in the internal structure of complex reservoir rocks, improving the understanding of pore scale processes and providing crucial information for pore scale modelling. Especially in-situ imaging using X-ray optimized Hassler type cells has enabled the direct visualization of fluid distributions at the pore scale under reservoir conditions. While sub-micrometre spatial resolutions are achievable in lab-based micro- CT, the temporal resolutions are still limited to minutes or hours. This time restriction is often a bottleneck for imaging dynamic in-situ processes, thus limiting the applicability to relatively slow pore scale processes occurring in the order of hours to days, or to end points in drainage-imbibition cycles. To overcome this issue, X-ray Engineering (XRE) and Ghent University’s Centre for X- ray Tomography (UGCT) have jointly developed a gantry-based micro-CT system. This system’s X-ray tube and detector rotate continuously in a horizontal plane around the fixed sample. The setup still allows to tune the geometrical magnification, with spatial resolutions down to 5 µm. This fixed sample setup is also ideal for in-situ imaging, as the flow cells can be directly connected to high pressure flow tubing and sensor lines, without the need to allow rotational movement relative to the X-ray source and detector. An efficient hardware design with a fast flat panel detector, combined with custom X-ray transparent flow cells to increase X-ray flux and dedicated 4D software tools in acquisition, reconstruction and analysis, allows to reach temporal resolutions in the order of seconds. The possibilities of this new approach in dynamic in-situ imaging are illustrated with flow tests on a carbonate sample. We discuss the challenges in dynamic imaging and present methods to improve X-ray flux and optimize image quality by means of this experiment. Furthermore, we show that the integration of fast imaging experiments with other information from peripheral sensors or from imaging data at different resolutions can help to link behaviour at the pore scale to the effective properties at the core scale, but also facilitates the experimental workflow.