Christopher K. Egan

Pixellated Cd(Zn)Te high-energy X-ray instrument

We have developed a pixellated high energy X-ray detector instrument to be used in a variety of imaging applications. The instrument consists of either a Cadmium Zinc Telluride or Cadmium Telluride (Cd(Zn)Te) detector bump-bonded to a large area ASIC and packaged with a high performance data acquisition system. The 80 by 80 pixels each of 250 μm by 250 μm give better than 1 keV FWHM energy resolution at 59.5 keV and 1.5 keV FWHM at 141 keV, at the same time providing a high speed imaging performance. This system uses a relatively simple wire-bonded interconnection scheme but this is being upgraded to allow multiple modules to be used with very small dead space. The readout system and the novel interconnect technology is described and how the system is performing in several target applications.

Non-invasive imaging of the crystalline structure within a human tooth

The internal crystalline structure of a human molar tooth has been non-destructively imaged in cross-section using X-ray diffraction computed tomography. Diffraction signals from high-energy X-rays which have large attenuation lengths for hard biomaterials have been collected in a transmission geometry. Coupling this with a computed tomography data acquisition and mathematically reconstructing their spatial origins, diffraction patterns from every voxel within the tooth can be obtained. Using this method we have observed the spatial variations of some key material parameters including nanocrystallite size, organic content, lattice parameters, crystallographic preferred orientation and degree of orientation. We have also made a link between the spatial variations of the unit cell lattice parameters and the chemical make-up of the tooth. In addition, we have determined how the onset of tooth decay occurs through clear amorphization of the hydroxyapatite crystal, and we have been able to map the extent of decay within the tooth. The described method has strong prospects for non-destructive probing of mineralized biomaterials.

3D chemical imaging in the laboratory by hyperspectral X-ray computed tomography

We report the development of laboratory based hyperspectral X-ray computed tomography which allows the internal elemental chemistry of an object to be reconstructed and visualised in three dimensions. The method employs a spectroscopic X-ray imaging detector with sufficient energy resolution to distinguish individual elemental absorption edges. Elemental distributions can then be made by K-edge subtraction, or alternatively by voxel-wise spectral fitting to give relative atomic concentrations. We demonstrate its application to two material systems: studying the distribution of catalyst material on porous substrates for industrial scale chemical processing; and mapping of minerals and inclusion phases inside a mineralised ore sample. The method makes use of a standard laboratory X-ray source with measurement times similar to that required for conventional computed tomography.

Dark-field hyperspectral X-ray imaging

In recent times, there has been a drive to develop non-destructive X-ray imaging techniques that provide chemical or physical insight. To date, these methods have generally been limited; either requiring raster scanning of pencil beams, using narrow bandwidth radiation and/or limited to small samples. We have developed a novel full-field radiographic imaging technique that enables the entire physio-chemical state of an object to be imaged in a single snapshot. The method is sensitive to emitted and scattered radiation, using a spectral imaging detector and polychromatic hard X-radiation, making it particularly useful for studying large dense samples for materials science and engineering applications. The method and its extension to three-dimensional imaging is validated with a series of test objects and demonstrated to directly image the crystallographic preferred orientation and formed precipitates across an aluminium alloy friction stir weld section.

A new approach to synchrotron energy-dispersive X-ray diffraction computed tomography

A new data collection strategy for performing synchrotron energy-dispersive X-ray diffraction computed tomography has been devised. This method is analogous to angle-dispersive X-ray diffraction whose diffraction signal originates from a line formed by intersection of the incident X-ray beam and the sample. Energy resolution is preserved by using a collimator which defines a small sampling voxel. This voxel is translated in a series of parallel straight lines covering the whole sample and the operation is repeated at different rotation angles, thus generating one diffraction pattern per translation and rotation step. The method has been tested by imaging a specially designed phantom object, devised to be a demanding validator for X-ray diffraction imaging. The relative strengths and weaknesses of the method have been analysed with respect to the classic angle-dispersive technique. The reconstruction accuracy of the method is good, although an absorption correction is required for lower energy diffraction because of the large path lengths involved. The spatial resolution is only limited to the width of the scanning beam owing to the novel collection strategy. The current temporal resolution is poor, with a scan taking several hours. The method is best suited to studying large objects (e.g. for engineering and materials science applications) because it does not suffer from diffraction peak broadening effects irrespective of the sample size, in contrast to the angle-dispersive case.

Removing multiple outliers and single-crystal artefacts from X-ray diffraction computed tomography data

This paper reports a simple but effective filtering approach to deal with single-crystal artefacts in X-ray diffraction computed tomography (XRD-CT). In XRD-CT, large crystallites can produce spots on top of the powder diffraction rings, which, after azimuthal integration and tomographic reconstruction, lead to line/streak artefacts in the tomograms. In the simple approach presented here, the polar transform is taken of collected two-dimensional diffraction patterns followed by directional median/mean filtering prior to integration. Reconstruction of one-dimensional diffraction projection data sets treated in such a way leads to a very significant improvement in reconstructed image quality for systems that exhibit powder spottiness arising from large crystallites. This approach is not computationally heavy which is an important consideration with big data sets such as is the case with XRD-CT. The method should have application to two-dimensional X-ray diffraction data in general where such spottiness arises.

Full-field energy-dispersive powder diffraction imaging using laboratory X-rays

A laboratory instrument with the ability to spatially resolve energy-dispersed X-ray powder diffraction patterns taken in a single snapshot has been developed. The experimental arrangement is based on a pinhole camera coupled with a pixelated spectral X-ray detector. Collimation of the diffracted beam is defined by the area of the footprint of a detector pixel and the diameter of the pinhole aperture. Each pixel in the image, therefore, contains an energy-dispersed powder diffraction pattern. This new X-ray imaging technique enables spatial mapping of crystallinity, crystalline texture or crystalline phases from within a sample. Validation of the method has been carried out with a back-to-back comparison with crystalline texture mapping local to a friction stir weld in an aluminium alloy taken using synchrotron radiation.

Energy calibration and gain correction of pixelated spectroscopic x-ray detectors using correlation optimised warping

We describe the implementation of a reliable, robust and flexible gain correction and energy calibration algorithm for pixelated spectroscopic x-ray detectors. This algorithm uses a data processing method known as correlation optimised warping which aligns shifted datasets by means of a segmental linear stretching and compression of the spectral data in order to best correlate with a reference spectrum. We found the algorithm to be very robust against low-count spectroscopy, and was reliable in a range of different spectroscopic applications. Analysis of the integrated spectrum over all pixels for a Cerium K-alpha x-ray emission (at 34.72 keV) yielded a peak width of 2.45 keV before alignment and 1.11 keV after alignment. This compares favourably with the best in class pixel peak width of 0.76 keV and the mean peak width for all pixels of 1.00 keV. We also found the algorithm to be more user friendly than other peak-search algorithms because there is less external input. A key advantage of this algorithm is that it requires no prior knowledge of the input spectral characteristics, shape or quality of the data. This therefore lends itself to being useful for in-line processing and potentially removes the need for a separate calibration standard (e.g. a radioactive source). This algorithm can be used for any system that simultaneously collects large numbers of spectral data—including multi-element detectors.