Algorithms for three-dimensional chemical analysis with multi-energy tomographic data
The conversion of 3D data sets of x-ray absorption images into 3D composition maps requires accurate mass absorption values, high-quality images, and a robust fitting algorithm. We evaluate the status of convenient x-ray absorption databases, the impact of various CCD parameters and imaging strategies (minimal vs over-determined), and styles of least-squares fits of the images (optionally including volume constraints). Concerns raised include the impact of NEXAFS features and limited CCD dynamic range. In the absence of these effects, the reduction of images to composition is fast and robust, as tested with simulations based on element-labeled Shepp-Logan phantoms. These studies allow one to evaluate a recent experiment in which synchrotron X-ray tomography is used to image a multicomponent sample. Those samples consisted of a mixture containing high-impact polystyrene (HIPS) and a two-component flame retardant, a brominated phthalimide dimer and a synergist, antimony oxide (Sb 2O 3). Complete tomography data sets were acquired at 3.34 micron spatial resolution using seven X-ray energies in the range of 12 to 40 keV, closely spanning Br and Sb Is electron binding energies at 13.474 and 30.491 keV, respectively.
Publication Source (Journal or Book title)
Proceedings of SPIE - The International Society for Optical Engineering
Ham, K., Willson, C., Rivers, M., Kurtz, R., & Butler, L. (2004). Algorithms for three-dimensional chemical analysis with multi-energy tomographic data. Proceedings of SPIE - The International Society for Optical Engineering, 5535, 286-292. https://doi.org/10.1117/12.560225