Maia X-ray fluorescence imaging: Capturing detail in complex natural samples

Motivated by the challenge of capturing complex hierarchical chemical detail in natural material from a wide range of applications, the Maia detector array and integrated realtime processor have been developed to acquire X-ray fluorescence images using X-ray Fluorescence Microscopy (XFM). Maia has b...

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Veröffentlicht in:J. Phys. Conf. Series 2014-04, Vol.499 (1), p.12002-12
Hauptverfasser: Ryan, C G, Siddons, D P, Kirkham, R, Li, Z Y, de Jonge, M D, Paterson, D J, Kuczewski, A, Howard, D L, Dunn, P A, Falkenberg, G, Boesenberg, U, De Geronimo, G, Fisher, L A, Halfpenny, A, Lintern, M J, Lombi, E, Dyl, K A, Jensen, M, Moorhead, G F, Cleverley, J S, Hough, R M, Godel, B, Barnes, S J, James, S A, Spiers, K M, Alfeld, M, Wellenreuther, G, Vukmanovic, Z, Borg, S
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Sprache:eng
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Zusammenfassung:Motivated by the challenge of capturing complex hierarchical chemical detail in natural material from a wide range of applications, the Maia detector array and integrated realtime processor have been developed to acquire X-ray fluorescence images using X-ray Fluorescence Microscopy (XFM). Maia has been deployed initially at the XFM beamline at the Australian Synchrotron and more recently, demonstrating improvements in energy resolution, at the P06 beamline at Petra III in Germany. Maia captures fine detail in element images beyond 100 M pixels. It combines a large solid-angle annular energy-dispersive 384 detector array, stage encoder and flux counter inputs and dedicated FPGA-based real-time event processor with embedded spectral deconvolution. This enables high definition imaging and enhanced trace element sensitivity to capture complex trace element textures and place them in a detailed spatial context. Maia hardware and software methods provide per pixel correction for dwell, beam flux variation, dead-time and pileup, as well as off-line parallel processing for enhanced throughput. Methods have been developed for real-time display of deconvoluted SXRF element images, depth mapping of rare particles and the acquisition of 3D datasets for fluorescence tomography and XANES imaging using a spectral deconvolution method that tracks beam energy variation.
ISSN:1742-6596
1742-6588
1742-6596
DOI:10.1088/1742-6596/499/1/012002