Characterization of micro pore optics for full-field X-ray fluorescence imaging. (1st January 2023)

• Record Type: Journal Article
• Authors: An, S.; Krapohl, D.; Thörnberg, B.; Roudot, R.; Schyns, E.; Norlin, B.
• Is Part Of: Journal of instrumentation. Volume 18:Number 1(2023)
• Publication Date: 2023-01-01
• Subjects: X-ray fluorescence (XRF) systems -- Scintillators and scintillating fibres and light guides -- Spectrometers -- X-ray transport and focusing; Scientific apparatus and instruments -- Periodicals; 502.84
• DOI: 10.1088/1748-0221/18/01/C01017
• Languages: English
• ISSNs: 1748-0221

Abstract

Abstract: Elemental mapping images can be achieved through step scanning imaging using pinhole optics or micro pore optics (MPO), or alternatively by full-field X-ray fluorescence imaging (FF-XRF). X-ray optics for FF-XRF can be manufactured with different micro-channel geometries such as square, hexagonal or circular channels. Each optic geometry creates different imaging artefacts. Square-channel MPOs generate a high intensity central spot due to two reflections via orthogonal channel walls inside a single channel, which is the desirable part for image formation, and two perpendicular lines forming a cross due to reflections in one plane only. Thus, we have studied the performance of a square-channel MPO in an FF-XRF imaging system. The setup consists of a commercially available MPO provided by Photonis and a Timepix3 readout chip with a silicon detector. Imaging of fluorescence from small metal particles has been used to obtain the point spread function (PSF) characteristics. The transmission through MPO channels and variation of the critical reflection angle are characterized by measurements of fluorescence from copper and titanium metal fragments. Since the critical angle of reflection is energy dependent, the cross-arm artefacts will affect the resolution differently for different fluorescence energies. It is possible to identify metal fragments due to the form of the PSF function. The PSF function can be further characterized using a Fourier transform to suppress diffuse background signals in the image.