Seminars Archive

Mon 25 May, at 11:00 - Training Room

Modelling of Grazing Incidence X-Ray Fluorescence (GIXRF) for surface layer characterisation

Fabio Brigidi
Fondazione Bruno Kessler, Trento

X-Ray fluorescence (XRF) is a well-established technique for quantitative elemental analysis. For the characterization of thin films and regions near the surface of smooth flat samples a grazing incidence configuration of XRF can be used which exploits reflection and refraction phenomena to modulate the amplitude of the electric field and hence the emitted fluorescence at the variation of the angle of incidence. This technique, entitled Grazing Incidence X-Ray Fluorescence (GIXRF) [1], shares the same phenomenological description with X-Ray Reflectivity, a well-established technique used in thin film metrology. GIXRF analysis is performed by fitting the simulated signal to the experimental measurement. Simulations are based on physical models and tabulated fundamental parameters. The modelling has to properly describe the expected fluorescence of particular elements given a sample specific structure and has also to include the parameters issued by the experimental apparatus. In order to model correctly an X-ray fluorescence experiment it is necessary to include the effect of the source (beam divergence, size, shape and energetic composition), the sample inspected area, the solid angle of detection, the direct and indirect excitation of the elements in a layered sample (including secondary excitation and cascade effect), the absorption of the emitted fluorescence intensities, and the detector response function. The modelling strategies implemented in the software GIMPy (acronym for Grazing Incidence Material analyses with Python) designed for the simulation of GIXRF profiles, will be described. Moreover the potential of the technique will be demonstrated via application examples dealing with the analyses of doping profiles and thin multi-layered samples. [1] de Boer, D. K. (1991). Physical Review B, 44(2), 498.

(Referer: E. Cantori)
Last Updated on Tuesday, 24 April 2012 15:21