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

Brigidi, Fabio (2015) Modelling of Grazing Incidence X-Ray Fluorescence (GIXRF) for surface layer characterisation. PhD thesis, University of Trento.

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Abstract

GIXRF (Grazing incidence X-Ray Fluorescence) is an analytical technique with high potential in the study of depth profiles and in the characterization of thin layered structures. To extract information from a GIXRF measurement and determine the layer composition it is necessary to compare the experimental data with simulation. However at the moment this thesis has been written, there is no software widely recognized from the scientific community as the reference software for the analysis. For this reason this work of thesis deals with the development of an analytical software and its application to several case studies. A program called GIMPy is presented. The program is capable to perform simulations of the expected GIXRF signal from a given model, but also of the expected fluorescence signal at high angle of incidence and the reflectivity (XRR). The use of a programming language like Python makes the library extremely portable, easily extendible and flexible thanks to its object oriented syntax and scripting capabilities. GIMPy bases the modelling of the electric field propagation inside the sample and the expected fluorescence from the theoretical description found in literature. Moreover a series of methods were developed to account for the effect of the instrumental set-up geometry, the detector response, indirect excitation and primary beam shape and energy composition. A round-robin related to GIXRF comparison with several institutes developing an analytical software has been organised. The comparison showed a good agreement between the results obtained with GIMPy and the other programs. GIXRF has then been applied to the characterisation of several systems. A combined XRR and GIXRF analysis of multi-layered transparent and conductive oxide films (TCO) of technological interest resulted in a nondestructive and precise characterization of their structures. Measurements were performed at the ESRF synchrotron facility and in the laboratory using a Cu tube as source. Combining the measurements performed with dif- ferent instrumental set-ups the effectiveness of the combined XRR-GIXRFapproach, that has proved already effective in the past, has been further shown. It has been possible to evidence the existence of a thin inter dif- fusion profile induced by annealing the samples, showing a sensitivity to structural changes in the depth of 0.5-1 nm. GIXRF measurements performed on Sn implants in Ge provided information about the total dose retained by the sample after an implantation process. Synchrotron tunable excitation energy was extremely valuable for the fluorescence analysis.The two different modelling strategies used for data fitting, one using a SIMS profile as an input the other an analytical description of the depth profile, and returned values close to the one obtained with other techniques. A new technology based on the deposition of ALD coatings for the preservation of cultural heritage object has been characterised with XRR and GIXRF. The XRR measurements were effective in revealing the deterioration of the coatings after the effect of an accelerated ageing process. Moreover the analysis of GIXRF also revealed the formation of nano-particles at the top of the surface, and allowed the characterisation of their size and composition. The last chapter shows some theoretical calculations investigating GIXRF potential in the size and chemical characterisation of nano-particles. It is shown how the experimental setup and the sample preparation can influ- ence the outcome of the measurement. The theoretical calculations are also reinforced by the result obtained on some preliminary experiments on Gold nano-particles.

Item Type:Doctoral Thesis (PhD)
Doctoral School:Physics
PhD Cycle:27
Subjects:Area 02 - Scienze fisiche > FIS/03 FISICA DELLA MATERIA
Funders:Fondazione Bruno Kessler
Repository Staff approval on:13 May 2015 14:53

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