In materials and earth science, but also in chemistry, pharmaceutics and engineering, the quantification of elements and crystal phases in solid samples is often essential for a full characterization of materials. The most frequently used techniques for this purpose are X-ray fluorescence (XRF) for elemental analysis and X-ray powder diffraction (XRPD) for phase analysis. In both methods, relations between signal and quantity do exist but they are expressed in terms of complex equations including many parameters related to both sample and instruments, and the dependence on the active element or phase amounts to be determined is convoluted among those parameters. Often real-life samples hold relations not suitable for a direct quantification and, therefore, estimations based only on the values of the relative intensities are affected by large errors. Preferred orientation (PO) and microabsorption (MA) in XRPD cannot usually be avoided, and traditional corrections in Rietveld refinement, such as the Brindley MA correction, are not able, in general, to restore the correct phase quantification. In this work, a multivariate approach, where principal component analysis is exploited alone or combined with regression methods, is used on XRPD profiles collected on ad hoc designed mixtures to face and overcome the typical problems of traditional approaches. Moreover, the partial or no known crystal structure (PONKCS) method was tested on XRPD data, as an example of a hybrid approach between Rietveld and multivariate approaches, to correct for the MA effect. Particular attention is given to the comparison and selection of both method and pre-process, the two key steps for good performance when applying multivariate methods to obtain reliable quantitative estimations from XRPD data, especially when MA and PO are present. A similar approach was tested on XRF data to deal with matrix effects and compared with the more classical fundamental-parameter approach. Finally, useful indications to overcome the difficulties of the general user in managing the parameters for a successful application of multivariate approaches for XRPD and XRF data analysis are given.

Low-cost, environmentally friendly and easily applicable coating for Mg alloys, able to resist in real world conditions, are studied. Coatings already used for other metals (aluminum, steel) and never tested on Mg alloy for its different surface and reactivity were deposited on AM60 magnesium alloys to facilitate their technological applications, also in presence of chemically aggressive conditions. A biobased PA11 powder coating was compared to synthetic silicon-based and polyester coatings, producing lab scale samples, probed by drop deposition tests and dipping in increasingly aggressive, salty, basic and acid solutions, at RT and at higher temperatures. Coatings were analyzed by SEM/EDX to assess their morphology and compositions, by optical and IR-ATR microscopy analyses, before and after the drop tests. Migration analyses from the samples were performed by immersion tests using food simulants followed by ICP-OES analysis of the recovered simulant to explore applications also in the food contact field. A 30 μm thick white lacquer and a 120 μm PA11 coating resulted the best solutions. The thinner siliconic and lacquer coatings, appearing brittle and thin in the SEM analysis, failed some drop and/or dipping test, with damages especially at the edges. The larger thickness is thus the unique solution for edgy or pointy samples. Finally, coffee cups in AM60 alloy were produced, as real word prototypes, with the best performing coatings and tested for both migration by dipping, simulating also real world aging (2 h in acetic acid at 70° and 24 h in hot coffee at 60 °C): PA11 resulted stable in all the tests and no migration of toxic metals was observed, resulting a promising candidate for many real world application in chemically aggressive environments and also food and beverage related applications.

Eutectic mixtures are usually studied by differential scanning calorimetry (DSC), able to identify the transition temperatures, possible hysteresis, and investigate the energetic features of transformations. However, DSC is not able to give compositional, structural, or morphological information. A new approach is proposed exploiting powder X-ray diffraction (XRPD) and imaging to overcome the issues posed to diffraction by the presence of an amorphous liquid phase. Principal component analysis (PCA) is applied blindly to in situ XRPD data from both solid and liquid phases in an approach called differential scanning diffraction (DSD), with PCA scores being the reaction coordinate of melting or crystallization steps. PCA was used in a similar way to analyze the imaging data in what was named differential scanning imaging (DSI). Exploiting this approach, the structural and morphological changes during phase transitions can be characterized by XRPD and imaging respectively, complementarily to the energetic effects probed by DSC. Melting and crystallization points can be identified together with the hysteresis between downward and upward temperature ramps, by the structural and morphological viewpoints. A three-component mixture (NaBr, KCl, and water), with wide industrial applications, was studied to describe the behavior around the eutectic composition and examine how small mixture changes can affect the transition temperature and the freezing/melting behaviors. The phase composition at the solid state was elucidated and a new phase of NaBr was identified and its lattice parameters were obtained by XRPD. DSD and DSI resulted complementary to traditional DSC data with many potential applications in solid state chemistry and materials science.

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