Multivariate versus traditional quantitative phase analysis of X-ray powder diffraction and fluorescence data of mixtures showing preferred orientation and microabsorption.

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 Biobased Coatings for AM60 Magnesium Alloys for Food Contact and Harsh Environment Applications.

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.

XRF and XRPD data sets in ternary mixtures with high level micro-absorption and/or preferred orientations problems for phase quantification analysis.

Micro-absorption (MA) and/or preferred orientations (PO) are two among the major problems affecting quantitative phase analysis (QPA) by X-ray Powder Diffraction Data (XRPD) in industrial samples such as minerals and ores, additives, cements, friction materials, coal combustion by-products. Typically XRPD data are coupled to elemental analysis by X-ray Fluorescence (XRF) to facilitate phase recognition and quantification when elements heavier than sodium are present. Graphite and urea are typical examples of large production industrial commodities showing such analytical problems. The present article provides a recipe to produce sets of data of increasing difficulty to test the performances of different approaches and/or software's for QPA by XRPD in graphite, zinc acetate and urea containing samples. Graphite, due to its platelet morphology, can exhibit orientation and was chosen because it is possible to control its PO degree by sieving. Simplex-centroid design augmented was used for the design of the experiments to select the mixtures with the more possible homogeneous exploration of the ternary experimental domains, from pure phase to equal-weighted mixtures. The different data sets collected on the four experimental domains by XRF and XRPD are provided and stored as a repository on Mendeley Data. Using the same approach, additional data sets sets with different composition and/or experimental setup can be added by us or any other contributor with the same DoE approach to create a wide open access data set of standardized X-ray powder diffraction and X-ray fluorescence data.