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Worldwide research activity at the nanoscale is triggering the appearance of new, and frequently surprising, materials properties in which the increasing importance of surface and interface effects plays a fundamental role. This opens further possibilities in the development of new multifunctional materials with tuned physical properties that do not arise together at the bulk scale. Unfortunately, the standard methods currently available for solving the atomic structure of bulk crystals fail for nanomaterials due to nanoscale effects (very small crystallite sizes, large surface-to-volume ratio, near-surface relaxation, local lattice distortions etc.). As a consequence, a critical reexamination of the available local-structure characterization methods is needed. This work discusses the real possibilities and limits of X-ray absorption spectroscopy (XAS) analysis at the nanoscale. To this end, the present state of the art for the interpretation of extended X-ray absorption fine structure (EXAFS) is described, including an advanced approach based on the use of classical molecular dynamics and its application to nickel oxide nanoparticles. The limits and possibilities of X-ray absorption near-edge spectroscopy (XANES) to determine several effects associated with the nanocrystalline nature of materials are discussed in connection with the development of ZnO-based dilute magnetic semiconductors (DMSs) and iron oxide nanoparticles.

In this study we have investigated the influence of hydrogen intercalation on the local atomic structure of rhenium trioxide using a new approach to EXAFS data analysis, based on the evolutionary algorithm (EA). The proposed EA-EXAFS method is an extension of the conventional reverse Monte Carlo approach but is computationally more efficient. It allows one to perform accurate analysis of EXAFS data from distant coordination shells, taking into account both multiple-scattering and disorder (thermal and static) effects. The power of the EA-EXAFS method is first demonstrated on an example of the model system, pure ReO3, and then it is applied to an in situ study of hydrogen bronze HxReO3 upon hydrogen intercalation. The obtained results allow us to detect changes in the lattice dynamics and correlation of atomic motion, and to follow the structural development at different stages of the reaction.

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The knowledge of the coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use an artificial neural network approach to extract the information on the local structure and its in situ changes directly from the x-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic and austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from a body-centered to a face-centered cubic arrangement of iron atoms. This method is attractive for a broad range of materials and experimental conditions.