Engineering of thermoelectric materials requires an understanding of thermal conduction by lattice and electronic degrees of freedom. Filled skutterudites denote a large family of materials suitable for thermoelectric applications where reduced lattice thermal conduction attributed to localized lowfrequency vibrations (rattling) of filler cations inside large cages of the structure. In this work, a multiwavelength method of exploiting X-ray dynamical diffraction in single crystals of CeFe 4 P 12 is presented and applied to resolve the atomic amplitudes of vibrations. The results suggest that the vibrational dynamics of the whole filler-cage system is the actual active mechanism behind the optimization of thermoelectric properties.
PyDDT is a free Python package of computer codes for exploiting X-ray dynamic multiple diffraction in single crystals. A wide range of tools are available for evaluating the usefulness of the method, planning feasible experiments, extracting phase information from experimental data and further improving model structures of known materials. Graphical tools are also useful in analytical methodologies related to the three-dimensional aspect of multiple diffraction. For general X-ray users, the PyDDT tutorials provide the insight needed to understand the principles of phase measurements and other related methodologies. Key points behind structure refinement using the current approach are presented, and the main features of PyDDT are illustrated for amino acid and filled skutterudite single crystals.
In nowadays, X-ray diffraction and scattering phenomena are widely used as analytical tools in the optimization and control of nanomaterial synthesizing processes. In systems of monocrystalline nanoparticles with size distribution, the physical meaning of size values as determined by using Xray methods is still controvertial. To answer such fundamental issue, series of virtual nanoparticles with sizes ranging from 1 nm to 90 nm were generated and their exact scattering power computed via pair distance distribution function. Composed X-ray diffraction and scattering patterns from systems of virtual nanoparticles demonstrated that diffraction and scattering phenomena see the size distributions with different weightings. Therefore, combining both phenomena leads to the determination of size distribution in the systems. In practice, X-ray diffraction and small-angle scattering experiments were applied to solve the size distributions in a series of samples of cubic ceria nanoparticles, revealing a systematic size dispersion as a function of synthesis parameters.
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