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One of the advantages of a multidetector neutron time-of-flight diffractometer such as the high pressure preferred orientation diffractometer (HIPPO) at the Los Alamos Neutron Science Center is the capability to measure efficiently preferred orientation of bulk materials. A routine experimental method for measurements, both at ambient conditions, as well as high or low temperatures, has been established. However, only recently has the complex data analysis been streamlined to make it straightforward for a noninitiated user. Here, we describe the Rietveld texture analysis of HIPPO data with the computer code Materials Analysis Using Diffraction (MAUD) as a step-by-step procedure and illustrate it with a metamorphic quartz rock. Postprocessing of the results is described and neutron diffraction results are compared with electron backscatter diffraction measurements on the same sample.

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The evolution of the Li-ion displacements in the 3D interstitial pathways of the cubic garnet-type Li(7)La(3)Zr(2)O(12), cubic Li(7)La(3)Zr(2)O(12), was investigated with high-temperature neutron diffraction (HTND) from RT to 600 °C; the maximum-entropy method (MEM) was applied to estimate the Li nuclear-density distribution. Temperature-driven Li displacements were observed; the displacements indicate that the conduction pathways in the garnet framework are restricted to diffusion through the tetrahedral sites of the interstitial space.

In this paper we describe the capabilities for texture measurements of the new neutron time-of-flight diffractometer HIPPO at the Los Alamos Neutron Science Center. The orientation distribution function (ODF) is extracted from multiple neutron time-of-flight histograms using the full-pattern analysis first described by Rietveld. Both, the well-established description of the ODF using spherical harmonics functions and the WIMV method, more recently introduced for the analysis of time-of-flight data, are available to routinely derive the ODF from HIPPO data. At ambient conditions, total count time of less than one hour is ample to collect sufficient data for texture analysis in most cases. The large sample throughput for texture measurements at ambient conditions possible with HIPPO requires a robust and reliable, semi-automated data analysis. HIPPO’s unique capabilities to measure large quantities of ambient condition samples and to measure texture at temperature and uni-axial stress are described. Examples for all types of texture measurements are given