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processing:complex-multi-phase

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In the works: indexing a complex dataset with many phases

When you have sample with multiple phases, your list of extracted experimental g-gvectors (the bottom section of your GVE file, see example at the link) includes vectors that could originate from all phases in your sample.

Here is how we proceed:

  • First work on our list of g-vectors to identify our phases and peaks,
  • Generate custom GVE files for each phase we will work on,
  • Run series of indexings, one phase after another, and multiple times.

Identify phases and peaks

One of the most critical tasks of this work is to know what you are looking for. In our case, we typically have

  • 2 or more sample phases, often with complex structures and many peaks,
  • a pressure medium, often a simple cubic phase, with one peak.

To do so, it is much better to work on an 2θ-histogram of the experimental g-vectors.

The figure on the left shows an example from Gay et al Earth and Planetary Science Letters 604 (2023) [doi: 10.1016/j.epsl.2023.118015]. The sample holds 4 sample phases and a pressure medium (KCl). Top image is an ω-stack for all experimental g-vectors, potted as a function of ds and η. The bottom image is what you get if you try to index an average diffraction image directly. The middle panel is what is extracted from a 2θ-histogram of the experimental g-vectors.

The histogram is less affected by very large grains (the pressure medium in our case). In addition, experimental peak broadening, due to the experiment or the sample properties such as grain size or microstrains, have been removed since we only consider the center of mass of eack peak.

You can then use your favorite powder diffraction software, such as PDIndexer or MAUD to identify sample phases and their unit cell parameters. Just keep in mind that peak intensities in the histograms are not true intensities, but a number of experimental g-vectors.

processing/complex-multi-phase.1702196263.txt.gz · Last modified: 2023/12/10 08:17 by smerkel