Application of the HLSVD technique to the filtering of X-ray diffraction data

A filter based on the Hankel Lanczos Singular Value Decomposition (HLSVD) technique is presented and applied for the first time to X-ray diffraction (XRD) data. Synthetic and real powder XRD intensity profiles of nanocrystals are used to study the filter performances with different noise levels. Results show the robustness of the HLSVD filter and its capability to extract easily and efficiently the useful crystallographic information. These characteristics make the filter an interesting and user-friendly tool for processing XRD data.Comment: 10 pages, 3 tables, 6 figure

Model independent pre-processing of X-ray powder diffraction profiles

Precise knowledge of X-ray diffraction profile shape is crucial in the investigation of the properties of matter in crystals powder. Line-broadening analysis is a pre-processing step in most of the full powder pattern fitting softwares. Final result of line-broadening analysis strongly depends on preliminary three steps: Noise filtering, removal of background signal and peak fitting. In this work a new model independent procedure for two of the aforementioned steps (background suppression and peak fitting) is presented. The former is dealt with by using morphological mathematics, while the latter relies on the Hankel Lanczos Singular Value Decomposition technique. Real X-ray powder diffraction (XRPD) intensity profiles of Ceria samples are used to test the performance of the proposed procedure. Results show the robustness of this approach and its capability of efficiently improving the disentangling of instrumental broadening. These features make the proposed approach an interesting and user-friendly tool for the pre-processing of XRPD data.Comment: 14 pages, 3 figures, 2 table