Noise reduction and peak detection in x-ray diffraction data by linear and nonlinear methods

Abstract

Considerable progress has been made in the last few years in removing white noise from visible–near-ultraviolet (UV/VIS) spectra while leaving information intact. For x-ray diffraction, the challenges are different: detecting and locating peaks rather than line shape analysis. Here, we investigate possibilities of state-of-the-art UV/VIS methods for noise reduction, peak detection, and peak location applied to x-ray diffraction data, in this case, data for a ZrO2 −33 mol. % TaO4 ceramic. The same advantages seen in UV/VIS spectroscopy are found here as well.