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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 06, 2023
Source ID
10.1116/6.0002526

Entities

People

  • David E. Aspnes
  • H.N.G. Wadley
  • Jeroen A. Deijkers
  • Long V. Le
  • Young Dong Kim

Organizations

  • Institute of Materials Science
  • Kyung Hee University
  • National Research Foundation of Korea
  • North Carolina State University
  • Office of Naval Research
  • University of Virginia
  • Vietnam Academy of Science and Technology

Tags

Readers

  • Approximation Theory.
  • Electrochemical Engineering/ Fuel Cell Technologies
  • Systems Analysis and Design