Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction

Daniel P. Banco, Eric Miller, Armand Beaudoin, Matthew P. Miller, Kamalika Chatterjee

Research output: Contribution to journalArticlepeer-review


Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.

Original languageEnglish (US)
Pages (from-to)568-586
Number of pages19
JournalIntegrating Materials and Manufacturing Innovation
Issue number4
StatePublished - Dec 2022


  • Convolutional sparse coding
  • Diffraction spot spreading
  • High-energy X-ray diffraction
  • Plasticity
  • Titanium

ASJC Scopus subject areas

  • General Materials Science
  • Industrial and Manufacturing Engineering


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