Peter F. Peterson

The pyRS (Python residual stress) analysis software was designed to address the data reduction and analysis needs of the High Intensity Diffractometer for Residual Stress Analysis (HIDRA) user community. pyRS implements frameworks for the calibration and reduction of measured 2D data into intensity versus scattering vector magnitude and subsequent single-peak-fitting analysis to facilitate texture and residual strain/stress analysis. pyRS components are accessible as standalone user interfaces for peak-fitting and stress/strain analysis or as Python scripts. The scripting interface facilitates automated data reduction and peak-fitting analysis using an autoreduction protocol. Details of the implemented functionality are discussed.

Errors and ambiguities in the article by Peterson, Olds, McDonnell & Page [J. Appl. Cryst. (2021), 54, 317–332] are corrected and clarified, respectively.

The total scattering method is the simultaneous study of both the real- and reciprocal-space representations of diffraction data. While conventional Bragg-scattering analysis (employing methods such as Rietveld refinement) provides insight into the average structure of the material, pair distribution function (PDF) analysis allows for a more focused study of the local atomic arrangement of a material. Generically speaking, a PDF is generated by Fourier transforming the total measured reciprocal-space diffraction data (Bragg and diffuse) into a real-space representation. However, the details of the transformation employed and, by consequence, the resultant appearance and weighting of the real-space representation of the system can vary between different research communities. As the worldwide total scattering community continues to grow, these subtle differences in nomenclature and data representation have led to conflicting and confusing descriptions of how the PDF is defined and calculated. This paper provides a consistent derivation of many of these different forms of the PDF and the transformations required to bridge between them. Some general considerations and advice for total scattering practitioners in selecting and defining the appropriate choice of PDF in their own research are presented. This contribution aims to benefit people starting in the field or trying to compare their results with those of other researchers.

The neutron powder diffractometer POWGEN at the Spallation Neutron Source has recently (2017–2018) undergone an upgrade which resulted in an increased detector complement along with a full overhaul of the structural design of the instrument. The current instrument has a solid angular coverage of 1.2 steradians and maintains the original third-generation concept, providing a single-histogram data set over a wide d-spacing range and high resolution to access large unit cells, detailed structural refinements and in situ/operando measurements.

Characterizing the structural response of functional materials (e.g., piezoelectrics and ferroelectrics) to electric fields is key for the creation of structure-property relationships. Here, we present a new sample environment and data reduction routines which allow the measurement of time-of-flight neutron total scattering during the in situ or ex situ application of high voltage (1/2Bi_1/2TiO₃ and observe lattice expansion parallel and contraction perpendicular to the electric field for both in situ and ex situ experiments, revealing the irreversible nature of the local scale structural changes to this composition. Additionally, changes in the distributions of nearest neighbor metal-oxygen bond lengths are observed, which have been difficult to observe in previously measured analogous orientation-dependent X-ray PDFs. Considerations related to sample positioning and background subtraction are discussed, and future research directions are suggested.

This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Finally, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.