Concept

Typical data processing in a diffraction experiment consists of three main steps:
data acquisition, data reduction, and data analysis.

flowchart LR
    a(Data Aquisition)
    b(Data Reduction)
    c(Data Analysis)
    a --> b
    b --> c

Data Acquisition

Data acquisition involves collecting raw data from the diffractometer (also referred to as the instrument) during a neutron or X-ray diffraction experiment.

The data is recorded by a detector that measures the intensity of the diffracted radiation as a function of angle or time. The radiation is scattered by the crystalline specimen (also called the sample), whose structural properties are being studied.

An illustration of the data acquisition step, where raw data is collected by a 2D detector. The studied sample originates from Mars. Credits: DOI 10.1126/science.1238932

A 2D diffraction pattern collected by the detector. Credits: DOI 10.1126/science.1238932

Data Reduction

Data reduction involves processing the raw data to remove background noise, correct for instrumental effects, and convert the data into a more usable format. The goal is to produce a clean and reliable dataset suitable for analysis.

An illustration of a 1D diffraction pattern reduced from the measured 2D data. Credits: DOI 10.1126/science.1238932

Data Analysis

Data analysis uses the reduced data to extract meaningful information about the sample. This may include determining the crystal or magnetic structure, identifying phases, performing quantitative analysis, etc.

Analysis often involves comparing experimental data with data calculated from a crystallographic model to validate and interpret the results. For powder diffraction, techniques such as Rietveld or Le Bail refinement may be used.

In EasyDiffraction, we focus on this model-dependent analysis. A model is built using prior knowledge of the system, and its parameters are optimized to achieve the best agreement between experimental and calculated diffraction data.

By "model", we usually refer to a crystallographic model of the sample. This includes unit cell parameters, space group, atomic positions, thermal parameters, and more. However, the term "model" also encompasses experimental aspects such as instrumental resolution, background, peak shape, etc. Therefore, EasyDiffraction separates the model into two parts: the sample model and the experiment.

The aim of data analysis is to refine the structural parameters of the sample by minimizing the difference (or residual) between the experimental and calculated data — and this is exactly where EasyDiffraction comes into play.