# X-ray Diffraction Data Analysis by Machine Learning Methods--A Review
## 1 Introduction
### Applications of XRD Data Analysis  
XRD data analysis is of paramount importance for many scientific and industrial applications. This section highlights the significance of XRD data analysis and its role in advancing materials science, research, and technology.  
One of the primary objectives of XRD data analysis, whether acquired on single crystals or polycrystalline samples, is the determination of crystal structure. Thus, the technique is used for the identification of the arrangements of atoms within crystalline materials in terms of lattice parameters, unit-cell dimensions, crystal symmetry and subsequent space group. As emphasized in a paper by [PERSON] [63], the mechanical behavior of solid materials is strongly connected to the crystal structure; consequently, by controlling the processing parameters for obtaining a desired structure, the compressive strength of a material might be controlled.  
XRD data analysis enables the identification of different phases in a sample. The set of \(d\) lattice spacings and corresponding \(I\) (intensity) values are characteristic for a material like a fingerprint is for a human [62]. Moreover, many materials can exist in various crystallization systems (polymorphic forms) and can undergo phase transformations under different temperature or pressure conditions. Identifying the phases accurately is crucial for ensuring material purity, assessing the success of synthesis processes, and characterizing complex multiphase materials.  
Quantitative phase analysis allows researchers to determine the relative abundance of different phases in a sample. This determination is useful for various materials, such as cement, ceramics, steel, alloys, electronic materials, and composite materials. In the cement industry, the quantitative phase analysis of clinker provides information for the control of kiln parameters, whereas the analysis of Portland cement provides the quality assessment of the finished product [64]. In the case of traditional ceramics, the abundance of phases and the evaluation of the crystallinity degree is decisive for establishing the thermal processing parameters [65]. Assessing the phase fraction of zirconia polymorphic phases is of great importance in dental ceramics applications for predicting the mechanical behavior of the material [65]. The mechanical behavior of stainless steel is primarily governed by its martensite and austenite content. Even if the material is textured, like in the case of orthodontic wires, assessments can still be made based on X-ray diffraction patterns [66]. In the case of electronic materials, [PERSON] et al. established the crystallization kinetics of PbZr\({}_{1\text{-}}\)Ti\({}_{\text{x}}\)O\({}_{3}\) using an in situ X-ray diffraction study [67].  
XRD data analysis plays a vital role in texture and microstructure characterization. Texture refers to the preferred orientation of crystalline planes in a material, influencing its anisotropic properties. Understanding texture is crucial in fields like metallurgy, where it impacts mechanical properties such as strength and ductility [68]. Additionally, XRD anal ysis provides information on crystallite size, microstrain, and defects, which are essential in assessing material stability and mechanical behavior [69].