ArticleJournal of applied crystallography2025
A systematic approach for quantitative orientation and phase fraction analysis of thin films through grazing-incidence X-ray diffraction.
Article in Journal of applied crystallography, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Origin and application of the Lorentz factor in X-ray diffraction.Acta crystallographica. Section A, Foundations and advances · 2026Article
- Overcoming the Limitations of Operando Microscopy and Spectroscopy for Revealing Degradation Mechanisms of Electrocatalysts in Liquid Media: Correlative Approaches.Nano letters · 2026Article
- Microstructural Evolution and Enhanced Macroscopic Properties of La-Doped TiOMicromachines · 2026Article
- 3D electron diffraction-the missing slice completing nanoscale analysis of organic solar cells in TEM.Nature communications · 2026Article
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9 authors.
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Abstract
Grazing-incidence X-ray diffraction (GIXD) is widely used for the structural characterization of thin films, particularly for analyzing phase composition and the orientation distribution of crystallites. While various tools exist for qualitative evaluation, a widely applicable systematic procedure to obtain quantitative information has not yet been developed. This work presents a first step in that direction, allowing accurate quantitative information to be obtained through the evaluation of radial line profiles from GIXD data. An algorithm is introduced for computing radial line profiles based on the crystal structure of known compounds. By fitting experimental data with calculated line profiles, accurate quantitative information about orientation distribution and phase composition is obtained, along with additional parameters such as mosaicity and total crystal volume. The approach is demonstrated using three distinct thin film systems, highlighting the broad applicability of the algorithm. This method provides a systematic and general approach to obtaining quantitative information from GIXD data.
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