ArticleActa crystallographica. Section A, Foundations and advances2021
A cloud platform for atomic pair distribution function analysis: PDFitc.
Article in Acta crystallographica. Section A, Foundations and advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- The AUREX cell: a versatileJournal of applied crystallography · 2024Article
- Article
- MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions.Digital discovery · 2024Article
- Towards the extraction of the crystal cell parameters from pair distribution function profiles.IUCrJ · 2023Article
- Article
- DeepStruc: towards structure solution from pair distribution function data using deep generative models.Digital discovery · 2023Article
- Structural Analysis of Molecular Materials Using the Pair Distribution Function.Chemical reviews · 2022Review
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8 authors.
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Abstract
A cloud web platform for analysis and interpretation of atomic pair distribution function (PDF) data (PDFitc) is described. The platform is able to host applications for PDF analysis to help researchers study the local and nanoscale structure of nanostructured materials. The applications are designed to be powerful and easy to use and can, and will, be extended over time through community adoption and development. The currently available PDF analysis applications, structureMining, spacegroupMining and similarityMapping, are described. In the first and second the user uploads a single PDF and the application returns a list of best-fit candidate structures, and the most likely space group of the underlying structure, respectively. In the third, the user can upload a set of measured or calculated PDFs and the application returns a matrix of Pearson correlations, allowing assessment of the similarity between different data sets. structureMining is presented here as an example to show the easy-to-use workflow on PDFitc. In the future, as well as using the PDFitc applications for data analysis, it is hoped that the community will contribute their own codes and software to the platform.
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