A cloud platform for atomic pair distribution function analysis: PDFitc
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.
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF); European Research Council (ERC)
- OSTI Identifier:
- 1712789
- Alternate Identifier(s):
- OSTI ID: 1787487
- Grant/Contract Number:
- AC05-00OR22725; DMREF-1534910; 804066
- Resource Type:
- Published Article
- Journal Name:
- Acta Crystallographica. Section A, Foundations and Advances (Online)
- Additional Journal Information:
- Journal Name: Acta Crystallographica. Section A, Foundations and Advances (Online) Journal Volume: 77 Journal Issue: 1; Journal ID: ISSN 2053-2733
- Publisher:
- International Union of Crystallography (IUCr)
- Country of Publication:
- Denmark
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; pair distribution function; PDF; data analysis; web applications; cloud computing
Citation Formats
Yang, Long, Culbertson, Elizabeth A., Thomas, Nancy K., Vuong, Hung T., Kjær, Emil T. S., Jensen, Kirsten M. Ø., Tucker, Matthew G., and Billinge, Simon J. L. A cloud platform for atomic pair distribution function analysis: PDFitc. Denmark: N. p., 2021.
Web. doi:10.1107/S2053273320013066.
Yang, Long, Culbertson, Elizabeth A., Thomas, Nancy K., Vuong, Hung T., Kjær, Emil T. S., Jensen, Kirsten M. Ø., Tucker, Matthew G., & Billinge, Simon J. L. A cloud platform for atomic pair distribution function analysis: PDFitc. Denmark. https://doi.org/10.1107/S2053273320013066
Yang, Long, Culbertson, Elizabeth A., Thomas, Nancy K., Vuong, Hung T., Kjær, Emil T. S., Jensen, Kirsten M. Ø., Tucker, Matthew G., and Billinge, Simon J. L. Tue .
"A cloud platform for atomic pair distribution function analysis: PDFitc". Denmark. https://doi.org/10.1107/S2053273320013066.
@article{osti_1712789,
title = {A cloud platform for atomic pair distribution function analysis: PDFitc},
author = {Yang, Long and Culbertson, Elizabeth A. and Thomas, Nancy K. and Vuong, Hung T. and Kjær, Emil T. S. and Jensen, Kirsten M. Ø. and Tucker, Matthew G. and Billinge, Simon J. L.},
abstractNote = {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.},
doi = {10.1107/S2053273320013066},
journal = {Acta Crystallographica. Section A, Foundations and Advances (Online)},
number = 1,
volume = 77,
place = {Denmark},
year = {Tue Jan 05 00:00:00 EST 2021},
month = {Tue Jan 05 00:00:00 EST 2021}
}
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