Volume 27, Issue 6 pp. 1741-1752
computer programs

THORONDOR: a software for fast treatment and analysis of low-energy XAS data

David Horst Simonne

Corresponding Author

David Horst Simonne

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

David Horst Simonne, e-mail: [email protected]; Andrea Martini, e-mail: [email protected]Search for more papers by this author
Andrea Martini

Corresponding Author

Andrea Martini

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

The Smart Materials Research Center, Southern Federal University, Sladkova 178/24, Rostov-on-Don344090, Russian Federation

David Horst Simonne, e-mail: [email protected]; Andrea Martini, e-mail: [email protected]Search for more papers by this author
Matteo Signorile

Matteo Signorile

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

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Alessandro Piovano

Alessandro Piovano

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

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Luca Braglia

Luca Braglia

CNR-IOM, TASC Laboratory, SS 14 km 163.5, Trieste34149, Italy

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Piero Torelli

Piero Torelli

CNR-IOM, TASC Laboratory, SS 14 km 163.5, Trieste34149, Italy

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Elisa Borfecchia

Elisa Borfecchia

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

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Gabriele Ricchiardi

Gabriele Ricchiardi

Department of Chemistry, INSTM Reference Center and NIS and CrisDi Interdepartmental Centers, University of Torino, Via P. Giuria 7, Torino10125, Italy

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First published: 28 September 2020
Citations: 1

Abstract

THORONDOR is a data treatment software with a graphical user interface (GUI) accessible via the browser-based Jupyter notebook framework. It aims to provide an interactive and user-friendly tool for the analysis of NEXAFS spectra collected during in situ experiments. The program allows on-the-fly representation and quick correction of large datasets from single or multiple experiments. In particular, it provides the possibility to align in energy several spectral profiles on the basis of user-defined references. Various techniques to calculate background subtraction and signal normalization have been made available. In this context, an innovation of this GUI involves the usage of a slider-based approach that provides the ability to instantly manipulate and visualize processed data for the user. Finally, the program is characterized by an advanced fitting toolbox based on the lmfit package. It offers a large selection of fitting routines as well as different peak distributions and empirical ionization potential step edges, which can be used for the fit of the NEXAFS rising-edge peaks. Statistical parameters describing the goodness of a fit such as χ2 or the R-factor together with the parameter uncertainty distributions and the related correlations can be extracted for each chosen model.

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