Dissemin is shutting down on January 1st, 2025

Published in

Wiley, X-Ray Spectrometry, 6(52), p. 371-377, 2023

DOI: 10.1002/xrs.3341

Links

Tools

Export citation

Search in Google Scholar

XRFitProc: A novel web‐based x‐ray fluorescence fitting system

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

AbstractX‐ray fluorescence (XRF) spectroscopy is a widely used technique in microscopy, spanning from biology to cultural heritage applications. Its purpose is to characterize qualitatively and quantitatively, the presence of elemental species in a sample. This is accomplished through fitting the acquired data to a Gaussian model, identifying which XRF lines and associated elements are present. As a result, 2D images of cumulative count‐rate maps associated with each element are produced. This procedure is not trivial to apply efficiently in a workflow, as it requires the user to be able to set a series of parameters (e.g., beam energy, background subtraction, etc.) on top of selecting XRF lines under investigation. Furthermore, users should easily and swiftly be able to change setup parameters and evaluate the effects on the results. In the present work, we introduce a web‐based application that allows users to load the XRF data, setup a fit and inspect the results interactively within a simple graphical user interface (GUI) that enables easily going back and forth from setup to result inspection. In particular, it is possible to quickly view the count‐rate maps and curve fitting simultaneously, on any single pixel spectra present in the images. The web‐application can be accessed locally by a web‐browser, but runs remotely on a cloud, freeing from the need of installing any software and will be made publicly available in the near future. At present, it has been designed to work on both conventional and sparse XRF data such as Compressive Sensing, in an embarrassingly parallel manner.