PyMossFit: A Google Colab Option for Mössbauer Spectra Fitting

This article introduces the main characteristics of PyMossFit, a software for Mössbauer spectra fitting. It is explained how each aspect of the code works. Based on the Lmfit Python package, it is a robust data fitting tool. Designed to run through Jupyter Notebook in the Google Colab cloud, it also allows one to work via multiple devices and operating systems. In addition, it allows the fitting procedure to be performed collaboratively among researchers. The software performs the folding of raw data with a discrete Fourier transform. Data smoothing is available with the use of a Savitzky–Golay algorithm. Moreover, a K-nearest neighbor algorithm enables users to determine the present phases by matching the correlations of hyperfine parameters from a local database.

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Publication Details

Journal
Spectroscopy Journal
Published
2025-11-04
DOI
https://doi.org/10.3390/spectroscj3040029
Citations
1
Primary Topic
Crystallography and Radiation Phenomena
Type
article
Field-Weighted Citation Impact
1.26

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article

PyMossFit: A Google Colab Option for Mössbauer Spectra Fitting

F.D. Saccone
1 citations
Spectroscopy Journal
Crystallography and Radiation Phenomena
1.26
article

PyMossFit: A Google Colab Option for Mössbauer Spectra Fitting

F.D. Saccone
article en
1 citations

Abstract

This article introduces the main characteristics of PyMossFit, a software for Mössbauer spectra fitting. It is explained how each aspect of the code works. Based on the Lmfit Python package, it is a robust data fitting tool. Designed to run through Jupyter Notebook in the Google Colab cloud, it also allows one to work via multiple devices and operating systems. In addition, it allows the fitting procedure to be performed collaboratively among researchers. The software performs the folding of raw data with a discrete Fourier transform. Data smoothing is available with the use of a Savitzky–Golay algorithm. Moreover, a K-nearest neighbor algorithm enables users to determine the present phases by matching the correlations of hyperfine parameters from a local database.

Spectroscopy JournalVol. 3(4)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Universidad de Buenos Aires (AR), National Institute of Industrial Technology (AR)
Comisión Nacional de Energía Atómica, Gobierno de Argentina, Consejo Nacional de Investigaciones Científicas y Técnicas
Openalex Percentile: Top 16%
Crystallography and Radiation Phenomena
1.26
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PyMossFit: A Google Colab Option for Mössbauer Spectra Fitting — F.D. Saccone · Spectroscopy Journal (2025) | TGRS Research Map | TGRS