MinSight – a new concept for fitting and interpreting Mössbauer spectroscopy data

Abstract MinSight, www.minsight.org , is presented as a new approach to read, fit, and interpret Mössbauer spectroscopy (MS) data by combining dynamically evolving databases with interactive features. MS is used to determine the oxidation state, coordination environment of iron, as well as the phase composition of materials across a wide range of scientific disciplines and industry. Nevertheless, the analysis and interpretation of MS data can prove complicated, especially to novices in the field. MinSight is unique compared to other Mössbauer software in its offering of a browser-based approach to fitting spectra. It has been built using Python, with Streamlit providing the web interface and Firebase handling data storage. Data can be uploaded in a file management system which also includes the ability to create many different projects, each of which may contain multiple spectra. Simple annotations prompt users to provide basic metadata such as the temperature, geometry (e.g. thin film, powder) and origin (e.g. synthetic, sediment, soil, etc.). Once data is uploaded the analysis page provides options to visualise and fit data using standard fitting routines (i.e. Lorentzian, Squared Lorentzian, Voigt, and extended Voigt). What distinguishes MinSight from other software are its additional features including the ability to “discover” parameter guesses based upon published literature. Users have the ability to directly compare their spectra against a spectral library, with a score ranking their similarity. If there is a satisfactory match, the parameters from the publication can be imported and used for fitting new data. This feature provides a starting point for complex spectra such as those from environmental soils and sediments, and enables users to quickly access relevant publications which may help in their interpretations. Parameter correlation plots (e.g. isomer shift vs. quadrupole splitting), help users to visually inspect if sites fall within acceptable limits or need further refinement. Parameters are also matched against a hyperfine parameter database for sample identification. With the possibility of loading multiple spectra within a project, more widespread comparisons can be made including for relative abundances, which are compared in a bar plot and update automatically. By embedding the software into a web browser users also gain flexibility to login to their accounts, upload and store data on a server, and access it from any device, including mobile. Collaborative tools also allow users to share their data with project partners, enhancing teamwork.

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Publication Details

Journal
Interactions
Published
2025-11-06
DOI
https://doi.org/10.1007/s10751-025-02331-7
Primary Topic
Iron oxide chemistry and applications
Type
article
Field-Weighted Citation Impact
0.00

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article

MinSight – a new concept for fitting and interpreting Mössbauer spectroscopy data

James M. Byrne
Interactions
Iron oxide chemistry and applications
article

MinSight – a new concept for fitting and interpreting Mössbauer spectroscopy data

James M. Byrne
article en

Abstract

Abstract MinSight, www.minsight.org , is presented as a new approach to read, fit, and interpret Mössbauer spectroscopy (MS) data by combining dynamically evolving databases with interactive features. MS is used to determine the oxidation state, coordination environment of iron, as well as the phase composition of materials across a wide range of scientific disciplines and industry. Nevertheless, the analysis and interpretation of MS data can prove complicated, especially to novices in the field. MinSight is unique compared to other Mössbauer software in its offering of a browser-based approach to fitting spectra. It has been built using Python, with Streamlit providing the web interface and Firebase handling data storage. Data can be uploaded in a file management system which also includes the ability to create many different projects, each of which may contain multiple spectra. Simple annotations prompt users to provide basic metadata such as the temperature, geometry (e.g. thin film, powder) and origin (e.g. synthetic, sediment, soil, etc.). Once data is uploaded the analysis page provides options to visualise and fit data using standard fitting routines (i.e. Lorentzian, Squared Lorentzian, Voigt, and extended Voigt). What distinguishes MinSight from other software are its additional features including the ability to “discover” parameter guesses based upon published literature. Users have the ability to directly compare their spectra against a spectral library, with a score ranking their similarity. If there is a satisfactory match, the parameters from the publication can be imported and used for fitting new data. This feature provides a starting point for complex spectra such as those from environmental soils and sediments, and enables users to quickly access relevant publications which may help in their interpretations. Parameter correlation plots (e.g. isomer shift vs. quadrupole splitting), help users to visually inspect if sites fall within acceptable limits or need further refinement. Parameters are also matched against a hyperfine parameter database for sample identification. With the possibility of loading multiple spectra within a project, more widespread comparisons can be made including for relative abundances, which are compared in a bar plot and update automatically. By embedding the software into a web browser users also gain flexibility to login to their accounts, upload and store data on a server, and access it from any device, including mobile. Collaborative tools also allow users to share their data with project partners, enhancing teamwork.

InteractionsVol. 246(1)
University of Bristol (GB)
UK Research and Innovation
Openalex Percentile: Top 77%
Iron oxide chemistry and applications
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