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

MinSight, www.minsight.org, is presented as a new approach to read, fit, and interpret Mössbauer spectroscopy (MBS) data by combining dynamically evolving databases with interactive features. MBS is used to determine the oxidation state, coordination environment, and mineral composition of materials from a wide range of scientific disciplines and industry. Nevertheless, the analysis and interpretation of MBS 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 meta data such as measurement temperature, type (e.g. thin film, powder), or collection environment (e.g. synthetic, sediment, soil, etc.). Once data is uploaded the analysis page provides options to visualise and fit data using standard models (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.