🪨 Algorithms for SEM-EDS Mineral Dust Classification

💡 About

A repository of functions for working with SEM-EDS data, with an emphasis on identifying mineral particles.

🚨 NEW: Latest Release Series: eds-classification v2

Click here to access the full release notes.

Brief Summary

• See the updated Documentation (/main/docs/).

• Replacing v1.5.2 and includes significant changes to the repository structure.

• New main functions (/main/src/):

  • Spectrum: A custom MATLAB class for EDS x-ray spectra visualization (replaces xray_plot).
  • msa_classification: A new method for mineral classification that allows you to process spectral data files (.msa / .emsa) directly.
  • eds_read: A custom MATLAB class for reading spectral data files (replacing msa_read).
  • stoich_quant & standard_stoich_quant: Provide methods for standardless quantification and standard quantification of mineral stoichiometries.

• New utility functions (/main/utils/). These functions are designed to work as part of the backend of the new function classes. The main repository functions are written so that the user does not have to learn the utility functions individually, but each function contains its own internal documentation just in case.

Depreciated Functions

• add_xray_plot

• clear_xray_labels

• convergence_angle

• read_msa

• sem_pixel_size

• xray_peak_label

• xray_plot

Previous Updates

1. v1.5 introduced an improved version of the supervised machine learning mineral classification model (weber_classification.m). For details on how the new model was trained, see the contents of the machine_learning_models folder. The training description provided in /Paper/supplement.md is no longer accurate.

2. For the convenience of Julia users, all Julia files have been migrated to https://github.com/weber1158/eds-classification.jl.

📖 Documentation

See the online Documentation for details on each of the algorithms.

⬇️ Installation

You can download the repository from the MATLAB Central File Exchange , or open it directly in your browser (recommended).

To add the EDS Classification functions to the default search path:

1. Un-zip the downloaded folder.

2. Execute the following command in the MATLAB Command Window:

pathtool

3. A popup menu should open. Click Add Folder with Subfolders and select the un-zipped main repository folder.

4. Finalize your chce by clicking Save or Apply.

🎓 How to cite

This repository has been peer-reviewed and published in Journal of Open Source Software. Please use the information below for citing the software:

APA-like

Weber, Austin M., (2025). Algorithms for SEM-EDS mineral dust classification. Journal of Open Source Software, 10(107), 7533, https://doi.org/10.21105/joss.07533

BibTeX:

@article{weber2025,
    author = {Weber, Austin M.},
    title = {Algorithms for {SEM-EDS} mineral dust classification},
    journal = {Journal of Open Source Software},
    volume = {10},
    number = {107},
    pages = {7533},
    year = {2025},
    DOI = {10.21105/joss.07533}
}