ESR-Analyses

MATLAB scripts to analyse cw-ESR data. ESR-Analyses requires the natural constants package.

If you publish any data processed with the ESR-Analyses routines, please cite Schott, S. et al. Nat. Phys. 15, 814–822 (2019) where the methods implemented here have been first published.

About

ESR-Analyses is structured as a package, to avoid name space conflicts with other toolboxes such as easyspin. Once downloaded, please rename the top level folder to "+esr_analyses". You can then access all functions by prepending esr_analyses, for example as esr_analyses.lorentzian, or after importing all functions from the package with import esr_analyses.*. An introduction to MATLAB packages is given here.

ESR-Analyses is composed of:

1. General utility functions which are useful in an ESR context:

   • Functions for common resonance lineshapes: lorentzian, gaussian, etc.
   • Utility functions for common conversions: b2g (converts magnetic field to g-factor), chi2nspin (converts susceptibility to number of spins), etc.
   • Functions to simulate ESR spectra: field_mod_sim, ESRLorentzSimulation, etc.

2. Functions to read and manipulate Bruker Xepr data files:

   • BrukerRead to read Xepr data files and return the measurement data as well all measurement parameters.
   • Functions to process the data: normalise_spectrum, subtract_background, baseline_corr, etc.

3. Functions to analyse cw-ESR data:

   • Low-level functions for specific tasks: gfactor_determination, double_int_num, spin_counting, etc.
   • High-level functions: PowerSatAnalysesLorentzFit, PowerSatAnalysesVoigtFit, etc.

All functions do exactly what you would expect from their name, and most of them are well documented. Therefore, please refer to the individual doc-strings for more information.

Requirements:

• The latest version of Matlab is recommended (Matlab 2020b as of writing)
• Image Processing Toolbox
• Curve Fitting Toolbox
• Statistics and Machine Learning Toolbox