Development of advanced analysis and simulation programs for EPR spectroscopy

Abstract: In most cases, extracting physical parameters from electron paramagnetic resonance (EPR) spectra requires fitting a model to the experimental data. For complicated spectra governed by several interactions or multiple components, the parameter space can easily become very large, rendering simple gradient-based least-squares fitting approaches insufficient. One strategy to overcome such problems is to simultaneously analyze several experimental data sets of the same sample recorded under different conditions. In this thesis, two analysis approaches for two rather different applications of EPR spectroscopy will be presented: (i) global analysis of pulsed electron-electron double resonance (PELDOR) data, and (ii) a framework for both, global and semi-stochastic analysis of data from a multitude of EPR techniques. The following three major computer program suites for simulating and analyzing EPR data have been developed.

GloPel:
GloPel (global analysis of PELDOR data), available as Python-based cross-platform GUI application, provides a comprehensive PELDOR data processing and analysis framework supporting global analysis. Tikhonov regularization as well as multi-Gaussian fitting models are implemented. The user-friendly GUI application offers spectra processing, fast data analysis, and validation tools to avoid a potential misinterpretation of the data. As a proof of concept, global analysis has been employed to simulated PELDOR time traces. Furthermore, its applicability is demonstrated on experimental PELDOR data obtained from the ammonia transporter AMT-1 from Archaeoglobus fulgidus.

SpecProFi:
SpecProFi (spectra processing and fitting) is a MATLAB-based comprehensive EPR data processing and fitting framework, that provides sophisticated analysis tools including the global analysis of multiple experimental data sets combined with a semi-stochastic search for optimized parameter sets. For example, cw-EPR measurements recorded at multiple microwave frequencies, cw-EPR and ENDOR spectra, orientation-selective ENDOR measurements recorded at different magnetic-field positions, multiple harmonics, or liquid-state and solid-state cw-EPR data can be modeled jointly. SpecProFi relies on the well-established and powerful EasySpin simulation package and uses the corresponding syntax, thus making it easy to use. Besides the fitting framework, SpecProFi provides various functions for data processing, such as denoising methods, automatic phase-correction for cw-EPR data, or differentiation of absorptive EPR data using Tikhonov regularization. Using simulated cw-EPR data, global analysis is demonstrated to be superior compared to single analysis. Furthermore, SpecProFi has been employed to analyze several experimental data sets, including orientation-dependent W-band ENDOR data and multi-frequency cw-EPR spectra.

SolidSim and FastMotion:
Implementing a Python-based EPR data processing and fitting framework requires the development of EPR simulation routines. Therefore, cw-EPR simulation programs were developed to simulate solid-state EPR spectra (SolidSim) and EPR spectra recorded in the fast-motion regime (FastMotion). SolidSim can be used for simulations of spectra recorded at thermal equilibrium as well as of spin-polarized spectra. Furthermore, it can be extended to the simulation of spin-correlated radical pair spectra. In future, the concepts of SpecProFi will be transferred to Python to create a comprehensive processing and analysis framework, using the Python-based EPR simulation infrastructure (SolidSim and FastMotion)

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch
• Notes: Universität Freiburg, Dissertation, 2019

Classification and Topics

• Keyword: Elektronenspinresonanz ; Datenanalyse

Contributors, Places and Time

• Event: Veröffentlichung
• (where): Freiburg
• (who): Universität
• (when): 2019
• Creator: Rein, Stephan
• Contributor: Weber, Stefan ; Timmel, Christiane R. ; Albert-Ludwigs-Universität Freiburg. Fakultät für Chemie und Pharmazie

Further information

• DOI: 10.6094/UNIFR/149616
• URN: urn:nbn:de:bsz:25-freidok-1496169
• Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 10:50 AM CEST