A Simulation Independent Analysis of Single- and Multi-Component cw ESR Spectra

Abstract

The accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understanding their structure–function relationships and electrochemical properties. The current methods of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly/partially resolved and unresolved spectra, which is common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper–nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

Time-Frequency Analysis of Two-Dimensional Electron Spin Resonance Signals

“…Wavelet transforms are powerful methods for time-frequency analysis due to their flexible window length and applicability to multi-dimensional signals. The advantages of using wavelet-based spectral analysis in both ESR and nuclear magnetic resonance (NMR) spectroscopic studies in one-dimensional experiments have been established, − where one can reliably decouple different spectral components, including noise, in separating individual peaks. In this work, we present a 2D undecimated discrete wavelet transform , (UDWT)-based approach that can effectively identify and separate overlapping peaks in 2D ESR signals.…”