Nanometre distance measurements between spin labels by pulse EPR techniques yield structural information on the molecular level. Here, backed by experimental data, we derive a description for the total signal of the single-frequency technique for refocusing dipolar couplings (SIFTER), showing how the different spin–spin interactions give rise to dipolar signal and background – the latter has thus far been unknown.

Recent advances in machine learning have opened new opportunities toward the automated analysis and spectral reconstruction of highly complex NMR spectra, including ones encountered in metabolomics. We demonstrate the combined power of the deep neural network DEEP Picker 1D and the Voigt Fitter1D software for the quantitative streamlined analysis of 1D 1H NMR spectra, extending the reach of a wide range of NMR applications.

Light-induced pulsed dipolar EPR spectroscopy (PDS) is an emerging field that uses photoexcited triplet states to determine distance restraints in the nanometer range. To date, light-induced PDS data have been analyzed with methods developed for techniques that do not invoke light-induced triplets. Here, we provide a new theoretical description that takes the full nature of the triplet state into account and demonstrate that it leads to more accurate fits of experimental data.

In this work, we study the relaxivity of long-lived states (LLSs) excited across two to three CH₂ groups in four different compounds and find that a commonly used polarising agent in dissolution dynamic nuclear polarization (d-DNP) does not enhance relaxation significantly. This result is important for the future implementation of d-DNP hyperpolarization of LLS.

The 20 genetically encoded amino acids provide the basis for most proteins and peptides that make up the machinery of life. This limited repertoire is vastly expanded by the introduction of non-canonical amino acids (ncAAs). Studying the structure of protein-containing ncAAs requires new computational representations that are compatible with existing modelling software. We have developed an online tool for this to aid future structural studies of this class of complex biopolymer.

Diffusion MRI is a clinically important tool for noninvasive detection of pathological conditions that lead to microscopic changes in cell and tissue structures, but this technique suffers from interpretational ambiguities when applied to heterogeneous and disordered tissues comprising cells with multiple sizes, shapes, and orientations. We propose a simple scheme to encode the MRI signal with a sufficient amount of information to resolve and study all properties simultaneously.

This tutorial paper shows how to simulate NMR spectra at zero to ultralow fields. The process is presented in detail, including the tricks that are usually omitted from research papers and assuming as little prior knowledge from the reader as possible. In this attempt to make NMR simulation approachable, the authors wish to pay tribute to the late Prof. Konstantin L’vovich Ivanov.

R-proton-detected local-field NMR is a powerful method to obtain structural information from biological membrane models. However, the conventional analysis of experiments, by using a Fourier transform in the indirect time-domain and reading-off splittings, is unsuitable to investigate complex systems. One then needs to model the experimental data. Fitting the experimental data with simulations that account for radiofrequency field inhomogeneity enables accurate modeling of R-PDLF data.

Since its discovery 65 years ago, the solid-state dynamic nuclear polarization effect has been rationalized in terms of mixing of the Zeeman energy levels. Before becoming aware of this explanation, Erb, Motchane and Uebersfeld proposed a dynamical equation to make sense of their experiments. Here we provide a formal justification of their phenomenological equation. The result is a different way of thinking about the solid-state effect, with novel implications for the effect in liquids.

We show that the field profile of the solid effect in liquids is rich in dynamical information, including about timescales of molecular diffusion. We develop a general theoretical framework for extracting this information through quantitative fits to the experimental data. Unusual peaks in the enhancement field profile, which resemble thermal mixing but are not related to it, are demonstrated to arise in liquids under some conditions. These additionally restrict the dynamical parameters.