Thomas Vosegaard

The objective of this work was to establish the peak assignment in liquid state 31P NMR of milk systems and investigate the method as a tool to identify di!erences in casein micelles as consequence of di!erent processing history. Suspensions of milk protein concentrate with removal of casein micelles by EDTA addition and ultra-centrifugation were analyzed by liquid state 31P NMR and compared with the original suspensions. Moreover, 1H-31P total correlation spectroscopy NMR was applied to di!erentiate between peaks from phosphoserines and inorganic phosphate in dairy systems. The results provide direct evidence that the signals observed in liquid-state 31P NMR of milk systems originate from phosphoserine residues in soluble caseins and inorganic phosphate in the serum phase, thereby resolving conflicting assignments reported in previous studies. Furthermore, it is demonstrated that liquid state 31P NMR is able to quantitatively di!erentiate the native amount of inorganic phosphate in the serum phase in suspensions of milk protein concentrate and skim milk. In light of the crucial importance of the calcium phosphate equilibrium between milk serum and casein micelles for understanding the casein micelle structure and its changes, liquid state 31P NMR shows potential as a suitable technique to get a better understanding of how processing a!ect the mineral equilibrium in casein micelles.

Multiexponential recovery is a process where a transient signal recovers through multiple relaxation pathways to a nonzero steady-state value. Such processes are ubiquitous in science and technology—for example in longitudinal ( T 1 ) relaxation in nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI). Existing schemes for extracting lifetime distributions from multiexponential recovery data are inaccurate or inefficient. They either impose unrealistic initial-condition constraints or require extensive late-time sampling. We present a robust inversion method that overcomes both limitations. The devised method determines the lifetime distribution by solving explicitly for the steady-state value and implicitly for the recovery factor—where the recovery factor defines the arbitrary starting point of the signal relative to the steady-state value. The method provides unprecedented accuracy even at shorter time windows and opens up new possibilities in research and industry. Several examples show the features of the method especially in nuclear magnetic resonance, food science, geoscience, and climate science.

Aimed at the simulation, design, and interpretation of advanced pulse experiments crossing the boundaries between nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR), including the rapidly emerging, hybrid discipline of pulsed dynamic nuclear polarisation (DNP), we present a host of novel features in the widely used SIMPSON software package addressing these aspects. Along with this come new features for advanced pulse sequence evaluation in terms of propagator splitting, high-order spin operator cross terms, and pulse phase transients. These fundamental new tools are introduced in a C++-based next generation of the SIMPSON software, which improves calculations speed in some aspects, is better prepared for further developments, and facilitates easier community contributions to the open-source software package.

Aimed at the simulation, design, and interpretation of advanced pulse experiments crossing the boundaries between nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR), including the rapidly emerging, hybrid discipline of pulsed dynamic nuclear polarisation (DNP), we present a host of novel features in the widely used SIMPSON software package addressing these aspects. Along with this come new features for advanced pulse sequence evaluation in terms of propagator splitting, high-order spin operator cross terms, and pulse phase transients. These fundamental new tools are introduced in a C++-based next generation of the SIMPSON software, which improves calculations speed in some aspects, is better prepared for further developments, and facilitates easier community contributions to the open-source software package.

Supported metal catalysts that integrate atomically dispersed species with controlled structures lie at the forefront of catalytic materials design, offering exceptional control over reactivity and high metal utilization, approaching the precision of molecular systems^1–3. However, accurately resolving the local metal coordination environments remains challenging, hindering the advancement of structure–activity relationships needed to optimize their design for diverse applications^1,2. Although electron microscopy reveals atomic dispersion, conventional spectroscopic methods used in heterogeneous catalysis only provide average structural information. Here we demonstrate that ¹⁹⁵Pt solid-state nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for characterizing atomically dispersed Pt sites on various supports, so called single-atom catalysts (SACs). Monte Carlo simulations allow the conversion of NMR spectra into SAC signatures that describe coordination environments with molecular precision, enabling quantitative assessment of Pt-site distribution and homogeneity. This methodology can track the influence of synthetic parameters, uncovering the impact of specific steps and support types, and can also monitor changes upon reaction. It offers critical insights for the reproducible development of SACs with targeted structures. Beyond SACs, this approach lays the foundation for studying more complex architectures, such as dual-atom or single-cluster catalysts, containing various NMR-active metals.

The cost and complexity of modern NMR spectrometers have led to the establishment of centralized, ultrahigh‐field facilities with multiple instruments that benefit from shared infrastructure and expertise. Many users have no NMR background, as they come from diverse scientific fields. This requires either heavy involvement of NMR experts in the data treatment or that data processing workflows are made user‐friendly, robust, and amenable to automation. This paper discusses how at the Danish Center for Ultrahigh Field NMR Spectroscopy at Aarhus University we develop automated—or guided—data processing workflows to serve the broad community of users of the Center. By providing consistency checks in the algorithms and reporting intermediate results, our data analysis tools raise flags if they are—or are likely—failing. We illustrate this approach with two examples: an automated quantitative lipidomics workflow and a semi‐automated multi‐exponential relaxation analysis in food matrices. The lipidomics workflow uses ¹H–³¹P TOCSY spectra, database matching, and quantitative ³¹P measurements, while color‐coded reliability labels highlight potential pitfalls. The multi‐exponential relaxation analysis automatically determines an appropriate value for the regularization parameter via the L‐curve. Both examples show how guided automation reduces expert supervision and accelerates data processing. We plan to further refine these automated workflows, share our software openly, and explore additional application areas to foster a semi‐automated NMR facility.

Single atom catalysts (SACs) have revolutionized the field of catalysis achieving an unprecedented level of control and metal utilization for solid materials, approaching what is expected with molecular catalysts.1-3 Establishing structure-activity relationships for their wide-ranging applications requires precise elucidation of the metal coordination environment, which remains a grand challenge.1,2 While electron microscopy reveals atomic dispersion, only average coordination environments can be deduced from state-of-the-art spectroscopic methods used in heterogeneous catalysis. Here, we establish 195Pt solid-state nuclear magnetic resonance (NMR) spectroscopy as a powerful methodology to acquire NMR signatures across a series of Pt-SACs dispersed on carbon based supports. Monte-Carlo simulations allow the conversion of NMR signatures into SAC fingerprints that describe local coordination environments with molecular precision and enable to quantitatively assess Pt-site distribution and homogeneity. This methodology can track the influence of synthetic parameters, e.g., specific protocols, synthetic steps and type of supports, on Pt-SAC structures, to guide the reproducible development of SACs with targeted structures; it also enables to monitor the change of coordination environment of SACs upon reaction. Such development provides a blueprint for the quantitative assessment of larger SAC families containing other NMR-active isotopes.

Few investigations have been made to determine whether pharmaceutical drugs cause any generational effects. These effects can be divided into intergenerational and transgenerational effects. In insects, the F1 offspring of exposed individuals are considered to show intergenerational effects (as they have been exposed as germ cells or early embryos), while the F2 generation is fully non-exposed and considered to show transgenerational effects. Here, the common over-the-counter (OTC) drug, paracetamol, is investigated for genotype-specific responses and effects across generations on three life-history traits: fecundity, longevity, and spontaneous locomotor activity levels in the model species Drosophila melanogaster. Seven isofemale D. melanogaster lines were exposed to a high and intermediate dose of paracetamol determined by a dose–response curve. NMR investigations verified the long-term presence of paracetamol in the food substrate. Phenotypic effects of paracetamol ingestion were investigated on flies exposed to the drug and in their offspring and grand-offspring. The dose–response curve indicated genotype-specific responses to paracetamol. In the following experiment, all traits investigated displayed significant effects of paracetamol ingestion for at least one of the seven isofemale lines, and we detected strong genotype-specific responses to paracetamol. Fecundity tended to increase in individuals directly exposed to the drug whereas fecundity in the F2 generation was reduced (transgenerational). Longevity generally decreased in directly exposed individuals but tended to increase in F1 offspring (intergenerational). Paracetamol effects on spontaneous locomotor activity were primarily detected as transgenerational effects and were rarely seen in directly exposed individuals. However, across lines, no clear overall trend could be determined for any trait. The generational effects and marked genotype-specific response to paracetamol warrants further investigation of both genotype-specific responses and generational effects in general.