Traditional nuclear magnetic resonance (NMR) spectroscopy relies on the versatile chemical information conveyed by spectra. To complement conventional NMR, Laplace NMR explores diffusion and relaxation phenomena to reveal details on molecular motions. Under a broad concept of ultrafast multidimensional Laplace NMR, here we introduce an ultrafast diffusion-relaxation correlation experiment enhancing the resolution and information content of corresponding 1D experiments as well as reducing the experiment time by one to two orders of magnitude or more as compared with its conventional 2D counterpart. We demonstrate that the method allows one to distinguish identical molecules in different physical environments and provides chemical resolution missing in NMR spectra. Although the sensitivity of the new method is reduced due to spatial encoding, the single-scan approach enables one to use hyperpolarized substances to boost the sensitivity by several orders of magnitude, significantly enhancing the overall sensitivity of multidimensional Laplace NMR.

The exchange of molecules between different physical or chemical environments due to diffusion or chemical transformations has a crucial role in a plethora of fundamental processes such as breathing, protein folding, chemical reactions and catalysis. Here, we introduce a method for a single-scan, ultrafast NMR analysis of molecular exchange based on the diffusion coefficient contrast. The method shortens the experiment time by one to four orders of magnitude. Consequently, it opens the way for high sensitivity quantification of important transient physical and chemical exchange processes such as in cellular metabolism. As a proof of principle, we demonstrate that the method reveals the structure of aggregates formed by surfactants relevant to aerosol research.

Although deep eutectic solvents (DESs) have demonstrated significant potential in lignin processing, their influence on molecular stacking and conformational evolution during lignin dissolution and nanoparticle formation remains insufficiently understood. Here, we develop a green, straightforward, and single‐step approach to produce self‐assembled lignin nanoparticles (LNPs). The LNPs obtained using the acidic DES method exhibited a great size reduction, with an average size approximately one‐ninth of that produced by conventional solvent‐exchange methods. To gain mechanistic insights into the reconstruction, dissolution, and self‐assembly of lignin in DESs, we integrate structural characterization with molecular dynamics simulations. Specifically, we simulate the dynamic behavior and configurational states of high‐molar‐mass lignin models (4,182 g mol ⁻¹ ) in aqueous solvent systems. The results reveal the critical role of molecular structure, intra/intermolecular π–π interactions, stacked conformations, solvent‐specific effects in determining the size and compactness of LNPs. Notably, the DES stabilizes lateral‐shifted configurations, promoting the formation of small and compact LNPs. In contrast, the tetrahydrofuran/H ₂ O solvent system favors offset‐stacked configurations and hydrophobic interactions, leading to larger, spherical LNPs. Overall, our findings offer new insights into the underlying mechanisms of LNP formation using DESs, demonstrating the possibility of regulating and controlling lignin assemblies through solvent parameters.