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Strongly confined flow of particulate fluids is encountered in applications ranging from three-dimensional (3D) printing to the spreading of foods and cosmetics into thin layers. When flowing in constrictions with gap sizes, w , within 10 2 times the mean size of particles or aggregates, d , structured fluids experience enhanced bulk velocities and inhomogeneous viscosities, as a result of so-called cooperative, or nonlocal, particle interactions. Correctly predicting cooperative flow for a wide range of complex fluids requires high-resolution flow imaging modalities applicable in situ to even optically opaque fluids. To this goal, we here developed a pressure-driven high-field magnetic resonance imaging (MRI) velocimetry platform, comprising a pressure controller connected to a capillary. Wall properties and diameter could be modified respectively as hydrophobic/hydrophilic, or within w ∼ 100-540 μm. By achieving a high spatial resolution of 9 μm, flow cooperativity length scales, ξ, down to 15 μm in Carbopol with d ∼ 2 μm could be quantified by means of established physical models with an accuracy of 13%. The same approach was adopted for a heterogeneous fat crystal dispersion (FCD) with d and ξ values up to an order of magnitude higher than those for Carbopol. We found that for strongly confined flow of Carbopol in the 100 μm capillary, ξ is independent of flow conditions. For the FCD, ξ increases with gap size and applied pressures over 0.25-1 bar. In both samples, nonlocal interactions span domains up to about 5-8 particles but, at the highest confinement degree explored, ∼8% for FCD, domains of only ∼2 particles contribute to cooperative flow. The developed flow-MRI platform is easily scalable to ultrahigh field MRI conditions for chemically resolved velocimetric measurements of, e.g. , complex fluids with anisotropic particles undergoing alignment. Future potential applications of the platform encompass imaging extrusion under confinement during the 3D printing of complex dispersions or in in vitro vascular and perfusion studies.

Chemical feedback between building block synthesis and their subsequent supramolecular self-assembly into nanostructures has profound effects on assembly pathways. Nature harnesses feedback in reaction-assembly networks in a variety of scenarios including virion formation and protein folding. Also in nanomaterial synthesis, reaction-assembly networks have emerged as a promising control strategy to regulate assembly processes. Yet, how chemical feedback affects the fundamental pathways of structure formation remains unclear. Here, we unravel the pathways of a templated reaction-assembly network that couples a covalent polymerization to an electrostatic coassembly process. We show how the supramolecular staging of building blocks at a macromolecular template can accelerate the polymerization reaction and prevent the formation of kinetically trapped structures inherent to the process in the absence of feedback. Finally, we establish a predictive kinetic reaction model that quantitatively describes the pathways underlying these reaction-assembly networks. Our results shed light on the fundamental mechanisms by which chemical feedback can steer self-assembly reactions and can be used to rationally design new nanostructures., Competing Interests: The authors declare no competing financial interest., (© 2020 American Chemical Society.)

Phasor analysis is a robust, nonfitting, method for the study of multiexponential decays in lifetime imaging data, routinely used in Fluorescence Lifetime Imaging Microscopy (FLIM) and only recently validated for Magnetic Resonance Imaging (MRI). In the established phasor approach, typically only the first Fourier harmonic is used to unravel time-domain exponential trends and their intercorrelations across image voxels. Here, we demonstrate the potential of full -harmonics (FH) phasor analysis by using all frequency-domain data points in simulations and quantitative MRI (qMRI) T 2 measurements of phantoms with bulk liquids or liquid-filled porous particles and of a human brain. We show that FH analysis, while of limited advantage in FLIM due to the correlated nature of shot noise, in MRI outperforms single-harmonic phasor in unravelling multiple physical environments and partial-volume effects otherwise undiscernible. We foresee application of FH phasor to, e.g., big-data analysis in qMRI of biological or other multiphase systems, where multiparameter fitting is unfeasible.

The noninvasive, in situ chemical identification of liquid mixtures confined in porous materials is experimentally challenging. NMR is chemically resolved and applicable to optically opaque systems but suffers from a significant loss in spectral resolution in the presence of the magnetic field inhomogeneities typical of porous media. In this work, we introduce a method of analysis of conventional two-dimensional (2D) 1 H NMR correlation spectroscopy (COSY) spectra based on the extraction of 1D antidiagonal projections, which are free from line-broadening effects and can therefore be used for chemical species identification. Here, we show the application of the technique to the measurement of linear n -alkanes where the cross-to-diagonal peak ratios are shown to follow a power-law curve as a function of the chain length. This calibration enables quantifying mixtures of linear hydrocarbons confined in any porous material independently of temperature or inter -molecular dynamics. Thus, this is a promising tool for quantitative chemical reaction monitoring studies in heterogeneous systems under operando experimental conditions.

Macromolecular dynamics in biological systems, which play a crucial role for biomolecular function and activity at ambient temperature, depend strongly on moisture content. Yet, a generally accepted quantitative model of hydration-dependent phenomena based on local relaxation and diffusive dynamics of both polymer and its adsorbed water is still missing. In this work, atomistic-scale spatial distributions of motional modes are calculated using molecular dynamics simulations of hydrated xyloglucan (XG). These are shown to reproduce experimental hydration-dependent 13 C NMR longitudinal relaxation times ( T 1 ) at room temperature, and relevant features of their broad distributions, which are indicative of locally heterogeneous polymer reorientational dynamics. At low hydration, the self-diffusion behavior of water shows that water molecules are confined to particular locations in the randomly aggregated XG network while the average polymer segmental mobility remains low. Upon increasing water content, the hydration network becomes mobile and fully accessible for individual water molecules, and the motion of hydrated XG segments becomes faster. Yet, the polymer network retains a heterogeneous gel-like structure even at the highest level of hydration. We show that the observed distribution of relaxations times arises from the spatial heterogeneity of chain mobility that in turn is a result of heterogeneous distribution of water-chain and chain-chain interactions. Our findings contribute to the picture of hydration-dependent dynamics in other macromolecules such as proteins, DNA, and synthetic polymers, and hold important implications for the mechanical properties of polysaccharide matrixes in plants and plant-based materials.

Improved moisture stability is desired in cellulose biocomposites. In order to clarify nanostructural effects, a new approach is presented where water and polymer matrix mobilities are characterized separately. Nanocomposites from cellulose nanofibers (CNF) in the xyloglucan (XG) biopolymer matrix are investigated at different hydration states. Films of XG, CNF, and CNF/XG composites are subjected to detailed (2)H and (13)C NMR relaxation studies. Since the (2)H NMR signal arises from heavy water and the (13)C signal from the polysaccharides, molecular water and polymer dynamics is for the first time investigated separately. In the neat components, (2)H transverse relaxation (T2) data are consistent with water clustering at the CNF fibril surfaces, but bulk spread of moisture in XG. The new method results in a description of water interaction with the nanoscale phases. At low hydration, water molecules at the CNF/XG interface exhibit higher water mobility than in neat CNF or XG, due to locally high water concentration. At the same time, CNF-associated interphase segments of XG show slower NMR-dynamics than that in neat XG.

We report that at ambient temperature and with 100% enriched para-hydrogen (p-H2) dissolved in organic solvents, paramagnetic spin catalysis of para → ortho hydrogen conversion is accompanied at the onset by a negative ortho-hydrogen (o-H2) proton NMR signal. This novel finding indicates an electron spin polarization transfer, and we show here that this can only occur if the H2 molecule is dissociated upon its transient adsorption by the paramagnetic catalyst. Following desorption, o-H2 is created until the thermodynamic equilibrium is reached. A simple theory confirms that in the presence of a static magnetic field, the hyperfine coupling between unpaired electrons and nuclear spins is responsible for the observed polarization transfer. Owing to the negative electron gyromagnetic ratio, this explains the experimental results and ascertains an as yet unexplored mechanism for para → ortho conversion. Finally, we show that the recovery of o-H2 magnetization toward equilibrium can be simply modeled, leading to the para → ortho conversion rate.

The cellular structure of wood, which is highly anisotropic along its main growth directions, is responsible for the observed anisotropy in its physical and mechanical properties that depend in a complex manner on the moisture content. Here, we demonstrate that the (1)H NMR spectra of wood from Norway spruce exhibit a strong and characteristic dependence on the direction of the sample relative to the applied magnetic field. By comparing spectra recorded at different magnetic-field strengths, we show that this variation is caused by the magnetic-field distribution created by the anisotropic and inhomogeneous distribution of matter and thereby magnetic susceptibility. On the basis of the observations that (i) the recorded spectral peak predominantly arises from translationally mobile water molecules and (ii) the spectral broadening is large if the long axis of the wood tracheid cells is perpendicular to the magnetic field, we set out to test the hypothesis that it is the susceptibility variation on the tracheid length scale that is responsible for the observed spectral features. To verify this, we numerically calculate in a discrete grid approximation the NMR line shapes obtained in realistic tracheid models, and we find that the calculated NMR line shapes are in good agreement with the corresponding experimental ones. We envisage the application of these findings for revealing the inhomogeneous distribution of water and its molecular properties in wood and wood-based materials at varying degrees of humidity.