Magnetic Resonance Relaxometry Research Articles

Swelling of food powders: Kinetics measurement and quantification using NMR relaxometry

Quantitative data on powder swelling kinetics is essential to understand phenomena occurring during rehydration, e.g. lump formation. In this study, swelling kinetics of food powders (gelatin powder, soy protein isolate, pea protein concentrate) were quantified by Nuclear Magnetic Resonance (NMR) relaxometry. Using gelatin plates as a model system, it was successfully demonstrated that NMR relaxometry is an efficient, non-destructive method to study swelling kinetics of non-dissolving systems with moderate swelling speeds. For plant-based proteins, high swelling speeds were observed. The obtained maximum water uptake due to swelling was 5.10 ± 0.80 g/g for soy protein isolate and 3.93 ± 0.16 g/g for pea protein isolate, which is in the expected range. Measurement speed was too low to resolve early swelling kinetics (below 84 s), evaluation was more elaborate and results less unambiguous.

Dynamical properties of solid and hydrated collagen: Insight from nuclear magnetic resonance relaxometry.

1H spin-lattice Nuclear Magnetic Resonance relaxometry experiments have been performed for collagen and collagen-based artificial tissues in the frequency range of 10 kHz-20MHz. The studies were performed for non-hydrated and hydrated materials. The relaxation data have been interpreted as including relaxation contributions originating from 1H-1H and 1H-14N dipole-dipole interactions, the latter leading to Quadrupole Relaxation Enhancement effects. The 1H-1H relaxation contributions have been decomposed into terms associated with dynamical processes on different time scales. A comparison of the parameters for the non-hydrated and hydrated systems has shown that hydration leads to a decrease in the dipolar relaxation constants without significantly affecting the dynamical processes. In the next step, the relaxation data for the hydrated systems were interpreted in terms of a model assuming two-dimensional translational diffusion of water molecules in the vicinity of the macromolecular surfaces and a sub-diffusive motion leading to a power law of the frequency dependencies of the relaxation rates. It was found that the water diffusion process is slowed down by at least two orders of magnitude compared to bulk water diffusion. The frequency dependencies of the relaxation rates in hydrated tissues and hydrated collagen are characterized by different power laws (ωH-β, where ωH denotes the 1H resonance frequency): the first of about 0.4 and the second close to unity.

Exploring Crystal-Phase Molecular Dynamics of the Low-Viscous Mesogen 6CHBT: A Combined FFC and High-Field NMR Relaxometry Investigation.

The molecular dynamics study of thermotropic mesogens exhibiting the crystal phases is valuable in unraveling the complex global (collective) and local (noncollective) motions executed by liquid crystal molecules, which would further advance the existing knowledge on orientationally disordered crystalline (ODIC) phases. Toward the fulfillment of such a task, a combined nuclear magnetic resonance (NMR) relaxometry approach employing the fast field cycling (FFC) NMR (10 kHz-30 MHz) and high-field pulsed NMR (400 MHz) techniques is utilized to sample the broad frequency range offered by molecular motions in the crystal phase of 4-(trans-4'-n-hexylcyclohexyl)-isothiocyanatobenzene (6CHBT). The validity of the observed relaxation data is tested and interpreted by the Bloembergen-Purcell-Pound (BPP) model involving the superposition of four mutually independent Lorentzian spectral densities, reflecting molecular dynamical processes on different time scales. The salient feature of the detailed analysis reveals that the lengthening of temporal dynamics in the crystal phase due to molecular rotations by jumps, which are of intermolecular origin, is evident and further supports the presence of collective-like local dynamics. The analysis does permit decoupling of the molecular reorientations about their short axes (∼100 ns) as well as long axes (∼50 ns) and methyl group rotations (∼0.5 ns) on distinct time scales. The activation energies for reorientations about the short axes and methyl group rotations are found to be 27.3 ± 2.7 and 15.8 ± 1.1 kJ/mol, respectively. The fast methyl rotations in the crystal phase of 6CHBT obtained from FFC NMR are further well complemented by high-field NMR, where 1H NMR line shapes are relatively narrow when compared to those of the nematic phase.

Physical and Chemical Methods to Assess Performance of TPO-Modified Asphalt Binder

The demand for effective asphalt additives is growing as road infrastructure ages and more sustainable pavement solutions are needed. Tire pyrolysis oil (TPO) is an example material that has been gaining attention as a potential asphalt additive. While physical performance grade (PG) temperatures are the predominant performance requirements for asphalt binders, chemical properties are also significant in the evaluation of asphalt performance. There is a need to chemically characterize the aging of asphalt binders modified with TPO and link chemical changes in binder components to binder performance. This study compares 2%, 4%, and 8% TPO and asphalt binder blends via dynamic shear rheometry (DSR), Fourier-transform infrared (FTIR) spectroscopy, and nuclear magnetic resonance (NMR) relaxometry. The variability in the modified blends was seen by both physical and chemical testing during four different blending times (1, 60, 120, and 240 min). After blending, high and intermediate PGs were determined by physical testing. The 8% TPO blend reduced the high PG of the binder from 64 °C to 58 °C. This effect was confirmed by chemical testing through changes in carbonyl indices and NMR relaxation times. With more oil present in the binder matrix, the binder’s resistance to rutting was reduced. While the high PG was hindered, the intermediate PG remained unchanged for all TPO blends. This physical similarity was mirrored in chemical testing. The chemical and physical variability along with the hindrance of the high PG temperature indicate that more treatment may be needed before TPO can be effectively applied to asphalt binders. This study suggests a correlation between physical performance and key chemical indicators.

Textural, rheological, melting properties, particle size distribution, and NMR relaxometry of cocoa hazelnut spread with inulin-stevia addition as sugar replacer.

This study investigated the influence of substituting 60, 80, and 100% of the sugar in traditional cocoa hazelnut paste (control) formulation with inulin-stevia (90:10, w/w) mixture on textural and rheological characteristics, melting behavior, water activity (aw), particle size distribution (PSD), and color. Textural, rheological, melting properties, and color of samples were analyzed after 1, 2, and 3 months of storage at 11°C. Nuclear magnetic resonance (NMR) relaxometry experiments were also performed to understand the interaction of new ingredients with oil. Replacement of sugar with inulin-stevia gave darker color, reduced Casson yield stress, and changed the textural parameters and melting profile of the samples depending on the level but did not create a remarkable effect on PSD and Casson plastic viscosity. Increasing inulin-stevia content yielded lower aw and higher T2a values indicating decreased mobility of water. Complete removal of sugar caused low spreadability. The results showed that an 80% replacement level yielded a product with similar textural parameters and fat-melting mouth feeling compared to control sample. Cocoa hazelnut spreads prepared with inulin and stevia showed good textural stability during storage.

Hydration and wetting mechanism of borosilicate – Polyvinyl alcohol (PVA) hybrid aerogels of potential bioactivity

Mesoporous borosilicate – polyvinyl alcohol (PVA) hybrid aerogels show positive bioactivity when interacting with dental pulp stem cells. The surface characteristics and the nanostructures of the hydrated aerogel particles are important in determining the biological response. This study reports the comparative structural characterization of pristine and stepwise hydrated hybrid aerogels, and proposes a qualitative mechanism for the wetting and pore-filling processes of these mesoporous materials. Nuclear magnetic resonance (NMR) relaxometry and cryoporometry revealed the extensive hydration of PVA macromolecules in the hybrid skeleton when contrasted to the wetting of pure silica aerogels. In spite of this extensive hydration, the open and permeable pore-structure of the hybrid borosilicate-PVA aerogels are preserved even when completely filled with liquid water. The conservation of the nanoscale architecture of the hybrid aerogels upon wetting was further confirmed by SANS. Finally, it was shown that the incorporation of microcrystalline hydroxyapatite into the hybrid skeleton does not alter the advantageous morphological features and wetting mechanism of the hybrid aerogels. The rough nanostructured skeleton is advantageous for cell binding and ensures facile mass transport through the particles in aqueous suspensions.

The Influence of Lyophilization Pretreatment and Whey Content on Whey and Gelatin-Based Hydrogels.

Whey and gelatin, natural polymers within the protein category, find widespread use in hydrogel formulations applied across the food, medical, and pharmaceutical industries. This study presents new characteristics of hydrogels based on whey, gelatin, and copper sulfate as a consequence of the additional steps in the preparation method, specifically refrigeration and freezing storage followed by lyophilization. The water state in hydrogels prior to lyophilization impacts the morphological appearance, with refrigerated hydrogels exhibiting a more regular and dense pore distribution, as shown by the Scanning Electron Microscopy (SEM) images. This observation aligns with the higher mobility of polymer chains indicated by T2 distributions in 1H nuclear magnetic resonance (RMN) relaxometry measurements. Changes in the intensity and amide-specific wavenumbers of the FTIR spectra of whey and gelatin proteins are evident in the Fourier Transformed Infrared (FTIR) spectra of crosslinked and frozen hydrogels before lyophilization. Moreover, the reinforcing effect in the hydrogel matrix, noted in mechanical tests, is attributed to increased polymer chain content and copper sulfate crosslinking.

Effects of high hydrostatic pressure on the functional properties of soy protein isolate

AbstractIn this study, functional properties of high hydrostatic pressure (HHP)‐treated soy protein isolate (SPI) samples including protein solubility, emulsification activity (EA), and water holding capacity (WHC) were studied. Fourier transform infrared spectroscopy (FTIR), viscosity, and nuclear magnetic resonance (NMR) relaxometry experiments were performed. Three pressure (300, 400, and 500 MPa), two pH (5.0 and 7.0), and two temperature levels (25 and 40°C) were used to prepare SPI samples. Solubility of SPI was more pH‐dependent than HHP‐dependent, whereas WHC was more sensitive to pressure. Samples processed at 300 MPa, pH 5.0, and 40°C demonstrated higher EA (p < .05) than the untreated samples. Pressure application significantly reduced the viscosity of SPI dispersions (p < .05). Samples processed at 300 MPa, pH 5.0, and 40°C and at 400 MPa, pH 5.0, and 40°C attained the longest transverse relaxation time (T2) values reflecting their low solubility profiles. Thus, results indicated that HHP was able to modify the functional properties of SPI at different temperature and pH conditions.Practical ApplicationsHigh hydrostatic pressure (HHP) is an emerging technology with its diverse range of applications in food industry. Modification of functional properties of food ingredients is one of the latest applications of HHP treatment. This study demonstrated that HHP treatment was able to modify some functional properties of soy protein isolate (SPI) samples including water holding capacity, solubility, and emulsification activity. Pressure level, pH, and temperature affected the functional properties of SPI samples. The parameter type/range and results of this study could be used in model HHP studies to improve some functional properties of SPI for different purposes.

Microscopic and Macroscopic Characterization of Hydrogels Based on Poly(vinyl-alcohol)-Glutaraldehyde Mixtures for Fricke Gel Dosimetry.

In recent decades, hydrogels have emerged as innovative soft materials with widespread applications in the medical and biomedical fields, including drug delivery, tissue engineering, and gel dosimetry. In this work, a comprehensive study of the macroscopic and microscopic properties of hydrogel matrices based on Poly(vinyl-alcohol) (PVA) chemically crosslinked with Glutaraldehyde (GTA) was reported. Five different kinds of PVAs differing in molecular weight and degree of hydrolysis were considered. The local microscopic organization of the hydrogels was studied through the use of the 1H nuclear magnetic resonance relaxometry technique. Various macroscopic properties (gel fraction, water loss, contact angle, swelling degree, viscosity, and Young's Modulus) were investigated with the aim of finding a correlation between them and the features of the hydrogel matrix. Additionally, an optical characterization was performed on all the hydrogels loaded with Fricke solution to assess their dosimetric behavior. The results obtained indicate that the degree of PVA hydrolysis is a crucial parameter influencing the structure of the hydrogel matrix. This factor should be considered for ensuring stability over time, a vital property in the context of potential biomedical applications where hydrogels act as radiological tissue-equivalent materials.

Vegan and sugar-substituted chocolates: assessing physicochemical characteristics by NMR relaxometry, rheology, and DSC

The main physicochemical characteristics of novel artisanal chocolates (both dark and milky) intended for vegan consumers or for those requiring assumption of fewer simple sugars, were analysed. Replacement of milk (with coconut copra, almonds, and soy protein isolates), and sucrose (with coconut sugars, stevia and erythritol, respectively) in dark chocolate, were accounted for by means of texture analysis, rheology, water activity, fatty acid composition, differential scanning calorimetry (DSC) and fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry. The vegan sample (i.e., the milk-less one) showed lower values of hardness and adhesiveness as well as a larger peak in the melting behavior at the calorimetric evaluation (DSC). Moreover, the absence of milk resulted in the halving of the yield stress and a decrease in both the apparent and Casson’s viscosity. In the sample of chocolate with less sucrose, the peak temperatures measured at the DSC indicate crystallization of cocoa butter in its best form (Vβ2), unlike in dark chocolate, due to the different sugar composition. Similarly, the Casson yield stress (τ0), increased significantly (almost 70%), with the substitution of sugar. Finally, the results of NMR FFC relaxometry made it possible to identify aggregates of different sizes, laying the basis for its use as a rapid, non-destructive method for chocolate analysis.

Alginate aerogels by spray gelation for enhanced pulmonary delivery and solubilization of beclomethasone dipropionate

Aerogel technology is an emerging platform that offers alternative and cost-effective dry carriers with advanced performances for the pharmaceutical industry. The innovative combination of compressed air-assisted spray gelation and “green” supercritical fluid (SCF) technology was used in this study to produce alginate aerogel microparticles with adequate properties for pulmonary drug delivery. Beclomethasone dipropionate (BDP), a poorly water-soluble anti-inflammatory drug for asthma treatment, was loaded into alginate aerogel particles by SCF-assisted impregnation ensuring high loading, as well as the amorphization of the drug. The production of aerogels was optimized through the fine-tuning of parameters in compressed air-assisted spray gelation, specifically adjusting the air flow rate and the pump speed. Alginate aerogels were aimed to be produced with an appropriate aerodynamic diameter from 1 to 5 µm, measured by in vitro deposition tests with Next Generation impactor and potential for deep lung penetration. Nuclear magnetic resonance (NMR) relaxometry was used to assess aerogel hydration and unveiled structure–property relationships leading to the sudden release of the drug. Finally, in vitro cytotoxicity tests in fibroblasts and ex vivo permeability tests were conducted. These biological tests confirmed the excellent biocompatibility of the aerogel formulations and demonstrated the efficient deposition of BDP in porcine bronchial tissues assisted by the porous alginate aerogel carrier.

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry.

Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well-established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal-organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high-throughput, non-destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

AbstractNanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Glass spectrum, excess wing phenomenon, and master curves in molecular glass formers: A multi-method approach.

The relaxation spectra of glass formers solely displaying an α-peak and excess wing contribution collected by various methods are reanalyzed to pin down their different spectral evolution. We show that master curve construction encompassing both α-peak and emerging excess wing works for depolarized light scattering (DLS) and nuclear magnetic resonance (NMR) relaxometry. It reveals the self-part of the slow dynamics' spectrum. Master curves are to be understood as a result of a more extensive scaling covering all temperatures instead of strict frequency-temperature superposition. DLS and NMR display identical relaxation spectra; yet, comparing different systems, we do not find a generic structural relaxation at variance with recent claims. Dielectric spectroscopy (DS) spectra show particularities, which render master curve construction obsolete. The DS α-peak is enhanced or suppressed with respect to that of DLS or NMR, yet, not correlated to the polarity of the liquid. Attempting to single out the excess wing from the overall spectrum discloses a stronger exponential temperature dependence of its amplitude compared to that below Tg and a link between its exponent and that of the fast dynamics' spectrum. Yet, such a decomposition of α-peak and excess wing appears to be unphysical. Among many different glasses, the amplitude of the excess wing power-law spectrum is found to be identical at Tg, interpreted as a relaxation analog to the Lindemann criterion.

Diffusion of Water Molecules on the Surface of Silica Nanoparticles─Insights from Nuclear Magnetic Resonance Relaxometry.

1H spin-lattice nuclear magnetic resonance (NMR) relaxation experiments have been performed for water dispersions of functionalized silica nanoparticles of diameters of 25 and 45 nm. The experiments have been performed in a broad frequency range spanning 3 orders of magnitude, from 10 kHz to 10 MHz, versus temperature, from 313 to 263 K. On the basis of the data, two-dimensional translation diffusion (diffusion close to the nanoparticle surface within a layer of the order of a few diameters of water molecules) has been revealed. The translational correlation times as well as the residence life times on the nanoparticle surface have been determined. It has turned out that the residence lifetime is temperature-independent and is on the order of 5 × 10-6 s for the smaller nanoparticles and by about a factor of 3 longer for the larger ones. The translational correlation time for the case of 25 nm nanoparticles is also temperature-independent and yields about 6 × 10-7 s, while for the dispersion of the larger nanoparticles, the correlation times changed from about 8 × 10-7 s at 313 K to about 1.2 × 10-6 s at 263 K. In addition to the quantitative characterization of the two-dimensional translation diffusion, correlation times associated with bound water molecules have been determined. The studies have also given insights into the population of the bound and diffusing water on the surface water fractions.

Microscopic moisture localisation in unsaturated materials using nuclear magnetic resonance relaxometry

Due to the detrimental effects of moisture in the built environment, there is a continuous interest in non-destructive experimental techniques that quantify and/or localise moisture in materials. Most existing experimental techniques, however, typically focus on macroscopic moisture contents in samples rather than the microscopic distribution of water in the individual pores of building materials. For the latter, a popular method such as X-ray computed tomography is not readily applicable, due to the gap between its spatial resolution limit and the typical pore sizes of building materials. Nuclear magnetic resonance (NMR) relaxometry is capable of measuring water in pores of both the nanometer and micrometer scale and is therefore an interesting possibility. While most NMR research focusses on water-saturated materials or overall moisture contents, this study determines the size distributions of the water islands in unsaturated materials with NMR, and compares results to X-ray computed tomography (XCT) images and pore network model (PNM) simulations. Results on unsaturated materials show that NMR focusses on the biggest water islands (i.e. in capillary filled pores) and disregards the hydrogen nuclei in smaller water islands (i.e. stored in pore corners). NMR relaxometry is therefore only adept at providing very rough estimates of the size of water-filled pores, especially since post-processing of the NMR experiments to obtain these water island size distributions involves a lot of uncertainty.

Magnetic resonance relaxometry in assessment of morphological properties of brain gliomas: state of the art

Magnetic resonance (MR) relaxometry, or measurement of tissue magnetic relaxation properties, is a technology intended to quantitatively depict the physical basis of structural MR imaging. This review is devoted to perspective directions of studies and application of MR relaxometry in brain glioma preoperative and pretherapeutic diagnosis. The current data advocate for emerging capabilities of relaxometry in glioma grading (despite possible overlap between different grades) and differentiating between gliomas and tumors of other origin. Some studies showed features of relaxometric values within the perifocal infiltrative edema zone possibly related to glioma infiltrative growth. We separately reviewed the works aimed at searching for the most aggressive and malignant foci in glioma tissue and extremely useful for tumor biopsy or removal. No less important are capabilities of relaxometry in radiogenomics, first of all, in IDH status prediction. The relaxometric method possesses perspective in multiparametric brain glioma diagnostics.

Characterization of Functionalized Chromatographic Nanoporous Silica Materials by Coupling Water Adsorption and Intrusion with Nuclear Magnetic Resonance Relaxometry

Characterization of Functionalized Chromatographic Nanoporous Silica Materials by Coupling Water Adsorption and Intrusion with Nuclear Magnetic Resonance Relaxometry

Evaluation and Prediction of Post-Hepatectomy Liver Failure Using Imaging Techniques: Value of Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.

Quantum Sensing and Light Guiding with Fluorescent Nanodiamond‐Doped PVA Fibers

AbstractFluorescent nanodiamonds (FNDs) containing quantum defects enable the optical measurement of electromagnetic fields and temperature and are among the most developed nanoscale quantum sensors today. Yet, for many applications in biomedicine and beyond, FNDs must be integrated into biocompatible substrates that preserve FND sensitivity and bring FNDs within nanoscale distance of their sensing target. At the same time, the high excitation light intensity required for most quantum sensing protocols remains a major challenge for applications in biomedicine. Here, it is shown that FNDs embedded in polyvinyl‐alcohol (PVA) fibers are a powerful 3D platform for nanoscale quantum sensing via light guiding. First, it is demonstrated that biocompatible PVA fibers can guide light to excite FNDs >10 µm from the excitation beam. Using this light‐guiding‐enabled excitation, optically detected magnetic resonance (ODMR) and T1 spin relaxometry measurements are performed using the nitrogen‐vacancy (NV) center in FNDs. Through ODMR thermometry, it is shown that light‐guiding‐enabled excitation mitigates light‐induced heating. Finally, the quantum sensing capability of the platform is established by detecting paramagnetic gadolinium in a dry and aqueous environment using T1 relaxometry of the NV center in FNDs. These results pave the way for light‐guiding‐enabled optical quantum sensing in biomedicine using nanodiamond‐doped biosubstrates.