Practical implications of the phase-compositional assessment of lipid-based food products by time-domain NMR

Characterisation of Fat Crystal Polymorphism in Cocoa Butter by Time-Domain NMR and DSC Deconvolution

The polymorphic state of edible fats is an important quality parameter in fat research as well as in industrial applications. Nowadays, X-ray diffraction (XRD) is the most commonly used method to determine the polymorphic state. However, quantification of the different polymorphic forms present in a sample is not straightforward. Differential Scanning Calorimetry (DSC) is another method which provides information about fat crystallization processes: the different peaks in the DSC spectrum can be coupled to the melting/crystallisation of certain polymorphs. During the last decade, nuclear magnetic resonance (NMR) has been proposed as a method to determine, qualitatively and/or quantitatively, the polymorphic forms present in fat samples. In this work, DSC- and NMR-deconvolution methods were evaluated on their ability to determine the polymorphic state of cocoa butter, with XRD as a reference method. Cocoa butter was subjected to two different temperature profiles, which enforced cocoa butter crystallization in different polymorphic forms. It was found that XRD remains the best method to qualitatively determine the polymorphic state of the fat. Whereas the quantitative NMR and DSC deconvolution results were not fully in line with the XRD results in all cases, NMR deconvolution showed great promise both in a qualitative and quantitative way.

Perspectives in process analytics using low field NMR

Low field NMR is a powerful analytical tool which creates an enormous added value in process analytics. Based on specific applications in process analytics and perspectives for low field NMR in form of spectroscopy, relaxation, diffusion, and imaging in quality control, diverse applications and technical realizations like spectrometers, time domain NMR, mobile NMR sensors and MRI will be discussed.

Low-field NMR for quality control on oils

Oil is a prominent, but multifaceted material class with a wide variety of applications. Technical oils, crude oils as well as edibles are main subclasses. In this review, the question is addressed how low-field NMR can contribute in oil characterization as an analytical tool, mainly with respect to quality control. Prerequisite in the development of a quality control application, however, is a detailed understanding of the oils and of the measurement. Low-field NMR is known as a rich methodical toolbox that was and is explored and further developed to address questions about oils, their quality, and usability as raw materials, during production and formulation as well as in use.

Kinetics of 12-Hydroxyoctadecanoic Acid SAFiN Crystallization Rationalized Using Hansen Solubility Parameters

Changes in solvent chemistry influenced kinetics of both nucleation and crystallization of 12-hydroxyoctadecenoic, as determined using differential scanning calorimetry and applying a modified Avrami model to the calorimetric data. Altering solvent properties influenced solvent-gelator compatibility, which in turn altered the chemical potential of the system at the onset of crystallization, the kinetics of gelation, and the resulting 12HOA crystal fiber length. The chemical potential at the onset of crystallization was linearly correlated to both the hydrogen-bonding Hansen solubility parameter and the solvent-gelator vectorial distance in Hansen space, R_a. Our work suggests that solvent properties can be modulated to affect the solubility of 12HOA, which in turn influences the kinetics of crystallization and the self-assembly of this organogelator into supramolecular crystalline structures. Therefore, modulation of solvent properties during organogelation can be used to control fiber length and thus engineer the physical properties of the gel.

To gel or not to gel: correlating molecular gelation with solvent parameters

Rational design of small molecular gelators is an elusive and herculean task, despite the rapidly growing body of literature devoted to such gels over the past decade. The process of self-assembly, in molecular gels, is intricate and must balance parameters influencing solubility and those contrasting forces that govern epitaxial growth into axially symmetric elongated aggregates. Although the gelator-gelator interactions are of paramount importance in understanding gelation, the solvent-gelator specific (i.e., H-bonding) and nonspecific (dipole-dipole, dipole-induced and instantaneous dipole induced forces) intermolecular interactions are equally important. Solvent properties mediate the self-assembly of molecular gelators into their self-assembled fibrillar networks. Herein, solubility parameters of solvents, ranging from partition coefficients (log P), to Henry's law constants (HLC), to solvatochromic parameters (ET(30)), and Kamlet-Taft parameters (β, α and π), and to Hansen solubility parameters (δp, δd, δh), are correlated with the gelation ability of numerous classes of molecular gelators. Advanced solvent clustering techniques have led to the development of a priori tools that can identify the solvents that will be gelled and not gelled by molecular gelators. These tools will greatly aid in the development of novel gelators without solely relying on serendipitous discoveries. These tools illustrate that the quest for the universal gelator should be left in the hands of Don Quixote and as researchers we must focus on identifying gelators capable of gelling classes of solvents as there is likely no one gelator capable of gelling all solvents.

Micro-viscosity of liquid oil confined in colloidal fat crystal networks

Molecular rotors may be utilized as non-invasive, non-disruptive and highly sensitive alternatives to conventional measures of bulk viscosity when the oil is entrained in a colloidal fat crystal network. Oil viscosity changes based on the molecular confinement of the oil, which is dependent on its molecular volume. Changes in micro-viscosity were not dependent on the solids content, but instead were strongly dependent on the box-counting fractal dimension in high-space filling colloidal fat crystal networks (i.e., D > 1.89). A bulk oil viscosity is often an overestimation of the actual viscosity of the entrained oil and may not be appropriate when predicting diffusion in multi-phase materials.

Non-destructive quantification of water gradient in sludge composting with Magnetic Resonance Imaging

Sludge from a slaughter-house wastewater plant, and mixtures of bulking agent (crushed wood pallet) and sludge were studied by Nuclear Magnetic Resonance (NMR). The NMR spin-spin relaxation (T(2)) and spin-lattice relaxation (T(1)) signals for sludge, wet crushed wood pallet and mixtures of sludge and bulking agent were decomposed into three relaxation time components. Each relaxation time component was explained by a non-homogeneous water distribution on a microscopic length scale and by the porosity of the material. For all samples, the T(2) relaxation time value of each component was directly related to the dry matter content. The addition of wet crushed wood to sludge induced a decrease in the relaxation time, explained by water transfer between the sludge and the wood. Magnetic Resonance Imaging (MRI) and respirometric measurements were performed on sludge and wood mixtures. MR images of the mixtures were successfully obtained at different biodegradation states. Based on specific NMR measurements in an identified area located in the MRI cells, the results showed that grey levels of MR images reflected dry matter content. This preliminary study showed that MRI would be a powerful tool to measure water distribution in sludge and bulking agent mixtures and highlights the potential of this technique to increase the understanding of sludge composting.

Engineering the oil binding capacity and crystallinity of self-assembled fibrillar networks of in edible oils

The crystallinity and oil binding capacity of 12-hydroxystearic acid (12HSA)-vegetable oil organogels was modified by changing the post-crystallization annealing temperature from 5 °C to 30 °C for 24 h. The gels stored at 5 °C had a highly branched crystalline structure with small uniform pores, as determined by cryo-scanning electron microscopy. Large T2proton relaxation peaks at 50 to 70 ms determined by pulse nuclear magnetic resonance (pNMR) suggested the presence of highly immobilized oil at 5 °C. When the gels were stored at 30 °C, longer fibers and a less branched network were observed. At 30 °C, the 12HSA network's crystallinity was enhanced with fewer inclusions of liquid oil as determined by pNMR. When the gels were stored at 30 °C, a significantly shorter T2 relaxation peak was observed. The increased crystallinity, at 30 °C, was attributed to a reduction in bulk supersaturation, resulting in a very high crystallographic mismatch nucleation barrier (ΔG*) which favored one-dimensional fiber growth. However, at a lower crystallization temperature of 5 °C, there is an increase in the supersaturation and hence the crystallographic mismatch barrier is significantly lower, increasing fiber tip branching. The nucleation-growth-branching-growth model for self-assembled fibrillar networks explains the differences in crystallinity, pore size and oil syneresis observed for the 12HSA-vegetable oil organogels. It was found that the gels stored at 30 °C syneresised 1.35 times faster than the gels stored at 5 °C. Furthermore, the change in the T2 relaxations and the ratio of the complex viscosity/pore radius were 1.35 and 1.30 respectively.