Novel 1H low field nuclear magnetic resonance applications for the field of biodiesel

Quantitative characterization of the crosslinking degree of hydroxypropyl guar gum fracturing fluid by low-field NMR

As a widely used water-based fracturing fluid, the performance of hydroxypropyl guar gum fracturing fluid is closely related to the degree of crosslinking, the quantitative characterization of which can reveal a detailed crosslinking mechanism and guide the preparation of fracturing fluid gels with an excellent performance. However, the commonly used high-temperature rheology method for evaluating the performance of fracturing fluids only qualitatively reflects the degree of crosslinking. In this study, low-field nuclear magnetic resonance (LF-NMR) was used to characterize the degree of crosslinking in guar gum fracturing fluid gels. The spin-spin relaxation time of the H proton in guar gum was molecularly analyzed using LF-NMR. The viscoelastic properties met the requirements when the crosslinking degree of the gel was 88-94 %. The transformation of the linear structure into a membrane structure during the crosslinking process of the guar gum fracturing fluid was confirmed by freeze-drying and scanning electron microscopy (SEM) from a microscopic perspective. The changing trend of the microstructure and viscoelastic properties of the fracturing fluid gel under different crosslinker dosages was consistent with changes in the degree of crosslinking. The LF-NMR test process is non-destructive to the gel structure, and the test results demonstrate good accuracy and repeatability.

Semi-Autonomic AI LF-NMR Sensor for Industrial Prediction of Edible Oil Oxidation Status

The evaluation of an oil's oxidation status during industrial production is highly important for monitoring the oil's purity and nutritional value during production, transportation, storage, and cooking. The oil and food industry is seeking a real-time, non-destructive, rapid, robust, and low-cost sensor for nutritional oil's material characterization. Towards this goal, a ¹H LF-NMR relaxation sensor application based on the chemical and structural profiling of non-oxidized and oxidized oils was developed. This study dealt with a relatively large-scale oil oxidation database, which included crude data of a ¹H LF-NMR relaxation curve, and its reconstruction into T₁ and T₂ spectral fingerprints, self-diffusion coefficient D, and conventional standard chemical test results. This study used a convolutional neural network (CNN) that was trained to classify T₂ relaxation curves into three ordinal classes representing three different oil oxidation levels (non-oxidized, partial oxidation, and high level of oxidation). Supervised learning was used on the T₂ signals paired with the ground-truth labels of oxidation values as per conventional chemical lab oxidation tests. The test data results (not used for training) show a high classification accuracy (95%). The proposed AI method integrates a large training set, an LF-NMR sensor, and a machine learning program that meets the requirements of the oil and food industry and can be further developed for other applications.

Time Domain (TD) Proton NMR Analysis of the Oxidative Safety and Quality of Lipid-Rich Foods

Food safety monitoring is highly important due to the generation of unhealthy components within many food products during harvesting, processing, storage, transportation and cooking. Current technologies for food safety analysis often require sample extraction and the modification of the complex chemical and morphological structures of foods, and are either time consuming, have insufficient component resolution or require costly and complex instrumentation. In addition to the detection of unhealthy chemical toxins and microbes, food safety needs further developments in (a) monitoring the optimal nutritional compositions in many different food categories and (b) minimizing the potential chemical changes of food components into unhealthy products at different stages from food production until digestion. Here, we review an efficient methodology for overcoming the present analytical limitations of monitoring a food's composition, with an emphasis on oxidized food components, such as polyunsaturated fatty acids, in complex structures, including food emulsions, using compact instruments for simple real-time analysis. An intelligent low-field proton NMR as a time domain (TD) NMR relaxation sensor technology for the monitoring of T₂ (spin-spin) and T₁ (spin-lattice) energy relaxation times is reviewed to support decision-making by producers, retailers and consumers in regard to food safety and nutritional value during production, shipping, storage and consumption.

Evaluation of quality change in Salviae miltiorrhizae radix et rhizoma during drying by LF-NMR and HPLC

Salviae miltiorrhizae radix et rhizoma (Danshen, in Chinese) is one of the traditional Chinese medicines commonly used in clinical practice. In this study, low field nuclear magnetic resonance (LF-NMR) was used to detect changes in the moisture content during the drying of Danshen. Three water states (bound, immobilized, and free) in Danshen were investigated by multi-exponential fitting of the NMR data. Mass changes during drying were analyzed using high-performance liquid chromatography and partial least squares discriminant analysis. The results revealed that two components, salvianolic acid B and tanshinone, were the main chemical substances that produced the differences. Correlations were found among chemical substances, color, and moisture. LF-NMR can quickly assess the moisture content during drying. It also provides a practical tool for the production and processing of medicines or slices.

Characterization of Water in Wood by Time-Domain Nuclear Magnetic Resonance Spectroscopy (TD-NMR): A Review

This review summarizes the development of the experimental technique and analytical method for using TD-NMR to study wood-water interactions in recent years. We briefly introduce the general concept of TD-NMR and magnetic resonance imaging (MRI), and demonstrate their applications for characterizing the following aspects of wood-water interactions: water state, fiber saturation state, water distribution at the cellular scale, and water migration in wood. The aim of this review is to provide an overview of the utilizations and future research opportunities of TD-NMR in wood-water relations. It should be noted that this review does not cover the NMR methods that provide chemical resolution of wood macromolecules, such as solid-state NMR.

Proton Low Field NMR Relaxation Time Domain Sensor for Monitoring of Oxidation Stability of PUFA-Rich Oils and Emulsion Products

The nutritional characteristics of fatty acid (FA) containing foods are strongly dependent on the FA’s chemical/morphological arrangements. Paradoxically the nutritional, health enhancing FA polyunsaturated fatty acids (PUFAs) are highly susceptible to oxidation into harmful toxic side products during food preparation and storage. Current analytical technologies are not effective in the facile characterization of both the morphological and chemical structures of PUFA domains within materials for monitoring the parameters affecting their oxidation and antioxidant efficacy. The present paper is a review of our work on the development and application of a proton low field NMR relaxation sensor (¹H LF NMR) and signal to time domain (TD) spectra reconstruction for chemical and morphological characterization of PUFA-rich oils and their oil in water emulsions, for assessing their degree and susceptibility to oxidation and the efficacy of antioxidants. The NMR signals are energy relaxation signals generated by spin–lattice interactions (T₁) and spin–spin interactions (T₂). These signals are reconstructed into 1D (T₁ or T₂) and 2D graphics (T₁ vs. T₂) by an optimal primal-dual interior method using a convex objectives (PDCO) solver. This is a direct measurement on non-modified samples where the individual graph peaks correlate to structural domains within the bulk oil or its emulsions. The emulsions of this review include relatively complex PUFA-rich oleosome-oil bodies based on the aqueous extraction from linseed seeds with and without encapsulation of externally added oils such as fish oil. Potential applications are shown in identifying optimal health enhancing PUFA-rich food formulations with maximal stability against oxidation and the potential for on-line quality control during preparation and storage.

Low field, time domain NMR in the agriculture and agrifood sectors: An overview of applications in plants, foods and biofuels

In this contribution, a selective overview of low field, time-domain NMR (TD-NMR) applications in the agriculture and agrifood sectors is presented. The first applications of commercial TD-NMR instruments were in food and agriculture domains. Many of these earlier methods have now been recognized as standard methods by several international agencies. Since 2000, several new applications have been developed, using state of the art instruments, new pulse sequences and new signal processing methods. TD-NMR is expected, in the coming years, to become even more important in quality control of fresh food and agricultural products, as well as for a wide range of food-processed products. TD-NMR systems provide excellent means to collect data relevant for use in the agricultural environment and the bioenergy industry. Data and information collected by TD-NMR systems thus may support decision makers in business and public organizations.

Liquid-phase characterization of molecular interactions in polyunsaturated and n-fatty acid methyl esters by (1)H low-field nuclear magnetic resonance

BACKGROUND

To identify and develop the best renewable and low carbon footprint biodiesel substitutes for petroleum diesel, the properties of different biodiesel candidates should be studied and characterized with respect to molecular structures versus biodiesel liquid property relationships. In our previous paper, (1)H low-field nuclear magnetic resonance (LF-NMR) relaxometry was investigated as a tool for studying the liquid-phase molecular packing interactions and morphology of fatty acid methyl esters (FAMEs). The technological potential was demonstrated with oleic acid and methyl oleate standards having similar alkyl chains but different head groups. In the present work, molecular organization versus segmental and translational movements of FAMEs in their pure liquid phase, with different alkyl chain lengths (10-20 carbons) and degrees of unsaturation (0-3 double bonds), were studied with (1)H LF-NMR relaxometry and X-ray, (1)H LF-NMR diffusiometry, and (13)C high-field NMR.

RESULTS

Based on density values and X-ray measurements, it was proposed that FAMEs possess a liquid crystal-like order above their melting point, consisting of random liquid crystal aggregates with void spaces between them, whose morphological properties depend on chain length and degree of unsaturation. FAMEs were also found to exhibit different degrees of rotational and translational motions, which were rationalized by chain organization within the clusters, and the degree and type of molecular interactions and temperature effects. At equivalent fixed temperature differences from melting point, saturated FAME molecules were found to have similar translational motion regardless of chain length, expressed by viscosity, self-diffusion coefficients, and spin-spin (T 2) (1)H LF-NMR. T 2 distributions suggest increased alkyl chain rigidity, and reduced temperature response of the peaks' relative contribution with increasing unsaturation is a direct result of the alkyl chain's morphological packing and molecular interactions.

CONCLUSIONS

Both the peaks' assignments for T 2 distributions of FAMEs and the model for their liquid crystal-like morphology in the liquid phase were confirmed. The study of morphological structures within liquids and their response to temperature changes by (1)H LF-NMR has a high value in the field of biodiesel and other research and applied disciplines in numerous physicochemical- and organizational-based properties, processes, and mechanisms of alkyl chains, molecular interactions, and morphologies.

Study of liquid-phase molecular packing interactions and morphology of fatty acid methyl esters (biodiesel)

BACKGROUND

(1)H low field nuclear magnetic resonance (LF-NMR) relaxometry has been suggested as a tool to distinguish between different molecular ensembles in complex systems with differential segmental or whole molecular motion and/or different morphologies. In biodiesel applications the molecular structure versus liquid-phase packing morphologies of fatty acid methyl esters (FAMEs) influences physico-chemical characteristics of the fuel, including flow properties, operability during cold weather, blending, and more. Still, their liquid morphological structures have scarcely been studied. It was therefore the objective of this work to explore the potential of this technology for characterizing the molecular organization of FAMEs in the liquid phase. This was accomplished by using a combination of supporting advanced technologies.

RESULTS

We show that pure oleic acid (OA) and methyl oleate (MO) standards exhibited both similarities and differences in the (1)H LF-NMR relaxation times (T2s) and peak areas, for a range of temperatures. Based on X-ray measurements, both molecules were found to possess a liquid crystal-like order, although a larger fluidity was found for MO, because as the temperature is increased, MO molecules separate both longitudinally and transversely from one another. In addition, both molecules exhibited a preferred direction of diffusion based on the apparent hydrodynamic radius. The close molecular packing arrangement and interactions were found to affect the translational and segmental motions of the molecules, as a result of dimerization of the head group in OA as opposed to weaker polar interactions in MO.

CONCLUSIONS

A comprehensive model for the liquid crystal-like arrangement of FAMEs in the liquid phase is suggested. The differences in translational and segmental motions of the molecules were rationalized by the differences in the (1)H LF-NMR T2 distributions of OA and MO, which was further supported by (13)C high field (HF)-NMR spectra and (1)H HF-NMR relaxation. The proposed assignment allows for material characterization based on parameters that contribute to properties in applications such as biodiesel fuels.