Low-field NMR Spectroscopy Research Articles

Quantitative composition analysis of natural gas by high-pressure proton low-field NMR spectroscopy: Development of an improved experimental methodology

Natural gas (NG) has been proposed as a bridging fuel between fossil and renewable energy sources, playing a significant role in the decarbonization of the energy sector. Its commercial value and the integrity of the NG infrastructure depend on the NG physical properties, which are strongly related to its composition. Thus, the development of low-cost and reliable analytical methods for composition analysis of NG can enable a more efficient operation. Recently, we showed that high-pressure (HP) benchtop 1H NMR spectroscopy combined with indirect hard modelling (IHM) is an efficient and low-cost method for composition quantification of NG. The current work extends this methodology by introducing and testing novel experimental strategies for increasing the reliability and accuracy of the method. This new approach includes the use of a recently published high-pressure tube design and single-scan acquisition combined with novel quality control parameters to obtain highly reproducible peak shape 1H NMR spectra over long periods. The proposed methodology tested on binary, ternary, and more complex mixtures at 200 bar and 160 bar gives compositions in excellent agreement with the vendor certificates.

Analysis and authentication of avocado oil by low-field benchtop NMR spectroscopy and chemometrics.

Avocado oil is a nutritious, edible oil produced from avocado fruit. It has high commercial value and is increasing in popularity, thus powerful analytical methods are needed to ensure its quality and authenticity. Recent advancements in low-field (LF) NMR spectroscopy allow for collection of high-quality data despite the use of low magnetic fields produced by non-superconductive magnets. Combined with chemometrics, LF NMR opens new opportunities in food analysis using targeted and untargeted approaches. Here, it was used to determine poly-, mono-, and saturated fatty acids in avocado oil. Although direct signal integration of LF NMR spectra was able to determine certain classes of fatty acids, it had several challenges arising from signal overlapping. Thus, we used partial least square regression and developed models with good prediction performance for fatty acid composition, with residual prediction deviation ranging 3.46-5.53 and root mean squared error of prediction CV ranging 0.46-2.48. In addition, LF NMR, combined with unsupervised and supervised methods, enabled the differentiation of avocado oil from other oils, namely, olive oil, soybean oil, canola oil, high oleic (OL) safflower oil, and high OL sunflower oil. This study showed that LF NMR can be used as an efficient alternative for the compositional analysis and authentication of avocado oil. PRACTICAL APPLICATION: Here, we describe the application of LF-NMR for fatty acid analysis and avocado oil authentication. LF-NMR can be an efficient tool for targeted and untargeted analysis, thus becoming an attractive option for companies, regulatory agencies, and quality control laboratories. This tool is especially important for organizations and entities seeking economic, user-friendly, and sustainable analysis solutions.

On the synthesis of diphenhydramine: Steady state kinetics, solvation effects, and in-situ Raman and benchtop NMR as PAT

Diphenhydramine is a first-generation antihistamine that is available over-the-counter to treat maladies such as allergic reactions and insomnia. Despite its ubiquity in society and high demand, the kinetics for either step of diphenhydramine synthesis have not been explored in detail. In this work, for the first step, a methodology has been devised to obtain kinetics from the heterogeneous halogenation of benzhydrol with hydrochloric acid in a batch reactor equipped with in-situ Raman probe and further verified with ex-situ low-field NMR spectroscopy. For the second step, the kinetics of etherification have been explored using a microfluidic flow reactor and at-line NMR spectroscopy in a variety of solvents. Arrhenius and Eyring parameters are determined for Step 2. We find that the reaction performance is well correlated with the acceptor number of the solvent indicating that the Lewis acidity of the solvent plays a significant role in the overall performance.

Compositional analysis of multilayered plastic constituents and constituent mixtures using benchtop 1H NMR spectroscopy.

Multilayered plastics are widely used in food packaging and other commercial applications due to their tailored functional properties. By layering different polymers, the multilayered composite material can have enhanced mechanical, thermal, and barrier properties compared to a single plastic. However, there is a significant need to recycle these multilayer plastics, but their complex structure offers significant challenges to their successful recycling. Ultimately, the use and recycling of these complex materials requires the ability to characterize the composition and purity as a means of quality control for both production and recycling processes. New advances and availability of low-field benchtop 1H NMR spectrometers have led to increasing interest in its use for characterization of multicomponent polymers and polymer mixtures. Here, we demonstrate the capability of low-field benchtop 1H NMR spectroscopy for characterization of three common polymers associated with multilayered packaging systems (low-density polyethylene [LDPE], ethylene vinyl alcohol [EVOH], and Nylon) as well as their blends. Calibration curves are obtained for determining the unknown composition of EVOH and Nylon in multilayered packaging plastics using both the EVOH hydroxyl peak area and an observed peak shift, both yielding results in good agreement with the prepared sample compositions. Additionally, comparison of results extracted for the same samples characterized by our benchtop spectrometer and a 500-MHz spectrometer found results to be consistent and within 2wt% on average. Overall, low-field benchtop 1H NMR spectroscopy is a reliable and accessible tool for characterization of these polymer systems.

Rapid reaction optimization by robust and economical quantitative benchtop 19F NMR spectroscopy.

The instrumental analysis of reaction mixtures is usually the rate-determining step in the optimization of chemical processes. Traditionally, reactions are analyzed by gas chromatography, HPLC or quantitative NMR spectroscopy on high-field spectrometers. However, chromatographic methods require elaborate work-up and calibration protocols, and high-field NMR spectrometers are expensive to purchase and operate. This protocol describes an inexpensive and highly effective analysis method based on low-field benchtop NMR spectroscopy. Its key feature is the use of fluorine-labeled model substrates that, because of the wide chemical shift range and high sensitivity of 19F, enable separate, quantitative detection of product and by-product signals even on low-field, permanent magnet spectrometers. An external lock/shim device obviates the need for deuterated solvents, permitting the direct, noninvasive measurement of crude reaction mixtures with minimal workup. The low field-strength facilitates a homogeneous excitation over a wide chemical shift range, minimizing systematic integration errors. The addition of the optimal amount of the nonshifting relaxation agent tris(acetylacetonato) iron(III) minimizes relaxation delays at full resolution, reducing the analysis time to 32 s per sample. The correct choice of processing parameters is also crucial. A step-by-step guideline is provided, the influence of all parameters, including adjustments needed when using high-field spectrometers, is discussed and potential pitfalls are highlighted. The wide applicability of the analytical protocol for reaction optimization is illustrated by three examples: a Buchwald-Hartwig amination, a Suzuki coupling and a C-H arylation reaction.

Facile identification of fluorosurfactant category in aqueous film-forming foam concentrates via optimized 19F NMR

Aqueous film-forming foams (AFFFs) are the primary source of toxic perfluoroalkyl and polyfluoroalkyl substances (PFAS) in wastewater. Thus, it is urgent to develop a facile and fast method for identifying fluorosurfactants in commercially available AFFFs. In this work, fluorine nuclear magnetic resonance (19F NMR) spectroscopy was optimized to measure AFFFs directly with the extra addition of 5% D2O as the locking reagent, and high-quality spectra could be acquired within 4 min (0.1% fluorosurfactant content). Recovery experiments demonstrated that the use of different AFFFs had no marked influence on the quantitative analysis of fluorosurfactants. Such method works with low-field NMR spectroscopy (1.4 T) as well. Two-dimensional (2D) 19F COSY NMR was used to make signal assignments for different fluorosurfactant derivatives. The optimized 19F NMR could quantify the commercially available fluorosurfactants in different AFFFs, identify them being in either the perfluorooctane sulfonate (PFOS) or fluorotelomer sulfonic acid (FTS) categories, and distinguish the head-group of PFOS and FTS derivatives, which exhibits great potentials in the developments of relevant commercial detections.

Accurate Determination of Trace Water in Organic Solution by Quantitative Nuclear Magnetic Resonance.

A new method accompanied by a derived equation for accurate determination of trace water was developed by using quantitative 1H nuclear magnetic resonance (qNMR) spectroscopy. Given that the response for each chemically distinct moiety is uniformly proportional to the number of the corresponding resonant nuclei within the analyte, it is practicable to directly quantify the water content via its proton number using qNMR. In this study, three water standards with known water contents (e.g., 10.02, 1.006, and 0.103 mg/g), which were accurately determined by a well-established Coulometric Karl Fischer (CKF) titration method, were measured by using the developed qNMR method. An excellent agreement between the results from these two methods was obtained. Then, the water content of Sudan I was determined by high-field NMR (HF-NMR) spectroscopy, and the water contents of acetone and bioethanol were measured by low-field NMR (LF-NMR) spectroscopy. These results were compared with the water content measured by the CKF method to confirm the applicability of the established qNMR method. The developed method can eliminate the influences of environmental humidity and background water in the solvent; subsequently, the results calculated by the derived equation were comparable to the nominal values. Under the optimal conditions, the limit of quantitation of this method was as low as 6.7 μg. The recommended sample sizes for practical samples with various water contents (e.g., 10.02, 1.006, and 0.103 mg/g) were determined to be 5, 50, and 60 mg, respectively, which are much smaller than those required for the CKF method. The new method has a static and stable process without any side reactions, and the traceability to the SI unit can be directly achieved through the NMR internal standard. This method overcomes the limitations of the CKF method, especially for measuring methanol-insoluble substances.

Analysis of Large Data Sets in a Physical Chemistry Laboratory NMR Experiment Using Python.

We describe an update to an experiment demonstrating low-field NMR spectroscopy in the undergraduate physical chemistry laboratory. A Python-based data processing and analysis protocol is developed for this experiment. The Python language is used in fillable worksheets in the notebook software JupyterLab, providing an interactive means for students to work with the measured data step by step. The protocol teaches methods for the analysis of large data sets in science or engineering, a topic that is absent from traditional chemistry curricula. Python is among the most widely used modern tools for data analysis. In addition, its open-source nature reduces the barriers for adoption in an educational laboratory.

On the Stability of Pickering and Classical Nanoemulsions: Theory and Experiments

Emulsification is a crucial technique for mixing immiscible liquids into droplets in various industries, such as food, cosmetics, biomedicine, agrochemistry, and petrochemistry. Quantitative analysis of the stability is pivotal before the utilization of these emulsions. Differences in X-ray attenuation for emulsion components and surface relaxation of the droplets may contribute to X-ray CT imaging and low-field NMR spectroscopy as viable techniques to quantify emulsion stability. In this study, Pickering (stabilized solely by nanoparticles) and Classical (stabilized solely by low molecular weight polymers) nanoemulsions were prepared with a high-energy method. NMR and X-ray CT were employed to constantly monitor the two types of nanoemulsions until phase separation. The creaming rates calculated from NMR match well with the results obtained from X-ray CT. Furthermore, we show that Stokes' law coupled with the classical Lifshitz-Slyozov-Wagner theory underestimates the creaming rate of the nanoemulsions compared to the experimental results from NMR and X-ray CT imaging. A new theory is proposed by fully incorporating the effects of Pickering nanoparticles, hydrocarbon types, volume fraction, size distribution, and flocculation on the droplet coarsening. The theoretical results agree well with the experimentally measured creaming rates. It reveals that the attachment of nanoparticles onto a droplet surface decreases the mass transfer for hydrocarbon molecules to move from the bulk aqueous phase into other droplets, thus slowing the Ostwald ripening. Therefore, Pickering nanoemulsions show a better stability behavior compared to Classical nanoemulsions. The impacts of hydrocarbon and emulsification energy on the stability of nanoemulsions are reported. These findings demonstrate that the stability of the nanoemulsions can be manipulated and optimized for a specific application, setting the stage for subsequent investigations of these nanodroplets.

Analysis of Adsorbed Polyphosphate Changes on Milled Titanium Dioxide, Using Low-Field Relaxation NMR and Photoelectron Spectroscopy.

In this study, changes in the adsorbed amount and surface structure of sodium hexametaphosphate (SHMP) were investigated for aluminum-doped TiO2 pigment undergoing milling. Relaxation NMR was utilized as a potential at-line technique to monitor the effect of milling on surface area and surface chemistry, while XPS was used primarily to consider the dispersant structure. Results showed that considerable amounts of weakly adsorbed SHMP could be removed with washing, and the level of dispersant removal increased with time, highlighting destructive effects of sustained high-energy milling. Nonetheless, there were no significant chemical changes to the dispersant, although increases to the bridging oxygen (BO) peak full width at half-maximum (FWHM) suggested some chemical degradation was occurring with excess milling. Relaxation NMR revealed a number of important features. Results with unmilled material indicated that dispersant adsorption could be tracked with pseudo-isotherms using the relative enhancement rate (Rsp), where the Rsp decreased with dispersant coverage, owing to partial blocking of the quadrupolar surface aluminum. Milled samples were also tracked, with very accurate calibrations of surface area possible from either T1 or T2 relaxation data for systems without dispersant. Behavior was considerably more complicated with SHMP, as there appeared to be an interplay between the dispersant surface coverage and relaxation enhancement from the surface aluminum. Nevertheless, findings highlight that relaxation NMR could be used as a real-time technique to monitor the extent of milling processes, so long as appropriate industrial calibrations can be achieved.

Low-Field Benchtop NMR Spectroscopy for Quantification of Aldehydic Lipid Oxidation Products in Culinary Oils during Shallow Frying Episodes.

Toxic aldehydic lipid oxidation products (LOPs) arise from the thermo-oxidative deterioration of unsaturated fatty acids present in heated culinary oils when exposed to high-temperature frying episodes, and currently these effects represent a major public health concern. In this study, we investigated the applications of low-field (LF), benchtop NMR analysis to detect and quantify toxic aldehyde species in culinary oils following their exposure to laboratory-simulated shallow frying episodes (LSSFEs) at 180 °C. Four culinary oils of variable fatty acid (FA) composition were investigated to determine the analytical capabilities of the LF NMR instrument. Oil samples were also analysed using a medium-field (400 MHz) NMR facility for comparative purposes. Aldehydes were quantified as total saturated and total α,β-unsaturated classes. The time-dependent production of α,β-unsaturated aldehydes decreased in the order chia > rapeseed ≈ soybean > olive oils, as might be expected from their polyunsaturated and monounsaturated FA (PUFA and MUFA, respectively) contents. A similar but inequivalent trend was found for saturated aldehyde concentrations. These data strongly correlated with medium-field 1H NMR data obtained, although LF-determined levels were significantly lower in view of its inability to detect or quantify the more minor oxygenated aldehydic LOPs present. Lower limit of detection (LLOD) values for this spectrometer were 0.19 and 0.18 mmol/mol FA for n-hexanal and trans-2-octenal, respectively. Aldehydic lipid hydroperoxide precursors of aldehydic LOPs were also detectable in LF spectra. We therefore conclude that there is scope for application of these smaller, near-portable NMR facilities for commercial or 'on-site' quality control determination of toxic aldehydic LOPs in thermally stressed frying oils.

Steady-State Free Precession sequences for high and low field NMR spectroscopy in solution: Challenges and opportunities

The receptivity of NMR spectroscopy is low when compared to other techniques. Historically, increasing the strength of the static magnetic field has been the major approach to increase NMR sensitivity. In recent years several polarization transfer protocols have been used to enhance the signal-to-noise ratio (SNR), although they require special accessories and/or sample preparation. In this paper, we consider both the challenges and opportunities of steady-state free precession (SSFP) pulse sequences as a simple and efficient alternative to enhance SNR, in standard high-resolution and benchtop low-resolution NMR spectrometers. The maximum gain in these sequences is obtained with the shortest time between the pulses (Tp). However, when Tp<T2, the SSFP signal contains FID and echo components which lead to phase, intensity, and truncation artifacts on spectra obtained by Fast Fourier transform (FT). Several phase alternation SSFP sequences were used to cancel the echo component and minimize these problems in the FT spectra. Krylov base diagonalization method (KBDM) was used to eliminate the phase and truncation problems in spectra acquired by SSFP pulse sequences and can be a viable alternative to FT. The experiments were performed in high and low resolution (bench top) NMR spectrometers and significant enhancements in SNR of low receptivity nuclei such as 13C and 15N could be achieved. The SSFP sequences were also shown to enhance SNR in nuclei with high receptivity such as 19F and 31P, in very dilute samples, as is common in environmental and biological samples.

Crosslinked networks in electron beam irradiated polyethylenes evaluated by proton low-field NMR spectroscopy

Effect of electron beam (EB) irradiation is analyzed in low and high density polyethylenes (LDPE and HDPE, respectively) at different doses. Parameters as important as degree of crystallinity, melting or crystallization temperatures are dependent on the initial PE molecular architecture, which also controls the gel content developed by action of EB irradiation and the EB dose applied. Thus, this gel amount, ascribed to formation of chain crosslinkings, is raised as irradiation dose increases, being larger in the HDPE than in the LDPE. In both, a plateau value is reached at the highest doses. The molecular changes that take place in both PEs during EB irradiation lead to a hindrance in their crystallization capacity, once macrochains are molten, and, accordingly, to a reduction in crystallinity and to formation of thinner crystallites. Variation with temperature of rigid and soft fractions together with their respective relaxation times is followed in the irradiated LDPE and HDPE specimens by pulse mixed magic-sandwich echo nuclear magnetic resonance (MSE-NMR) measurements. The network structure promoted in these PEs is evaluated by using the multiple-quantum nuclear magnetic resonance (MQ-NMR) approach, showing important differences caused by EB irradiation due to their intrinsic molecular characteristics.

Moisture Dynamics of Wood-Based Panels and Wood Fibre Insulation Materials.

Moisture performance is an important factor determining the resistance of wood-based building materials against fungal decay. Understanding how material porosity and chemistry affect moisture performance is necessary for their efficient use, as well as for product optimisation. In this study, three complementary techniques (X-ray computed tomography, infrared and low-field NMR spectroscopy) are applied to elucidate the influence of additives, manufacturing process and material structure on the liquid water absorption and desorption behaviour of a selection of wood-based panels, thermally modified wood and wood fibre insulation materials. Hydrophobic properties achieved by thermal treatment or hydrophobic additives such as paraffin and bitumen, had a major influence on water absorption and desorption rates. When hydrophobic additives did not play a role, pore distributions and manufacturing process had a decisive influence on the amount and rate of absorption and desorption. In that case, a higher porosity resulted in a higher water absorption rate. Our results show that there is a clear potential for tailoring materials towards specific moisture performance by better understanding the influence of different material characteristics. This is useful both for achieving desired moisture buffering as well as to increase service life of wood-based materials. From a sustainability perspective, fit-for-purpose moisture performance is often easier to achieve and preferred than wood protection by biocide preservative treatments.

Quality of Cuttlefish as Affected by Different Thawing Methods

ABSTRACT To investigate the effect of different thawing methods on the quality of frozen cuttlefish, six different thawing methods were used: hydrostatic thawing (HT), flowing water thawing (FWT), saline solution thawing (SWT), ultrasonic water thawing (UWT), microwave thawing (MT), and 4°C refrigerator thawing (RT). In this study, the water retention (thawing loss rate, centrifugal loss rate, and cooking loss), pH value, malondialdehyde content, TVB-N value, and sulfhydryl content were measured to evaluate the quality after thawing. Protein secondary structure was measured using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, protein tertiary structure was obtained by fluorescence spectroscopy and water migration was determined using low-field NMR spectroscopy. The results showed that the microwave thawing time was the shortest, but the water holding capacity after thawing was the worst, and the TVB-N content was the highest at 14.31 mg/100 g. Ultrasonic thawing led to the best water holding capacity, but ultrasound promoted the oxidation of protein and fat. Microscopic observation showed that the muscle fiber bundles in the saline solution thawing samples were compactly arranged and intact, with minimal gaps. The samples thawed in saline solution had the highest hardness and chewiness. The results of comprehensive analysis showed that saline solution thawing and ultrasonic water thawing are more suitable for thawing cuttlefish, and this study provides some theoretical basis for the selection of thawing methods in the actual production of cuttlefish.

Crosslinked Networks in Electron Beam Irradiated Polyethylenes Evaluated by Proton Low-Field Nmr Spectroscopy

Crosslinked Networks in Electron Beam Irradiated Polyethylenes Evaluated by Proton Low-Field Nmr Spectroscopy

Properties and digestibility of a novel porous starch from lotus seed prepared via synergistic enzymatic treatment

The objective was to investigate the effect of synergistic enzymatic treatment on the properties and digestibility of a novel C-type lotus seed porous starch (LPS). Scanning electron microscopy showed that the densest and most complete pores were formed on the surface of LPS when the concentration of enzymes added was 1.5% (LS-1.5E). With increases in enzyme addition, the oil and water absorption of the porous starch increased and reached maxima at 1.5% of enzyme. Increased in the specific surface area, total pore volume and average pore diameter of LPS were determined by low-temperature nitrogen adsorption, while when the enzymes exceeded 1.5%, there were no significant changes. Compared to lotus seed starch (LS), the particle size of LPS also decreased. With the increases in enzyme addition, LPS exhibited higher relative crystallinity and ordering structure by XRD and FTIR. The results by SAXS confirmed that LPS had higher ordered semi-crystalline lamellar and denser lamellar structure compared to LS. Low-field 1H NMR spectroscopy indicated that the proportion of bound water in LPS increased, while the proportion of bulk water decreased. Moreover, the degree of hydrolysis of LPS was lower than that of LS, and the content of rapidly digestible starch decreased, while the content of slowly digestible starch and resistant starch increased with the enzyme addition, which was consistent with the structural properties.

Application of 1H Low-Field NMR Spectroscopy for the Determination of the Concentration and Molecule Weight of Polycarboxylate Superplasticizers

Application of 1H Low-Field NMR Spectroscopy for the Determination of the Concentration and Molecule Weight of Polycarboxylate Superplasticizers

Fourier and Laplace-like low-field NMR spectroscopy: The perspectives of multivariate and artificial neural networks analyses

Low field Nuclear Magnetic Resonance (LF-NMR) is a rich source of information for a wide range of samples types. These can be hard or soft solids, such as plastics or elastomers; bulk liquids or liquids absorbed in porous materials, and can come from biomaterials, biological tissues, archaeological artifacts, cultural heritage objects. LF-NMR instruments present a significant advance especially for in situ, ex situ and in vivo measurement of relaxation and diffusion. Moreover, high resolution 1D and 2D spectroscopy, as well as magnetic resonance (MR) imaging are available in these fields. In this work we discuss the advanced analysis of the data measured in LF-NMR from the perspectives of tertiary level that implies the analysis on principal components (PCA), and on the quaternary analysis that uses an artificial neural network (ANN). The principles of PCA and ANN are largely discussed. For the PCA analysis, a series of 52 spectra were analyzed, having been recorded in vivo by LF-NMR. Of these spectra, 38 were generated from normal uterus, 7 by uterus tissue with endometrial cancer, and another 7 were obtained from tissues of women with uterine cervical cancer. The PC1 vs PC2 plot was further analyzed using an artificial neural network, and the results are presented as 2D maps of probability. Furthermore, the perspectives of applying an ANN to solve the problem of Laplace-like inversion are discussed. An example of such ANN was presented and the performance was discussed. Finally, a model of complex ANN, capable to sequentially solve this kind of problems specific to LF-NMR is proposed and discussed.

Compact NMR Spectroscopy for Low-Cost Identification and Quantification of PVC Plasticizers.

Polyvinyl chloride (PVC), one of the most important polymer materials nowadays, has a large variety of formulations through the addition of various plasticizers to meet the property requirements of the different fields of applications. Routine analytical methods able to identify plasticizers and quantify their amount inside a PVC product with a high analysis throughput would promote an improved understanding of their impact on the macroscopic properties and the possible health and environmental risks associated with plasticizer leaching. In this context, a new approach to identify and quantify plasticizers employed in PVC commodities using low-field NMR spectroscopy and an appropriate non-deuterated solvent is introduced. The proposed method allows a low-cost, fast, and simple identification of the different plasticizers, even in the presence of a strong solvent signal. Plasticizer concentrations below 2 mg mL−1 in solution corresponding to 3 wt% in a PVC product can be quantified in just 1 min. The reliability of the proposed method is tested by comparison with results obtained under the same experimental conditions but using deuterated solvents. Additionally, the type and content of plasticizer in plasticized PVC samples were determined following an extraction procedure. Furthermore, possible ways to further decrease the quantification limit are discussed.