Low-field Benchtop Nuclear Magnetic Resonance Research Articles

Discriminating extra virgin olive oils from common edible oils: Comparable performance of PLS-DA models trained on low-field and high-field 1H NMR data.

Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper edible oils or fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price. There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high-field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low-field benchtop NMR presents an affordable alternative. We compared the predictive performance of partial least squares discrimination analysis (PLS-DA) models trained on low-field 60 MHz benchtop proton (1H) NMR and high-field 400 MHz 1H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils. We demonstrate that PLS-DA models trained on low-field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high-field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths.

Cryogen-free 400-MHz nuclear magnetic resonance spectrometer as a versatile tool for pharmaceutical process analytical technology.

The discovery of new ceramic materials containing Ba-La-Cu oxides in 1986 that exhibited superconducting properties at high temperatures in the range of 35 K or higher, recognized with the Nobel Prize in Physics in 1987, opened a new world of opportunities for nuclear magnetic resonance (NMRs) and magnetic resonance imaging (MRIs) to move away from liquid cryogens. This discovery expands the application of high temperature superconducting (HTS) materials to fields beyond the chemical and medical industries, including electrical power grids, energy, and aerospace. The prototype 400-MHz cryofree HTS NMR spectrometer installed at Amgen's chemistry laboratory has been vital for a variety of applications such as structure analysis, reaction monitoring, and CASE-3D studies with RDCs. The spectrometer has been integrated with Amgen's chemistry and analytical workflows, providing pipeline project support in tandem with other Kinetic Analysis Platform technologies. The 400-MHz cryofree HTS NMR spectrometer, as the name implies, does not require liquid cryogens refills and has smaller footprint that facilitates installation into a chemistry laboratory fume hood, sharing the hood with a process chemistry reactor. Our evaluation of its performance for structural analysis with CASE-3D protocol and for reaction monitoring of Amgen's pipeline chemistry was successful. We envision that the HTS magnets would become part of the standard NMR and MRI spectrometers in the future. We believe that while the technology is being developed, there is room for all magnet options, including HTS, low temperature superconducting (LTS) magnets, and low field benchtop NMRs with permanent magnets, where utilization will be dependent on application type and costs.

Detection of common adulterants in olive oils by bench top 60 MHz 1H NMR with partial least squares regression

Olive oil is the oil obtained from the fruit of the olive tree, Olea europaea L., and is commonly used in cooking, cosmetics, and soaps. The high value and demand for olive oil products has led to some producers adding cheaper edible non-olive oils to olive oil to increase their profitability. Many of these adulterant oils have similar taste profiles to extra virgin olive oil; however, these can cause allergic reactions in individuals with sensitivities to the non-olive oil. Given the implications of olive oil adulteration, there is a demand for methods to identify and quantify adulterant oils in olive oil samples. This work explores the utility of low-field benchtop nuclear magnetic resonance (NMR) with a novel chemometrics workflow for the quantification of non-olive oils in authentic extra virgin olive oil samples. The measurements were obtained using a 60 MHz 1H NMR. The icoshift algorithm was utilized for alignment, and partial least squares regression models of the entire NMR spectrum were used for quantification. Here, 17 different varieties of edible non-olive oils were investigated. The models were highly linear, accurate, and precise. Most of these adulterant oils were detectable below 10% v/v in extra virgin olive oil samples.

Predicting Mandarin Fruit Acceptability: From High-Field to Benchtop NMR Spectroscopy.

Recent advances in nuclear magnetic resonance (NMR) have led to the development of low-field benchtop NMR systems with improved sensitivity and resolution suitable for use in research and quality-control laboratories. Compared to their high-resolution counterparts, their lower purchase and running costs make them a good alternative for routine use. In this article, we show the adaptation of a method for predicting the consumer acceptability of mandarins, originally reported using a high-field 400 MHz NMR spectrometer, to benchtop 60 MHz NMR systems. Our findings reveal that both instruments yield comparable results regarding sugar and citric acid levels, leading to the development of virtually identical predictive linear models. However, the lower cost of benchtop NMR systems would allow cultivators to implement this chemometric-based method as an additional tool for the selection of new cultivars.

Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring

Low-cost and user-friendly benchtop low-field nuclear magnetic resonance (NMR) spectrometers are typically used to monitor food processes in the food industry. Because of excessive spectral overlap, it is difficult to characterize food mixtures using low-field NMR spectroscopy. In addition, for standard compounds, low-field benchtop NMR data are typically unavailable compared to high-field NMR data, which have been accumulated and are reusable in public databases. This work focused on NMR parameter visualization of the chemical structure and mobility of mixtures and the use of high-field NMR data to analyze benchtop NMR data to characterize food process samples. We developed a tool to easily process benchtop NMR data and obtain chemical shifts and T2 relaxation times of peaks, as well as transform high-field NMR data into low-field NMR data. Line broadening and time–frequency analysis methods were adopted for data processing. This tool can visualize NMR parameters to characterize changes in the components and mobilities of food process samples using benchtop NMR data. In addition, assignment errors were smaller when the spectra of standard compounds were identified by transferring the high-field NMR data to low-field NMR data rather than directly using experimentally obtained low-field NMR spectra.

Quantitative measurement of Mono-Ethylene Glycol (MEG) content using low-field Nuclear Magnetic Resonance (NMR)

Extraction of natural gas from remote subsea reservoirs is often accompanied by increased flow assurance risks such as hydrate blockages, which if formed can pose a serious threat to both productivity and safety. Such hydrates can be prevented via injection of monoethylene glycol (MEG) to subsea systems, which is subsequently regenerated via distillation and re-injected. Inaccurate compositional analysis of reclaimed MEG can, however, result in both process inefficiencies and over-use of MEG during re-injection. Limitations in current analytical methods mean that there is demand for the development and optimisation of alternative methods for quantifying MEG within the recycled fluids. Here, benchtop Nuclear Magnetic Resonance (NMR) Spectroscopy is proven to be an accurate and reproducible method of monitoring such MEG composition to within a concentration error of 1 wt% in the presence of a range of impurities at concentrations consistent with those encountered in industry. Binary mixtures of MEG and water, and those with either methyl diethanolamine (MDEA) or acetic acid, provided accurate determination of MEG concentration within this range. The presence of saline water similarly produced concentration errors within 1 wt% with adequate optimisation of the NMR methods used. Industrial applicability as an on-line measurement was demonstrated by accurate MEG concentration determination during continuous flow (0–20 mL min−1). These results demonstrate low-field benchtop NMR spectrometry to be a viable candidate for MEG composition monitoring under typical environments encountered during the recycling of MEG for hydrate inhibition.

Benchtop nuclear magnetic resonance-based metabolomic approach for the diagnosis of bovine tuberculosis.

Even though enormous efforts and control strategies have been implemented, bovine tuberculosis (TB) remains a significant source of health and socioeconomic concern. The standard method used in TB eradication programs for in vivo detection is the tuberculin skin test. However, the specificity of the tuberculin skin test is affected by infection with non-tuberculous mycobacteria or by vaccination. Thus, some animals are not correctly diagnosed. This study aimed first to identify a plasma metabolic TB profile by high-field (HF) nuclear magnetic resonance (NMR) spectroscopy and second measure this characteristic TB metabolic profile using low-field benchtop (LF) NMR as an affordable molecular technology for TB diagnosis. Plasma samples from cattle diagnosed with TB (derivation set, n=11), diagnosed with paratuberculosis (PTB, n=10), PTB-vaccinated healthy control (n=10) and healthy PTB-unvaccinated control (n=10) were analyzed by NMR. Unsupervised Principal Component Analysis (PCA) was used to identify metabolic differences between groups. We identified 14 metabolites significantly different between TB and control animals. The second group of TB animals was used to validate the results (validation set, n=14). Predictive models based on metabolic fingerprint acquired by both HF and LF NMR spectroscopy successfully identified TB versus control subjects (Area under the curve of Receiver Operating Characteristic over 0.92, in both models; Confidence Interval 0.77-1). In summary, plasma fingerprinting using HF and LF-NMR differentiated TB subjects from uninfected animals, and PTB and PTB-vaccinated subjects who may provide a TB-false positive, highlighting the use of LF-NMR-based metabolomics as a complementary or alternative diagnostic tool to the current diagnostic methods.

Improved Description of Organic Matter in Shales by Enhanced Solid Fraction Detection with Low-Field 1H NMR Relaxometry

Nuclear magnetic resonance (NMR) relaxometry is routinely used to characterize the oil fraction in unconventional shale formations with low-field benchtop NMR hardware. However, organic phases with restricted mobility like kerogen and bitumen are typically not detectable with the standard Carr–Purcell–Meiboom–Gill (CPMG) method on such equipment, with the rapid spin–spin (T2) signal decay of these solid/viscous components not visible to the measurement. The solid-echo (SE) and mixed-echo (ME) pulse sequences offer an alternative to the CPMG, extending the lifetime of the time-domain signal and allowing the capture of solid hydrogen-containing species. Accordingly, we combine NMR relaxation data generated from the application of the CPMG, SE, and ME experiments to a set of powdered oil- and brine-saturated Eagle Ford shale samples, with the aim of identifying and quantifing both the immobile (kerogen/bitumen) and mobile (oil/brine) components. Two-dimensional relaxometry correlating spin–lattice relation times T1 to the effective decay times T2 obtained using CPMG and SE techniques provides more complete information on the immobile phases in the shales, such as solid organic matter and clay-bound water. The three spin–echo techniques have similar efficiencies when detecting signal from mobile and low-viscosity fluids, while significant differences are seen in shale samples containing immobile organics. Overall, the combination of the three spin echo techniques provides an improved description of the solid, viscous, and liquid components in the investigated shales at low magnetic field.

Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker

Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.

Application of benchtop low-field NMR spectrometers in the refining industry: A multivariate calibration approach for rapid characterization of crude oils.

High-field nuclear magnetic resonance (NMR) has proven to be a valuable tool to analyze petroleum products but has never acquired widespread acceptance in routine work in oil refinery due to the high cost. The advent of compact, reliable, and affordable cryogen-free low-field benchtop NMR spectrometers suggest a possible role of such instrument for a variety of uses in refining spanning from routine lab work applications to online analysis. In this work, we report the development of a novel benchtop NMR application to estimate the API gravity, sulfur content, total acidity number (TAN), and distillation yields of crude petroleum from 60 MHz 1 H NMR spectra and partial least square (PLS) regression models. The results obtained on a dataset of over 170 crude oil samples and tested with external validation set show performances in terms of root mean square standard error of prediction (RMSEP) matching the analytical methods' ASTM precision. This novel benchtop NMR and multivariate analysis application can thus be used in typical refinery laboratories to provide within minutes and without physical distillation, reliable estimates of the most important properties usually measured on the crude petroleum during refining. The method proves to be a fast, cheaper alternative to the current analytical options providing readily available data for managing crude oil and has high potential to be further exploited for online application.

Monitoring Hydrogenation Reactions using Benchtop 2D NMR with Extraordinary Sensitivity and Spectral Resolution.

Low‐field benchtop nuclear magnetic resonance (BT‐NMR) spectrometers with Halbach magnets are being increasingly used in science and industry as cost‐efficient tools for the monitoring of chemical reactions, including hydrogenation. However, their use of low‐field magnets limits both resolution and sensitivity. In this paper, we show that it is possible to alleviate these two problems through the combination of parahydrogen‐induced polarization (PHIP) and fast correlation spectroscopy with time‐resolved non‐uniform sampling (TR‐NUS). PHIP can enhance NMR signals so that substrates are easily detectable on BT‐NMR spectrometers. The interleaved acquisition of one‐ and two‐dimensional spectra with TR‐NUS provides unique insight into the consecutive moments of hydrogenation reactions, with a spectral resolution unachievable in a standard approach. We illustrate the potential of the technique with two examples: the hydrogenation of ethylphenyl propiolate and the hydrogenation of a mixture of two substrates – ethylphenyl propiolate and ethyl 2‐butynoate.

Low-Field, Benchtop NMR Spectroscopy as a Potential Tool for Point-of-Care Diagnostics of Metabolic Conditions: Validation, Protocols and Computational Models

Novel sensing technologies for liquid biopsies offer promising prospects for the early detection of metabolic conditions through omics techniques. Indeed, high-field nuclear magnetic resonance (NMR) facilities are routinely used for metabolomics investigations on a range of biofluids in order to rapidly recognise unusual metabolic patterns in patients suffering from a range of diseases. However, these techniques are restricted by the prohibitively large size and cost of such facilities, suggesting a possible role for smaller, low-field NMR instruments in biofluid analysis. Herein we describe selected biomolecule validation on a low-field benchtop NMR spectrometer (60 MHz), and present an associated protocol for the analysis of biofluids on compact NMR instruments. We successfully detect common markers of diabetic control at low-to-medium concentrations through optimised experiments, including α-glucose (≤2.8 mmol/L) and acetone (25 µmol/L), and additionally in readily accessible biofluids, particularly human urine. We present a combined protocol for the analysis of these biofluids with low-field NMR spectrometers for metabolomics applications, and offer a perspective on the future of this technique appealing to ‘point-of-care’ applications.

Magnetic resonance diffusion measurements of droplet size in drilling fluid emulsions on a benchtop instrument

Oil-based drilling fluids are complex emulsio-dispersions used in the construction of subsurface wellbores. Design and control of the rheological properties are crucial for successful drilling operations because the fluid performs several critical functions, such as hole cleaning (particle transport) and ensuring wellbore stability. One of the physical characteristics of the fluid that relates to rheology is the size of the water-in-oil emulsion droplets. Here we demonstrate the use of nuclear magnetic resonance (NMR) pulsed field gradient (PFG) diffusion measurements to determine droplet size distributions in oil-based drilling fluid analogues and a commercial formulation. NMR PFG allows these optically opaque samples to be measured without dilution, and the measurement is sensitive only to the liquid components. Although the NMR technique is established, the application to drilling fluids is novel. Through simulation and experiment, the suitability of a low-field benchtop NMR instrument (commonly used for rock core analysis in the petroleum industry) for measuring droplet size distributions in these fluids is explored. Despite limitations on the available gradient strength and the bulk diffusion coefficient of the brine, droplet radii in the range a = 1 μm to 50 μm are measured. The low-field NMR instrument is shown to be suitable for characterizing drilling fluids and similar complex emulsions.

NMR derived water content from high magnetic susceptibility rock cuttings

Nuclear magnetic resonance (NMR) well logging is a well-established technique for in-situ fluid measurement. It is however not routinely used in the mining industry to quantify water content in high magnetic susceptibility iron ore rock cuttings because the ore’s magnetic properties adversely affect the measurement. In this study the relationship between NMR signal intensity and magnetic susceptibility is studied using a low magnetic field (2 MHz) benchtop NMR instrument. Magnetic susceptibility is commonly measured during well logging protocols and therefore could be used to correct and hence render quantitative NMR measurements of moisture content in iron ore. In this study NMR signal from water-saturated synthetic samples (magnetite/maghemite/hematite mixed with borosilicate glass beads) is measured as a function of iron content and magnetic susceptibility to obtain such a correlation. This correlation is then applied to iron ore rock cuttings. Comparison with gravimetric measurements show that a standard error of estimate of water content across all samples tested of 6.4 wt% using no correction, is reduced to 1.5 wt% using the corrections, corresponding to a relative error reduction from 47% to 11%. Additional comparison with whole rock cores shows that a higher magnetic susceptibility threshold for using the corrections is required for whole rock cores than for the rock cuttings, this difference requires further study. These results encourage the broad use of these types of correlations for NMR measurements of iron rich cuttings and application of NMR well logging to iron ore deposits.

A 43 MHz Low-Field Benchtop 1H Nuclear Magnetic Resonance Method to Discriminate Perilla Oil Authenticity.

The aim of this study was to discriminate the authenticity of perilla oils distributed in Korea using their 1H nuclear magnetic resonance (NMR) spectra acquired by a 43 MHz low-field benchtop NMR spectrometer. Significant differences existed in the integration values of all 6 peaks found in the spectrum between authentic and adulterated perilla oil samples. The integration values of 4 peaks that signify the methylene protons present in all fatty acids (FA) and allylic or olefinic protons present in all unsaturated FA were the best variables for establishing perilla oil authenticity. The procedure for applying the range of variables found in authentic perilla oil samples correctly discriminated between the samples of perilla oils with soybean oils added at concentrations of ≥ 6 vol%. The results demonstrated that this NMR procedure is a possible cost-effective alternative to the high-field 1H NMR method for discriminating the authenticity of perilla oils.

Determination of Alcohol Content in Alcoholic Beverages Using 45 MHz Benchtop NMR Spectrometer

Alcohol or ethanol is considered the most widely used recreational drug worldwide, and its production, consumption, and sale are strictly regulated by laws. Alcohol content of alcoholic beverages (wine, beers, and spirits) is about 3–50% v/v. Analytical methods to determine the alcohol content must be reliable, precise, and accurate. In this study, the amount of ethanol in several alcoholic beverages was determined using a 45 MHz low-field benchtop NMR (nuclear magnetic resonance) spectrometer. Internal standard and standard addition analytical methods were utilized to quantify ethanol. For both methods, acetic acid or acetonitrile was used as internal standard to quantify alcohol content by using the peak area corresponding to the methyl peaks of ethanol, acetic acid, or acetonitrile. Results showed that internal standard method gave values of percent alcohol that are in close agreement with the indicated label as confirmed by running the samples in a 400 MHz high-field NMR spectrometer using acetic acid as internal standard. This study demonstrates the utility of a benchtop NMR spectrometer that can provide an alternative technique to analyze percent alcohol in alcoholic products.

Optimized Droplet Sizing of Water-in-Crude Oil Emulsions Using Nuclear Magnetic Resonance

Water-in-crude oil emulsions are an increasing problem during production. Essential to any emulsion breaking method is an ability to accurately measure droplet size distributions; this is rendered extremely difficult given that the samples are both concentrated and opaque. Here, we systematically consider the use of a standard, low-field benchtop nuclear magnetic resonance (NMR) apparatus to accurately measure the droplet size distributions. Such measurements are challenging because the NMR signal from the oil phase erroneously contributes to the measured water droplet size distribution. Conventionally, the oil-phase signal is nulled-out based on differences in the NMR T1 relaxation parameter between water and oil. However, in the case of crude oil, the oil presents a broad T1 distribution, rendering this approach infeasible. On the basis of this oil T1 distribution, we present an optimization routine that adjusts various NMR measurement timing parameters [observation time (Δ) and inversion time (Tinv)] to effectively eliminate this erroneous crude oil contribution. An implementation of this optimization routine was validated against measurements performed using unambiguous chemical-shift selection of the water (droplet) signal, as would conventionally be provided by high-field superconducting NMR spectrometers. We finally demonstrate successful droplet sizing of a range of water-in-crude oil emulsions.

A non-invasive study of flow dynamics in membrane distillation hollow fiber modules using low-field nuclear magnetic resonance imaging (MRI)

Low-field bench-top nuclear magnetic resonance imaging (MRI) has been applied to investigate the hydrodynamics in novel hollow fiber modules with four different configurations of randomly-packed, spacer-knitted, curly and semi-curly fibers, specifically designed for the membrane distillation (MD) process. Imaging, spatially resolved velocity maps and propagators (probability distributions of displacement/velocity) were all acquired in the modules with flow in the shell side. The MRI data were correlated with overall module performance.The results have revealed that the curly configuration exhibited more significant transverse flow and hence enhanced mixing, compared to the randomly packed configuration; this was consistent with an enhanced MD performance in terms of permeation flux. Interestingly, the velocity maps of the spacer-knitted fiber design indicated a significant flow channeling in the center of the module, despite its enhanced MD performance. Fortunately, combined with further investigations on the localized velocity images of this configuration, the acquisition of propagators provided valuable information in revealing the existence of reduced stagnant regions and significant transverse flow at varied operating conditions, which indicated a better overall mixing and hence confirmed its module performance.