Application Of Nuclear Magnetic Resonance Research Articles

Scanning Nuclear Spin Level Anticrossings by Constant-Adiabaticity Magnetic Field Sweeping of Parahydrogen-Induced 13C Polarization.

The polarization transfer between 1H protons and 13C heteronuclei is of central importance in the development of parahydrogen-based hyperpolarization techniques dedicated to the production of 13C-hyperpolarized molecular probes. Here we unveil the spin conversion efficiency in the polarization transfer between parahydrogen-derived protons and 13C nuclei of an ethyl acetate biomolecule, formed by the homogeneous hydrogenation of vinyl acetate with parahydrogen, obtained by applying constant-adiabaticity sweep profiles at ultralow magnetic fields. The experiments employed natural C-13 abundance. Spin level anticrossings can be detected experimentally using a scanning approach and are selected to improve the polarization transfer efficiency. 13C polarization of up to 12% is readily achieved on the carbonyl center. The results demonstrate the simplicity, reproducibility, and high conversion efficiency of the technique, opening the door for a refined manipulation of hyperpolarized spins in both basic science experiments (e.g., state-selected spectroscopy in the strong-coupling regime) and biomedical nuclear magnetic resonance applications.

Study of native oil-bearing rocks of the Cuban basin by high resolution NMR spectroscopy

Application of high resolution 13C nuclear magnetic resonance (NMR) spectroscopy to characterize Cuba oil and oil-containing rock samples from Cuban basin was demonstrated. The chemical shifts of 13C NMR functional groups for later determination the composition of the oil and rock samples were determined. The different contribution of the studied samples in the aliphatic and aromatic areas was determined. Molar fractions of primary, secondary, quaternary, tertiary, aromatic groups, aromaticity factor and the mean length of hydrocarbon chain length of aliphatic hydrocarbons were estimated. Comparative analysis on the quantitative level for all major hydrocarbon components, the aromaticity factor and the mean length of the hydrocarbon chain were carried out.

Application of nuclear magnetic resonance in food analysis

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful techniques to analyze sample components, determine the structures of compounds and study chemical reaction processes. NMR is a rapid and noninvasive analytical method that was initially used to study moisture in food. The structural composition of food can be determined by analyzing the components of oil, protein and carbohydrates. The combination of NMR and multivariate statistical data has become increasingly popular in the field of food science. However, due to its low sensitivity and imperfect technical knowledge, NMR still has great development potential in the field of food science and very bright prospects. This review focuses on the application of NMR in food analysis, including oil, red wine, honey, milk, fruits and vegetables. NMR can quickly identify various compounds, distinguish the geographical origin of species, assess food quality, reveal various fraud behaviors, and predict the shelf life of food.

Hydraulic Conductivity from Nuclear Magnetic Resonance Logs in Sediments with Elevated Magnetic Susceptibilities.

This study examined the application of slim-hole nuclear magnetic resonance (NMR) tools to estimate hydraulic conductivity (KNMR ) in an unconsolidated aquifer that contains a range of grain sizes (silt to gravel) and high and variable magnetic susceptibilities (MS) (10-4 to 10-2 SI). A K calibration dataset was acquired at 1-m intervals in three fully screened wells, and compared to KNMR estimates using the Schlumberger-Doll research (SDR) equation with published empirical constants developed from previous studies in unconsolidated sediments. While KNMR using published constants was within an order of magnitude of K, the agreement, overprediction, or underprediction of KNMR varied with the MS distribution in each well. An examination of the effects of MS on NMR data and site-specific empirical constants indicated that the exponent on T2ML (n-value in the SDR equation, representing the diffusion regime) was found to have the greatest influence on KNMR estimation accuracy, while NMR porosity did not improve the prediction of K. KNMR was further improved by integrating an MS log into the NMR analyses. A first approach detrended T2ML for the effects of MS prior to calculating KNMR , and a second approach introduced an MS term into the SDR equation. Both were found to produce similar refinements of KNMR in intervals of elevated MS. This study found that low frequency NMR logging with short echo times shows promise for sites with moderate to elevated MS levels, and recommends a workflow that examines parameter relationships and integrates MS logs into the estimation of KNMR .

SpinSPJ: a novel NMR scripting system to implement artificial intelligence and advanced applications

BackgroundSoftware for nuclear magnetic resonance (NMR) spectrometers offer general functionality of instrument control and data processing; these applications are often developed with non-scripting languages. NMR users need to flexibly integrate rapidly developing NMR applications with emerging technologies. Scripting systems offer open environments for NMR users to write custom programs. However, existing scripting systems have limited capabilities for both extending the functionality of NMR software’s non-script main program and using advanced native script libraries to support specialized application domains (e.g., biomacromolecules and metabolomics). Therefore, it is essential to design a novel scripting system to address both of these needs.ResultHere, a novel NMR scripting system named SpinSPJ is proposed. It works as a plug-in in the Java based NMR spectrometer software SpinStudioJ. In the scripting system, both Java based NMR methods and original CPython based libraries are supported. A module has been developed as a bridge to integrate the runtime environments of Java and CPython. The module works as an extension in the CPython environment and interacts with Java via the Java Native Interface. Leveraging this bridge, Java based instrument control and data processing methods of SpinStudioJ can be called with the CPython style. Compared with traditional scripting systems, SpinSPJ better supports both extending the non-script main program and implementing advanced NMR applications with a rich variety of script libraries. NMR researchers can easily call functions of instrument control and data processing as well as developing complex functionality (such as multivariate statistical analysis, deep learning, etc.) with CPython native libraries.ConclusionSpinSPJ offers a user-friendly environment to implement custom functionality leveraging its powerful basic NMR and rich CPython libraries. NMR applications with emerging technologies can be easily integrated. The scripting system is free of charge and can be downloaded by visiting http://www.spinstudioj.net/spinspj.

NP-MRD: the Natural Products Magnetic Resonance Database.

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation. Details of these database features, how they are implemented and plans for future upgrades are also provided. The NP-MRD is available at https://np-mrd.org.

Growth-phase dependence of bacterial membrane lipid profile and labeling for in-cell solid-state NMR applications

Cell labeling is a preliminary step in multiple biophysical approaches, including the solid-state nuclear magnetic resonance (NMR) study of bacteria in vivo. Deuterium solid-state NMR has been used in the past years to probe bacterial membranes and their interactions with antimicrobial peptides, following a standard labeling protocol. Recent results from our laboratory on a slow-growing bacterium has shown the need to optimize this protocol, especially the bacterial growth time before harvest and the concentration of exogenous labeled fatty acids to be used for both Escherichia coli and Bacillus subtilis. It is also essential for the protocol to remain harmless to cells while providing optimal labeling. We have therefore developed a fast and facile approach to monitor the lipid composition of bacterial membranes under various growth conditions, combining solution 31P NMR and GCMS. Using this approach, the optimized labeling conditions of Escherichia coli and Bacillus subtilis with deuterated palmitic acid were determined. Our results show a modification of B. subtilis phospholipid profile as a function of the growth stage, as opposed to E. coli. Our protocol recommends low concentrations of exogenous palmitic acid in the growth medium, and bacteria harvest after the exponential phase.

NMR chemical shifts of carbon atoms and characteristic shift ranges in the oil sample

Application of high resolution 13C nuclear magnetic resonance (NMR) spectroscopy to characterize crude oil was demonstrated. The chemical shifts of 13C NMR functional groups that determine the composition of the oil sample were determined. Molar fractions of primary, secondary, quaternary, tertiary, aromatic groups, aromatic factor and average hydrocarbon chain length of aliphatic hydrocarbons of the oil sample according to 13C NMR spectra were determined. Detailed description of the 13C NMR spectra of the oil sample using a single consideration of three NMR spectra: 13C, 13C Attached Proton Test (APT), 13C with Gated Decoupling (GD) was performed. The different contribution of the studied oil sample in the aliphatic (10–75 ppm) and aromatic (115–165 ppm) areas of the 13C NMR spectra was determined. The presence of all major hydrocarbon components in the studied oil sample was established on the quantitative level, the aromaticity factor and the mean length of the hydrocarbon chain were evaluated. Quantitative fractions of aromatic molecules and functional groups constituting oil hydrocarbons were determined. In this work we demonstrate that the attached proton test and gated decoupling 13C NMR spectroscopy can afford all information to complete the chemical shift assignment of an oil sample, especially for determination of long range 1H–13C coupling constants and 13C multiplicity.

1H NMR Spectroscopy of the New Xalapa Molecule

Proton nuclear magnetic resonance (¹H NMR) is the application of nuclear magnetic resonance in NMR spectroscopy with respect to 1H within the molecules of a substance, in order to determine the structure of its molecules.

NMR technique and methodology in botanical health product analysis and quality control

Botanicals have played an important role in maintaining human health and well-being throughout history. During the past few decades in particular, the use of botanical health products has gained more popularity. Whereas, quality, safety and efficacy concerns have continuously been critical issues due to the intrinsic chemical complexity of botanicals. Chemical analytical technologies play an imperative role in addressing these issues. Nuclear magnetic resonance (NMR) spectroscopy has proven to be a powerful and useful tool for the investigation of botanical health products. In this review, NMR techniques and methodologies that have been successfully applied to the research and development of botanical health products in all stages, from plants to products, are discussed and summarized. Furthermore, applications of NMR together with other analytical techniques in a variety of domains of botanical health products investigation, such as plant species differentiation, adulteration detection, and bio-activity evaluation, are discussed and illustrated with typical examples. This article provides an overview of the potential uses of NMR techniques and methodologies in an attempt to further promote their recognition and utilization in the field of botanical health products analysis and quality control.

Detection of Planar Defects in Multilayered GFRP Composite Structures Using Low-Field Nuclear Magnetic Resonance

Adhesively bonded interfaces of glass fiber– reinforced plastics (GFRP) composite to rubber and rubber to propellant were investigated for planar interfacial defects with a spatial resolution of 100 μm. Single-sided low-field nuclear magnetic resonance (NMR) with a magnetic field strength of 0.3 T (12.88 MHz proton frequency) has been used for noninvasive inspection of planar defects in GFRP-based multilayered composite structures. Further, in this paper, the application of low-field NMR for adhesive liner thickness measurement is also demonstrated. The investigation revealed applicability of single-sided low-field NMR for onsite field applications. Results were compared with other nondestructive evaluation (NDE) techniques: acousto-ultrasonic and radiographic testing (RT). It is observed that single-sided low-field NMR is an excellent NDE tool to study adhesive bonds and defects such as debonding, variations in thickness to accuracies ranging from 50 to 200 μm, and degradation. In comparison with the acousto-ultrasonic technique and RT, single-sided low-field NMR is observed to be more sensitive.

Investigation of hydration and setting process in nanosilica-cement blended pastes: In situ characterization using low field nuclear magnetic resonance

In order to characterize the effect of nano-SiO2 addition on early properties of Portland cement paste, low-field nuclear magnetic resonance (NMR) was used to monitor the hydration process and microstructure evolution. The relaxation signals of low-field NMR can provide the information about the water molecules status and corresponding content, thus indirectly revealing the microstructure evolution of cement paste. Based on the relaxation signals, new applications of low-field NMR in predicting the strength and setting time of cement were developed. The results indicate that the increasing nano-SiO2 addition as well as decreasing water-to-cement ratio can accelerate the early hydration process of cement and densify its microstructure, thus shortening the setting time and enhancing the early compressive strength. The effectiveness of low-field NMR in predicting the strength and setting time of cement was confirmed by the results of compression test and Vicat needle test, respectively. Due to the non-destructive and non-invasive characteristics of low-field nuclear magnetic resonance technology, this method shows special advantages in characterizing the influence of nano-silica on the early performance of cement paste.

Quantitative analysis of wine and other fermented beverages with benchtop NMR

We present a fully automated approach for quantitative compositional analysis of fermented beverages using benchtop nuclear magnetic resonance (NMR) spectroscopy. NMR spectroscopy, renowned for its applications in chemical structure elucidation, is gaining attention as a quantitative analytical technique due to its inherent linearity and the ability to obtain comprehensive quantitative information with a single simple experiment. Recently developed benchtop NMR spectrometers offer the quantitative capabilities of NMR to a wide range of potential users in industry, but their applicability has been limited by the reduced effective spectral resolution and the need for more advanced data processing. We address this problem with a model-based algorithm that hinges on the well-understood description of quantum mechanical phenomena in NMR spectroscopy. We demonstrate the effectiveness of our approach on a challenging problem of analysing the composition of wine and related fermented beverages – an important potential niche application of quantitative NMR. We successfully quantify more than 15 major components in the wine matrix and enable the quantification of species whose analysis is generally not possible with established methods. The average discrepancy of the obtained concentrations, when compared to the traditional methods of analysis, usually does not exceed 10% and is lower for the most abundant species (e.g. below 5% for ethanol).

Modeling of Antioxidant Activity, Polyphenols and Macronutrients Content of Bee Pollen Applying Solid-State 13C NMR Spectra.

An application of solid 13C nuclear magnetic resonance (NMR) spectroscopy for the determination of macronutrients, total polyphenols content, antioxidant activity, N C S elements, and pH in commercially available bee pollens is reported herein. Solid-state 13C NMR spectra were recorded for homogenized pollen granules without chemical treatment or dissolution of samples. By combining spectral data with the results of reference analyses, partial least squares models were constructed and validated separately for each of the studied parameters. To characterize and compare the models’ quality, the relative standard errors of prediction (RSEP) were calculated for calibration and validation sets. In the case of the analysis of protein, fat and reducing sugars, these errors were in the 1.8–2.5% range. Modeling the elemental composition of bee pollen on the basis of 13C NMR spectra resulted in RSEPcal/RSEPval values of 0.3/0.6% for the sum of NHCS elements, 0.3/0.4% for C, 1.8/1.9% for N, and 4.2/6.1% for S quantification. Analyses of total phenolics and ABTS antioxidant activity resulted in RSEP values in the 2.7–3.5% and 2.8–3.8% ranges, respectively, whereas they were 1.4–2.1% for pH. The obtained results demonstrate the usefulness of 13C solid-state NMR spectroscopy for direct determination of various important physiochemical parameters of bee pollen.

Understanding the microstructural evolution of hypersaline cemented paste backfill with low-field NMR relaxation

Cemented paste backfill (CPB) comprising mineral tailings, binders and mixing water is an important potential support material in the mining industry. As the mechanical properties of CPB are significantly influenced by its microstructural characteristics the development of measurement tools to better understand its pore structure evolution is important for its increased utilisation. This study reports the application of low-field nuclear magnetic resonance (NMR) relaxation time measurements to characterise the microstructural evolution of CPB materials over 56 days of hydration, contrasting common tap water and hypersaline water (~22 wt% salt) as mixing water. Distinct NMR relaxation time populations were evidenced within each CPB sample, revealing the presence of both capillary (T1,2 ≈ 10 ms) and gel pore water (T1,2 ≈ 300–500 μs), with time-dependent relaxation measurements facilitating characterisation of capillary pore structure evolution over the hydration period assessed. Hypersaline samples demonstrated a time-lag in this measured capillary pore evolution, relative to those hydrated with tap water, while pore structure evolution rates were observed to increase with increased CPB binder content. Further, both T1 and T2 NMR relaxation times were found to correlate with the uniaxial compressive strength of the CPB materials investigated, facilitating the formulation of a predictive correlation function between NMR relaxation characteristics and mechanical properties.

A data-oriented approach to making new molecules as a student experiment: artificial intelligence-enabling FAIR publication of NMR data for organic esters.

The lack of machine-readable data is a major obstacle in the application of nuclear magnetic resonance (NMR) in artificial intelligence (AI). As a way to overcome this, a procedure for capturing primary NMR spectroscopic instrumental data annotated with rich metadata and publication in a Findable, Accessible, Interoperable and Reusable (FAIR) data repository is described as part of an undergraduate student laboratory experiment in a chemistry department. This couples the techniques of chemical synthesis of a never before made organic ester with illustration of modern data management practices and serves to raise student awareness of how FAIR data might improve research quality and replicability. Searches of the registered metadata are shown, which enable actionable finding and accessing of such data. The potential for re-use of the data in AI applications is discussed.

The First Application of 1H NMR Spectroscopy for the Assessment of the Authenticity of Perfumes.

The manufacture of counterfeit goods is one of the world’s largest underground businesses and is rapidly growing. Counterfeits can lead not only to the loss of profit for honest producers but also have a negative impact on consumers who pay excessive prices for poor quality goods that may result in health or safety problems. The perfume industry is constantly vulnerable to counterfeits, particularly in the fast developing market of “smell-alike” designer-inspired perfumes because these prompt the identification of the methods that classify their quality. In this paper, the application of proton nuclear magnetic resonance (1H NMR) spectroscopy is employed for the first time to authenticate perfumery products. The molecular composition of several types of authentic brand fragrances for women was compared with cheap inspired equivalents and fakes. Our approach offers the prospect of a fast and simple method for detecting counterfeit perfumes using 1H NMR spectroscopy.

Real-time nuclear magnetic resonance spectroscopy in the study of biomolecular kinetics and dynamics.

The review describes the application of nuclear magnetic resonance (NMR) spectroscopy to study kinetics of folding, refolding and aggregation of proteins, RNA and DNA. Time-resolved NMR experiments can be conducted in a reversible or an irreversible manner. In particular, irreversible folding experiments pose large requirements for (i)signal-to-noise due to the time limitations and (ii)synchronising of the refolding steps. Thus, this contribution discusses the application of methods for signal-to-noise increases, including dynamic nuclear polarisation, hyperpolarisation and photo-CIDNP for the study of time-resolved NMR studies. Further, methods are reviewed ranging from pressure and temperature jump, light induction to rapid mixing to induce rapidly non-equilibrium conditions required to initiate folding.

Influence of the Distribution of the Properties of Permanent Magnets on the Field Homogeneity of Magnet Assemblies for Mobile NMR

We optimized the magnetic field homogeneity of two canonical designs for mobile microfluidic nuclear magnetic resonance (NMR) applications: two parallel magnets with an air gap and a modified Halbach array. Along with the influence of the sample length, general design guidelines will be presented. For a fair comparison, the sensitive length of the sample has been chosen to be the same as the gap size between the magnets to ensure enough space for the transmitting and receiving unit, as well as basic electric shimming components. Keeping the compactness of the final device in mind, a box with an edge length 5 times the gap size has been defined, in which the complete magnet configuration should fit. With the chosen boundary conditions, the simple parallel cuboid configuration reaches the best homogeneity without active shimming ( 0.5B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> , 41 ppm), while the pseudo-Halbach configuration has the highest field strength ( 0.9B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> , 994 ppm), assuming perfect magnets. However, permanent magnet configurations suffer from imperfections, such as magnetization, fabrication, and positioning errors, which results in worse magnetic field homogeneities than expected from simulations using a fixed optimized parameter set. We present a sensitivity analysis for a magnetic cube and the results of studies of the variations in the magnetization and angle of magnetization of magnets purchased from different suppliers, composed of different materials and coatings, and of different sizes. We performed a detailed Monte Carlo simulation on the effect of the measured distribution of magnetic properties on the mentioned configurations. The cuboid design shows a mean homogeneity of 430 ppm (std. dev. 350 ppm), the Pseudo-Halbach has a mean homogeneity of 1086 ppm (std dev. 8 ppm).

Challenges and Advances in the Application of Dynamic Nuclear Polarization to Liquid-State NMR Spectroscopy.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method to study the molecular structure and dynamics of materials. The inherently low sensitivity of NMR spectroscopy is a consequence of low spin polarization. Hyperpolarization of a spin ensemble is defined as a population difference between spin states that far exceeds what is expected from the Boltzmann distribution for a given temperature. Dynamic nuclear polarization (DNP) can overcome the relatively low sensitivity of NMR spectroscopy by using a paramagnetic matrix to hyperpolarize a nuclear spin ensemble. Application of DNP to NMR can result in sensitivity gains of up to four orders of magnitude compared to NMR without DNP. Although DNP NMR is now more routinely utilized for solid-state (ss) NMR spectroscopy, it has not been exploited to the same degree for liquid-state samples. This Review will consider challenges and advances in the application of DNP NMR to liquid-state samples. The Review is organized into four sections: (i) mechanisms of DNP NMR relevant to hyperpolarization of liquid samples; (ii) applications of liquid-state DNP NMR; (iii) available detection schemes for liquid-state samples; and (iv) instrumental challenges and outlook for liquid-state DNP NMR.