Time-domain Nuclear Magnetic Resonance Spectroscopy Research Articles

Designing Sustainable Hydrophilic Interfaces via Feature Selection from Molecular Descriptors and Time-Domain Nuclear Magnetic Resonance Relaxation Curves.

Surface modification using hydrophilic polymer coatings is a sustainable approach for preventing membrane clogging due to foulant adhesion to water treatment membranes and reducing membrane-replacement frequency. Typically, both molecular descriptors and time-domain nuclear magnetic resonance (TD-NMR) data, which reveal physicochemical properties and polymer-chain dynamics, respectively, are required to predict the properties and understand the mechanisms of hydrophilic polymer coatings. However, studies on the selection of essential components from high-dimensional data and their application to the prediction of surface properties are scarce. Therefore, we developed a method for selecting features from combined high-dimensional molecular descriptors and TD-NMR data. The molecular descriptors of the monomers present in polyethylene terephthalate films were calculated using RDKit, an open-source chemoinformatics toolkit, and TD-NMR spectroscopy was performed over a wide time range using five-pulse sequences to investigate the mobility of the polymer chains. The model that analyzed the data using the random forest algorithm, after reducing the features using gradient boosting machine-based recursive feature elimination, achieved the highest prediction accuracy. The proposed method enables the extraction of important elements from both descriptors of surface properties and can contribute to the development of new sustainable materials and material-specific informatics methodologies encompassing multiple information modalities.

Non-Invasive Single-Grain Screening of Proteins and Other Features by Combination of Near-Infrared Spectroscopy and Nuclear Magnetic Resonance

The non-invasive analysis of seeds is of great interest to experimental biologists and breeders. To reach a high varietal identity and purity of seed material, it is often necessary to access features of individual seeds via the screening of mutant populations. While near-infrared spectroscopy (NIRS) and time-domain nuclear-magnetic-resonance spectroscopy (TD-NMR) are well-known in seed research and industry for bulk seed measurements, their application for individual seeds is challenging. Here we demonstrate how to overcome this limitation using a practical approach to cereal grains using oat (Avena sp.) as a model. For this, we generated a representative collection of oat seeds from the ex situ German federal gene bank, which includes wide variation in grain size, shape, and coloration. Next, we established a short experimental pipeline to exemplify how to improve the procedure for individual seed measurements. In its current state, the method is ready to use for the high-accuracy estimation of nitrogen (protein) content (R2 = 0.877), water content (R2 = 0.715), and seed weight (R2 = 0.897) of individual oat grains. This work introduces the combination of NIRS and TD-NMR as an efficient, precise, and, most importantly, non-destructive analytic platform for a high throughput analysis of individual intact seeds.

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.

Monitoring of soluble pectin content in orange juice by means of MIR and TD-NMR spectroscopy combined with machine learning.

This study represents a rapid and non-destructive approach based on mid-infrared (MIR) spectroscopy, time domain nuclear magnetic resonance (TD-NMR), and machine learning classification models (ML) for monitoring soluble pectin content (SPC) changes in orange juice. Current reference methods of SPC in orange juice are laborious, requiring several extractions with successive adjustments hindering rapid process intervention. 109 fresh orange juices samples, representing different harvests, were analysed using MIR, TD-NMR and reference method. Unsupervised algorithms were applied for natural clustering of MIR and TD-NMR data in two groups. Analyses of variance of the two MIR and TD-NMR datasets show that only the MIR groups were different at 95% confidence for SPC average values. This approach allows build classification models based on MIR data achieving 85% and 89% of accuracy. Results demonstrate that MIR/ML can be a suitable strategy for the quick assessment of SPC trends in orange juices.

Solid-state and time domain NMR to elucidate degradation behavior of thermally aged poly (urea-urethane)

We have demonstrated that solid-state and time-domain Nuclear Magnetic Resonance spectroscopy (NMR) techniques are effective in monitoring the degradation site of poly (urea-urethane). We prepared two types of commercial poly (urea-urethane), Urethane-A and Urethane-B, and aged them at 100 °C for up to 10000 h. We performed tensile strength tests and solid-state NMR experiments, in which 13C and 15N NMR spectra and T2 were collected. The tensile strength of Urethane-A decreased, increased and decreased again, whereas that of Urethane-B decreased at a lower rate with aging. Solid-state NMR experiments clearly showed that the degradation of Urethane-A was caused by molecular chain scission and cross-linking in its urea bonds, and that of Urethane-B occurred owing to molecular chain scission in its urethane bonds. T2 had three components, short T2 (T2S), intermediate T2 (T2I) and long T2 (T2L), whose fractions were xS, xI and xL, respectively. We have demonstrated that molecular chain scission in urea bonds decreases xS and increases xL, and that in urethane bonds increases T2I and T2L without changing all the T2 fractions.

A nondestructive and noninvasive method to determine water content in lyophilized proteins using low-field time-domain NMR.

Determining the moisture content in lyophilized solids is a fundamental step towards predicting the quality and stability of lyophilized products, but conventional methods are time-consuming, invasive, and destructive. High levels of residual moisture in a lyophilized product can lead to cake collapse, product degradation, and reduced shelf life. The aim of this study was to develop a fast, noninvasive, nondestructive, and inexpensive method for determining the moisture content in a lyophilized monoclonal antibody (mAb) formulation using benchtop low-field time-domain nuclear magnetic resonance spectroscopy.

Investigation on curing characterization of epoxy molding compounds with different latent catalysts by thermal, electrical and mechanical analysis

This research was conducted to investigate comprehensively curing characteristics of epoxy molding compound (EMC) with various latent catalysts by using their thermal, electrical and mechanical properties. The conversion prediction on isothermal condition for three types of organophosphine based catalysts was studied by model free method with differential scanning calorimetry (DSC). The T2 relaxation time was measured by time-domain nuclear magnetic resonance spectroscopy (TD-NMR) in order to compare the cross-linking density for each catalyst according to curing time. The results of DSC and TD-NMR showed that catalysts with lower latency reached curing in a shorter time. Furthermore, we observed the electrical-mechanical characteristics of EMC using additional thermal analysis. The ion viscosity was measured by dielectric analysis (DEA) according to the curing time, and the results suggested that the ion viscosity and the volume resistivity were lower for the catalyst with a slower curing rate. Dynamic mechanical analysis (DMA) was performed to compare activation energy of glass transition and glass modulus of final product. It was shown that the use of a catalyst with a low latency increases the modulus against external physical forces. In conclusion, our results demonstrated that the various analytical approaches are highly significant to understand the curing characteristics of EMC, which helps select appropriate catalysts in order to enhance the reliability of EMC.

Variability in determination of the single kernel moisture content of grain by means of TD-NMR spectroscopy

Detailed information on the moisture distribution of grains is important to predict its storability, because there can be a significant variance in the moisture content among individual grain kernels. Hence, it is important to determine the single kernel moisture content. For it, the time domain nuclear magnetic resonance (TD-NMR) spectroscopy was applied and adopted for the non-destructive measurement at different types of grain with the focus on wheat. The TD-NMR is widely used in food industry to determine the moisture content precisely. The influence of the single kernel position in the measuring cell was examined more closely. As could be demonstrated, the particle moisture varied significantly depending on the angular position in the TD-NMR spectroscope. When the kernel was turned by 90°, the moisture deviated by up to 0.9% wet basis, and this deviation increased as the grain water content increased. In addition, the experiments showed that the dry mass of the kernel has an impact on the received moisture content. Hence, the kernel should always have the same position in the NMR-spectroscope. Also the calibration should be carried out in this position and a wide range of kernel weight should be selected.

Time-Domain Nuclear Magnetic Resonance (TD-NMR) and Chemometrics for Determination of Fat Content in Commercial Products of Milk Powder.

This study shows the use of time-domain (TD)-NMR transverse relaxation (T2) data and chemometrics in the nondestructive determination of fat content for powdered food samples such as commercial dried milk products. Most proposed NMR spectroscopy methods for measuring fat content correlate free induction decay or echo intensities with the sample's mass. The need for the sample's mass limits the analytical frequency of NMR determination, because weighing the samples is an additional step in this procedure. Therefore, the method proposed here is based on a multivariate model of T2 decay, measured with Carr-Purcell-Meiboom-Gill pulse sequence and reference values of fat content. The TD-NMR spectroscopy method shows high correlation (r = 0.95) with the lipid content, determined by the standard extraction method of Bligh and Dyer. For comparison, fat content determination was also performed using a multivariate model with near-IR (NIR) spectroscopy, which is also a nondestructive method. The advantages of the proposed TD-NMR method are that it (1) minimizes toxic residue generation, (2) performs measurements with high analytical frequency (a few seconds per analysis), and (3) does not require sample preparation (such as pelleting, needed for NIR spectroscopy analyses) or weighing the samples.

Prediction of beef color using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate analyses.

Time-domain nuclear magnetic resonance and chemometrics were used to predict color parameters, such as lightness (L*), redness (a*), and yellowness (b*) of beef (Longissimus dorsi muscle) samples. Analyzing the relaxation decays with multivariate models performed with partial least-squares regression, color quality parameters were predicted. The partial least-squares models showed low errors independent of the sample size, indicating the potentiality of the method. Minced procedure and weighing were not necessary to improve the predictive performance of the models. The reduction of transverse relaxation time (T2 ) measured by Carr-Purcell-Meiboom-Gill pulse sequence in darker beef in comparison with lighter ones can be explained by the lower relaxivity Fe2+ present in deoxymyoglobin and oxymyoglobin (red beef) to the higher relaxivity of Fe3+ present in metmyoglobin (brown beef). These results point that time-domain nuclear magnetic resonance spectroscopy can become a useful tool for quality assessment of beef cattle on bulk of the sample and through-packages, because this technique is also widely applied to measure sensorial parameters, such as flavor, juiciness and tenderness, and physicochemical parameters, cooking loss, fat and moisture content, and instrumental tenderness using Warner Bratzler shear force. Copyright © 2016 John Wiley & Sons, Ltd.

Through-package fat determination in commercial samples of mayonnaise and salad dressing using time-domain nuclear magnetic resonance spectroscopy and chemometrics

Although fat is an essential component in the human diet, the consumption of food with high fat content has been the major cause of obesity. Here we are demonstrating that time-domain nuclear magnetic resonance (TD-NMR) decays, obtained by Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence, can be used to predict the total fat content in sealed packages of commercial food emulsions, such as mayonnaise and salad dressing that may contain more than 50% of fat. The PLS model of the CPMG decays shows high linear correlation (>0.9) and low root mean square errors (RMSE) for cross-validation and validation data. Therefore, this procedure can be used to predict the total fat content in food emulsion after packaging, to detect problems in the manufacturing process or fraud. In addition, the TD-NMR instrument and the proposed methods can also be adapted for using at the end of the food chain (store) to measure the fat content in consumer packaged goods.

A fundamental investigation of the microarchitecture and mechanical properties of tempo-oxidized nanofibrillated cellulose (NFC)-based aerogels

Freeze-dried nanofibrillated cellulose based-aerogels were produced from cellulosic pulps extracted from Eucalyptus urograndis. Nanofibers were isolated under high pressure and modified with TEMPO-mediated oxidation and/or hydroxyapatite (HAp) to observe potential changes in mechanical properties. Two degrees of oxidation (DO), 0.1 and 0.2, were achieved as measured by conductimetric titration. Oxidized and non-oxidized samples were modified with HAp at a ratio of HAp:cellulose of 0.2:1. Morphology (FE-SEM), pore size, surface area, and mechanical properties were obtained to characterize the produced aerogels. The results clearly demonstrate a homogeneous morphology for aerogels fabricated with oxidized cellulose nanofibers. The nature of water present in the material was measured using time domain-nuclear magnetic resonance spectroscopy (TD-NMR) and demonstrated that it played a key role in the development of the porous and uniform micro-architecture. TEMPO-mediated oxidation and the addition of HAp resulted in aerogels with high mechanical strength as demonstrated from an increase from approximately 75–200 kPa in compressive strength when reduced to 50 % of their original height. However, the contribution of oxidation to the mechanical properties was more pronounced than the addition of HAp. In general, the density of the aerogels varied from 0.008 to 0.011 g/cm3 in which slightly lightweight aerogels were produced by increasing the degree of oxidation, whereas the incorporation of HAp as a modifying agent for potential bio-based tissue scaffolding matrices did not significantly contribute to higher densities.

Simultaneous measurements of T1 and T2 during fast polymerization reaction using continuous wave‐free precession NMR method

Continuous wave-free precession (CWFP) pulse sequence employing time domain nuclear magnetic resonance spectroscopy (TD-NMR) was used to measure longitudinal (T(1)) and transverse relaxation times (T(2)), during the cure of a commercial epoxy resin (Araldite(TM)) with a 10-min solidification time. The intensity of the NMR signal after the first pulse and in the CWFP regime were used to monitor the concentration of the monomers, and the relaxation times were used to monitor the chain mobility. The main advantage of CWFP over the standard methods to measure relaxation times, inversion recovery (inv-rec) for T(1) and Carr-Purcell-Meiboom-Gill (CPMG) for T(2), is that the measurement of both relaxation times can be performed in a fast and single NMR experiment and, therefore, using a single reaction batch. CWFP is also as fast as the CPMG measurement but at least fivefold faster than the method to obtain T(1) using null point approximation in the inv-rec method. Therefore, the CWFP sequence can be used as a fast and general method to measure relaxation times in polymerization reactions, even with fast solidification time. As a TD-NMR technique, CWFP can be employed in any low-cost bench top TD-NMR equipment commonly used in an academic or industrial laboratory.

Direct determination of the lipid content in starch–lipid composites by time-domain NMR

Starch–lipid composites, prepared by excess steam jet cooking aqueous mixtures of starch and lipid, are used in a broad range of applications for which their performance can depend upon accurately knowing the amount of the lipid contributed by the composites. A rapid and non-destructive method based on time-domain nuclear magnetic resonance spectroscopy (TD-NMR) was evaluated to quantitate soybean oil (SBO) or butterfat (BF) content in a series of dried starch–lipid composites. Transverse hydrogen relaxation ( T 2) properties of the composites were examined using Carr, Purcell, Mieboom, Gill (CPMG) pulse experiments and multi-exponential decay fitting routines were utilized to evaluate the various components. Spin–echo TD-NMR experiments were used to quantitate the amount of lipid in the composites and agreed well with lipid extraction experiments ( R 2 = 0.998). Moisture levels in the composites were also simultaneously determined and compared reasonably well to moisture levels determined gravimetrically ( R 2 = 0.881). TD-NMR was shown to be a rapid method to determine lipid and moisture content in these starch–lipid composites without the need for labor intensive extraction and gravimetric methods currently employed.

Molecular mobility in model dough systems studied by time-domain nuclear magnetic resonance spectroscopy

The microscopic distribution and dynamic state of water and molecular mobility in various model systems are investigated using time-domain NMR spectroscopy. Starch and gluten showed different continuous distribution populations in T 21 (μsec range, obtained from One pulse experiments) and T 22 (msec range, obtained from CPMG experiments) proving that starch and gluten have different water dynamics and molecular mobility. A starch/gluten mixture (76:12, w/w) and wheat flour dough exhibited similar patterns indicating that water and molecular mobilities in dough tended to be more representative of interactions with starch than gluten, even though both water–starch and water–gluten interactions are occurring in wheat flour dough. Increasing the water content did not influence the continuous distribution pattern of T 21 but affected the relative amount of each fraction in T 21 (i.e. an increase of the more mobile fraction and a decrease of the less mobile fraction with increasing moisture). Added water has an important role in the more mobile fraction but not in the less mobile fraction, which is in μs range. This indicates that model food systems contain multiple microstructural domains with various water and molecular mobilities that show correspondingly different water dynamics. Therefore, the dispersion of various relaxation time constants helped identify the distribution of independent microstructural domains. The manipulation of the composition of the model food system influences the water dynamics and molecular mobility and provides a basis for the application of the microstructural domain concept to real food systems.

Time domain-nuclear magnetic resonance study of chars from southern hardwoods☆

Chars from the thermal degradation of silver maple (Acer saccharinum), red maple (Acer rubrum), sugar maple (Acer saccharum), and white oak (Quercus spp.), performed at temperatures from 250 to 350 °C, were examined using time domain-nuclear magnetic resonance spectroscopy. Prior to analysis, the chars were equilibrated under conditions insuring the presence of bound water only and both bound water and free water. Transverse relaxation times were found to be related to the moisture content of the chars, which varied with temperature. At elevated temperatures the number of signals assigned to free water decreased, indicative of an increase in pore size within the chars.

Spectral Fitting of NMR Spectra Using an Alternating Optimization Method with a Priori Knowledge

As alternatives to the fast Fourier transform, advanced parametric methods based on the damped sinusoidal data model have been devised to better quantify the nuclear magnetic resonance (NMR) spectroscopy time-domain data. Previously, linear prediction (LP) fitting methods using Householder triangularization and singular value decomposition (SVD) techniques have been applied to the NMR spectroscopy data analysis. In this paper, we propose an alternating optimization method to quantify the time-domain NMR spectroscopy data. The proposed algorithm uses the a priori knowledge of the possible frequency intervals of the damped sinusoids to obtain more accurate parameter estimates when the NMR spectroscopy data are obtained under low signal-to-noise ratio conditions and the peaks are close together. None of the LP and SVD type of methods can use such approximate a priori knowledge. We have shown with measured NMR spectroscopy data that the proposed algorithm can be used to obtain accurate parameter estimates of frequencies, amplitudes, and damping ratios of the damped sinusoids and therefore the ultimate fit of the spectrum by using the a priori knowledge about the possible frequency intervals of the damped sinusoids.