Solution-State 2D NMR Spectroscopy of Mixtures HyperpolarizedUsing Optically Polarized Crystals

The HYPNOESYS method (Hyperpolarized NOE System), which relies on the dissolution of optically polarized crystals, has recently emerged as a promising approach to enhance the sensitivity of NMR spectroscopy in the solution state. However, HYPNOESYS is a single-shot method that is not generally compatible with multidimensional NMR. Here we show that 2D NMR spectra can be obtained from HYPNOESYS-polarized samples, using single-scan acquisition methods. The approach is illustrated with a mixture of terpene molecules and a benchtop NMR spectrometer, paving the way to a sensitive, information-rich and affordable analytical method.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

In Situ Characterization of Mixtures of Linear and Branched Hydrocarbons Confined within Porous Media Using 2D DQF-COSY NMR Spectroscopy

The analysis of 1D anti-diagonal spectra from the projections of 2D double-quantum filtered correlation spectroscopy NMR spectra is presented for the determination of the compositions of liquid mixtures of linear and branched alkanes confined within porous media. These projected spectra do not include the effects of line broadening and therefore retain high-resolution information even in the presence of inhomogeneous magnetic fields as are commonly found in porous media. A partial least-square regression analysis is used to characterize the mixture compositions. Two case studies are considered. First, mixtures of 2-methyl alkanes and n-alkanes are investigated. It is shown that estimation of the mol % of branched species present was achieved with a root-mean-square error of prediction (RMSEP) of 1.4 mol %. Second, the quantification of multicomponent mixtures consisting of linear alkanes and 2-, 3-, and 4-monomethyl alkanes was considered. Discrimination of 2-methyl and linear alkanes from other branched isomers in the mixture was achieved, although discrimination between 3- and 4- monomethyl alkanes was not possible. Compositions of the linear alkane, 2-methyl alkane, and the total composition of 3- and 4-methyl alkanes were estimated with a RMSEP <3 mol %. The approach was then used to estimate the composition of the mixtures in terms of submolecular groups of CH₃CH₂, (CH₃)₂CH, and CH₂CH(CH₃)CH₂ present in the mixtures; a RMSEP <1 mol % was achieved for all groups. The ability to characterize the mixture compositions in terms of molecular subgroups allows the application of the method to characterize mixtures containing multimethyl alkanes. The motivation for this work is to develop a method for determining the mixture composition inside the catalyst pores during Fischer–Tropsch synthesis. However, the method reported is generic and can be applied to any system in which there is a need to characterize mixture compositions of linear and branched alkanes.

A comparison of non-uniform sampling and model-based analysis of NMR spectra for reaction monitoring

Nuclear magnetic resonance (NMR) spectroscopy is widely used for applications in the field of reaction and process monitoring. When complex reaction mixtures are studied, NMR spectra often suffer from low resolution and overlapping peaks, which places high demands on the method used to acquire or to analyse the NMR spectra. This work presents two NMR methods that help overcome these challenges: 2D non-uniform sampling (NUS) and a recently proposed model-based fitting approach for the analysis of 1D NMR spectra. We use the reaction of glycerol with acetic acid as it produces five reaction products that are all chemically similar and, hence, challenging to distinguish. The reaction was measured on a high-field 400 MHz NMR spectrometer with a 2D NUS-heteronuclear single quantum coherence (HSQC) and a conventional 1D ¹ H NMR sequence. We show that comparable results can be obtained using both 2D and 1D methods, if the 2D volume integrals of the 2D NUS-HSQC NMR spectra are calibrated. Further, we monitor the same reaction on a low-field 43 MHz benchtop NMR spectrometer and analyse the acquired 1D ¹ H NMR spectra with the model-based approach and with partial least-squares regression (PLS-R), both trained using a single, calibrated data set. Both methods achieve results that are in good quantitative agreement with the high-field data. However, the model-based method was found to be less sensitive to the training data set used than PLS-R and, hence, was more robust when the reaction conditions differed from that of the training data.

Benefits of time-resolved nonuniform sampling in reaction monitoring: The case of aza-Michael addition of benzylamine and acrylamide

Monitoring of chemical reactions is best carried out using methods that sample the test object at a rate greater than the time scale of the processes taking place. The recently proposed time-resolved nonuniform sampling (TR-NUS) method allows the use of two-dimensional (2D) nuclear magnetic resonance (NMR) spectra for this purpose and provides a time resolution equivalent to that achievable using one-dimensional spectra. Herein, we show that TR-NUS acquired data eliminates 2D spectral line disturbances and enables more accurate signal integration and kinetics conclusions. The considerations are exemplified with a seemingly simple aza-Michael reaction of benzylamine and acrylamide. Surprisingly, the product identification is possible only using 2D spectra, although credible monitoring requires TR-NUS.

Controlling the Self-Assembly of New Metastable Tin Vanadium Selenides Using Composition and Nanoarchitecture of Precursors

In solid-state chemistry, the direct reaction of elements at low temperatures is limited by low solid-state interdiffusion rates. This and the limited number of processing parameters often prevent the synthesis of metastable compounds. Precisely controlling the number of atoms and nanoarchitecture of layered elemental precursors enabled the selective synthesis of two closely related metastable tin vanadium selenides via near-diffusionless reactions at low temperatures. Although the nanoarchitectures of the precursors required to form [(SnSe₂)_0.80]₁(VSe₂)₁ and [(SnSe)_1.15]₁(VSe₂)₁ are very similar, controlling the local composition of the Sn|Se layers in the precursors enables the selective synthesis of either compound. The metastable alloy Sn_xV_1-xSe₂ was preferentially formed over [(SnSe₂)_0.80]₁(VSe₂)₁, which has the identical composition, by modifying the nanoarchitecture of the precursor. Ex situ in-plane X-ray diffraction and X-ray reflectivity collected as a function of annealing temperature provided information on lateral and perpendicular growth of [(SnSe₂)_0.80]₁(VSe₂)₁. The presence of Laue oscillations throughout the self-assembly provided atomic-scale information on the thickness of the [(SnSe₂)_0.80]₁(VSe₂)₁ domains, giving insights into the self-assembly process. A reaction mechanism is proposed and used to rationalize how composition and nanoarchitecture control the reaction pathway through the free energy landscape.

Solvent Effects in the Homogeneous Catalytic Reduction of Propionaldehyde with Aluminium Isopropoxide Catalyst: New Insights from PFG NMR and NMR Relaxation Studies

Solvent effects in homogeneous catalysis are known to affect catalytic activity. Whilst these effects are often described using qualitative features, such as Kamlet‐Taft parameters, experimental tools able to quantify and reveal in more depth such effects have remained unexplored. In this work, PFG NMR diffusion and T₁ relaxation measurements have been carried out to probe solvent effects in the homogeneous catalytic reduction of propionaldehyde to 1‐propanol in the presence of aluminium isopropoxide catalyst. Using data on diffusion coefficients it was possible to estimate trends in aggregation of different solvents. The results show that solvents with a high hydrogen‐bond accepting ability, such as ethers, tend to form larger aggregates, which slow down the molecular dynamics of aldehyde molecules, as also suggested by T₁ measurements, and preventing their access to the catalytic sites, which results in the observed decrease of catalytic activity. Conversely, weakly interacting solvents, such as alkanes, do not lead to the formation of such aggregates, hence allowing easy access of the aldehyde molecules to the catalytic sites, resulting in higher catalytic activity. The work reported here is a clear example on how combining traditional catalyst screening in homogeneous catalysis with NMR diffusion and relaxation time measurements can lead to new physico‐chemical insights into such systems by providing data able to quantify aggregation phenomena and molecular dynamics.

Enhancing Compression Level for More Efficient Compressed Sensing and Other Lessons from NMR Spectroscopy

Modern nuclear magnetic resonance spectroscopy (NMR) is based on two- and higher-dimensional experiments that allow the solving of molecular structures, i.e., determine the relative positions of single atoms very precisely. However, rich chemical information comes at the price of long data acquisition times (up to several days). This problem can be alleviated by compressed sensing (CS)—a method that revolutionized many fields of technology. It is known that CS performs the most efficiently when measured objects feature a high level of compressibility, which in the case of NMR signal means that its frequency domain representation (spectrum) has a low number of significant points. However, many NMR spectroscopists are not aware of the fact that various well-known signal acquisition procedures enhance compressibility and thus should be used prior to CS reconstruction. In this study, we discuss such procedures and show to what extent they are complementary to CS approaches. We believe that the survey will be useful not only for NMR spectroscopists but also to inspire the broader signal processing community.

Fast time-resolved NMR with non-uniform sampling

NMR spectroscopy is a versatile tool for studying time-dependent processes: chemical reactions, phase transitions or macromolecular structure changes. However, time-resolved NMR is usually based on the simplest among available techniques - one-dimensional spectra serving as "snapshots" of the studied process. One of the reasons is that multidimensional experiments are very time-expensive due to costly sampling of evolution time space. In this review we summarize efforts to alleviate the problem of limited applicability of multidimensional NMR in time-resolved studies. We focus on techniques based on sparse or non-uniform sampling (NUS), which lead to experimental time reduction by omitting a significant part of the data during measurement and reconstructing it mathematically, adopting certain assumptions about the spectrum. NUS spectra are faster to acquire than conventional ones and thus better suited to the role of "snapshots", but still suffer from non-stationarity of the signal i.e. amplitude and frequency variations within a dataset. We discuss in detail how these instabilities affect the spectra, and what are the optimal ways of sampling the non-stationary FID signal. Finally, we discuss related areas of NMR where serial experiments are exploited and how they can benefit from the same NUS-based approaches.

Online reaction monitoring by single-scan 2D NMR under flow conditions

Single-scan 2D NMR based on spatial encoding can be used to monitor chemical reactions with a flow unit in realistic reaction conditions.

Enabling High Spectral Resolution of Liquid Mixtures in Porous Media by Antidiagonal Projections of Two-Dimensional 1H NMR COSY Spectra

The noninvasive, in situ chemical identification of liquid mixtures confined in porous materials is experimentally challenging. NMR is chemically resolved and applicable to optically opaque systems but suffers from a significant loss in spectral resolution in the presence of the magnetic field inhomogeneities typical of porous media. In this work, we introduce a method of analysis of conventional two-dimensional (2D) ¹H NMR correlation spectroscopy (COSY) spectra based on the extraction of 1D antidiagonal projections, which are free from line-broadening effects and can therefore be used for chemical species identification. Here, we show the application of the technique to the measurement of linear n-alkanes where the cross-to-diagonal peak ratios are shown to follow a power-law curve as a function of the chain length. This calibration enables quantifying mixtures of linear hydrocarbons confined in any porous material independently of temperature or inter-molecular dynamics. Thus, this is a promising tool for quantitative chemical reaction monitoring studies in heterogeneous systems under operando experimental conditions.

Nonstationary Two-Dimensional Nuclear Magnetic Resonance: A Method for Studying Reaction Mechanisms in Situ

Nuclear magnetic resonance spectroscopy (NMR) is a versatile tool of chemical analysis allowing one to determine structures of molecules with atomic resolution. Particularly informative are two-dimensional (2D) experiments that directly identify atoms coupled by chemical bonds or a through-space interaction. Thus, NMR could potentially be powerful tool to study reactions in situ and explain their mechanisms. Unfortunately, 2D NMR is very time-consuming and thus often cannot serve as a "snapshot" technique for in situ reaction monitoring. Particularly difficult is the case of spectra, in which resonance frequencies vary in the course of reaction. This leads to resolution and sensitivity loss, often hindering the detection of transient products. In this paper we introduce a novel approach to correct such nonstationary 2D NMR signals and raise the detection limits over 10 times. We demonstrate success of its application for studying the mechanism of the reaction of AgSO₄-induced synthesis of diphenylmethane-type compounds. Several reactions occur in the studied mixture of benzene and toluene, all with rather low yield and leading to compounds with similar chemical shifts. Nevertheless, with the use of a proposed 2D NMR approach we were able to describe complex mechanisms of diphenylmethane formation involving AgSO₄-induced toluene deprotonation and formation of benzyl carbocation, followed by nucleophilic attacks.

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.

Ultrafast Maximum-Quantum NMR Spectroscopy for the Analysis of Aromatic Mixtures

Maximum-quantum (MaxQ) NMR experiments have been introduced to overcome issues related to peak overlap and high spectral density in the NMR spectra of aromatic mixtures. In MaxQ NMR, spin systems are separated on the basis of the highest-quantum coherence that they can form. MaxQ experiments are however time consuming and methods have been introduced to accelerate them. In this article, we demonstrate the ultrafast, single-scan acquisition of MaxQ NMR spectra using spatial encoding of the multiple-quantum dimension. So far, the spatial encoding methodology has been applied only for the encoding of up to double-quantum coherences, and here we show that it can be extended to higher coherence orders, to yield a massive reduction of the acquisition time of multi-quantum spectra of aromatic mixtures, and also to monitor chemical reactions.

High-fidelity spectroscopy reconstruction in accelerated NMR

High-fidelity spectra, particularly low intensity peaks, are reconstructed for fast NMR with better rank approximation in the EnhanCed Low Rank (ECLR) method.

An integrated total neutron scattering – NMR approach for the study of heterogeneous catalysis

By combining total neutron scattering with nuclear magnetic resonance (NeuNMR) in a single experimental apparatus, new insights into the kinetics and mechanisms of heterogeneous catalytic reactions occurring in situ, within the catalyst pore space, are possible.

Magnetic Resonance Imaging and Velocity Mapping in Chemical Engineering Applications

This review aims to illustrate the diversity of measurements that can be made using magnetic resonance techniques, which have the potential to provide insights into chemical engineering systems that cannot readily be achieved using any other method. Perhaps the most notable advantage in using magnetic resonance methods is that both chemistry and transport can be followed in three dimensions, in optically opaque systems, and without the need for tracers to be introduced into the system. Here we focus on hydrodynamics and, in particular, applications to rheology, pipe flow, and fixed-bed and gas-solid fluidized bed reactors. With increasing development of industrially relevant sample environments and undersampling data acquisition strategies that can reduce acquisition times to <1 s, magnetic resonance is finding increasing application in chemical engineering research.

Fast 2D NMR Spectroscopy for In vivo Monitoring of Bacterial Metabolism in Complex Mixtures

The biological toolbox is full of techniques developed originally for analytical chemistry. Among them, spectroscopic experiments are very important source of atomic-level structural information. Nuclear magnetic resonance (NMR) spectroscopy, although very advanced in chemical and biophysical applications, has been used in microbiology only in a limited manner. So far, mostly one-dimensional ¹H experiments have been reported in studies of bacterial metabolism monitored in situ. However, low spectral resolution and limited information on molecular topology limits the usability of these methods. These problems are particularly evident in the case of complex mixtures, where spectral peaks originating from many compounds overlap and make the interpretation of changes in a spectrum difficult or even impossible. Often a suite of two-dimensional (2D) NMR experiments is used to improve resolution and extract structural information from internuclear correlations. However, for dynamically changing sample, like bacterial culture, the time-consuming sampling of so-called indirect time dimensions in 2D experiments is inefficient. Here, we propose the technique known from analytical chemistry and structural biology of proteins, i.e., time-resolved non-uniform sampling. The method allows application of 2D (and multi-D) experiments in the case of quickly varying samples. The indirect dimension here is sparsely sampled resulting in significant reduction of experimental time. Compared to conventional approach based on a series of 1D measurements, this method provides extraordinary resolution and is a real-time approach to process monitoring. In this study, we demonstrate the usability of the method on a sample of Escherichia coli culture affected by ampicillin and on a sample of Propionibacterium acnes, an acne causing bacterium, mixed with a dose of face tonic, which is a complicated, multi-component mixture providing complex NMR spectrum. Through our experiments we determine the exact concentration and time at which the anti-bacterial agents affect the bacterial metabolism. We show, that it is worth to extend the NMR toolbox for microbiology by including techniques of 2D z-TOCSY, for total "fingerprinting" of a sample and 2D ¹³C-edited HSQC to monitor changes in concentration of metabolites in selected metabolic pathways.

The inversion of 2D NMR relaxometry data using L1 regularization

NMR relaxometry has been used as a powerful tool to study molecular dynamics. Many algorithms have been developed for the inversion of 2D NMR relaxometry data. Unlike traditional algorithms implementing L2 regularization, high order Tikhonov regularization or iterative regularization, L1 penalty term is involved to constrain the sparsity of resultant spectra in this paper. Then fast iterative shrinkage-thresholding algorithm (FISTA) is proposed to solve the L1 regularization problem. The effectiveness, noise vulnerability and practical utility of the proposed algorithm are analyzed by simulations and experiments. The results demonstrate that the proposed algorithm has a more excellent capability to reveal narrow peaks than traditional inversion algorithms. The L1 regularization implemented by our algorithm can be a useful complementary to the existing algorithms.

Artifacts in time-resolved NUS: A case study of NOE build-up curves from 2D NOESY

Multidimensional NMR spectroscopy requires time-consuming sampling of indirect dimensions and so is usually used to study stable samples. However, dynamically changing compounds or their mixtures commonly occur in problems of natural science. Monitoring them requires the use multidimensional NMR in a time-resolved manner - in other words, a series of quick spectra must be acquired at different points in time. Among the many solutions that have been proposed to achieve this goal, time-resolved non-uniform sampling (TR-NUS) is one of the simplest. In a TR-NUS experiment, the signal is sampled using a shuffled random schedule and then divided into overlapping subsets. These subsets are then processed using one of the NUS reconstruction methods, for example compressed sensing (CS). The resulting stack of spectra forms a temporal "pseudo-dimension" that shows the changes caused by the process occurring in the sample. CS enables the use of small subsets of data, which minimizes the averaging of the effects studied. Yet, even within these limited timeframes, the sample undergoes certain changes. In this paper we discuss the effect of varying signal amplitude in a TR-NUS experiment. Our theoretical calculations show that the variations within the subsets lead to t1-noise, which is dependent on the rate of change of the signal amplitude. We verify these predictions experimentally. As a model case we choose a novel 2D TR-NOESY experiment in which mixing time is varied in parallel with shuffled NUS in the indirect dimension. The experiment, performed on a sample of strychnine, provides a near-continuous NOE build-up curve, whose shape closely reflects the t1-noise level. 2D TR-NOESY reduces the measurement time compared to the conventional approach and makes it possible to verify the theoretical predictions about signal variations during TR-NUS.

Resolution-enhanced 2D NMR of complex mixtures by non-uniform sampling

NMR is a powerful tool for the analysis of complex mixtures and the identification of individual components. Two-dimensional (2D) NMR potentially offers a wealth of information, but resolution is often sacrificed in order to contain experimental times. We explore the use of non-uniform sampling (NUS) to increase substantially the resolution of 2D NMR spectra of complex mixtures of small molecules, with no increase in experimental time. Two common pulse sequences for metabolomics applications are analysed, HSQC and TOCSY. Specific attention is paid to sensitivity in resolution-enhanced NUS spectra, using the signal-to-maximum-noise ratio as a metric. With a careful choice of sampling schedule and reconstruction algorithm, resolution in the (13) C dimension for HSQC is increased by a factor of at least 32, with no loss in sensitivity and no spurious peaks. For TOCSY, multiplets can be resolved in the indirect dimension in a reasonable experimental time. These properties should increase the usefulness of 2D NMR for metabolomics applications by, for example, increasing the chances of metabolite identification.

Surface modification of sewage sludge derived carbonaceous catalyst for m-cresol catalytic wet peroxide oxidation and degradation mechanism

Organic synthesis is used to investigate the degradation of m-cresol and the intermediates are identified by in situ NMR.