Selective and Controlled Grafting from PVDF-Based Materials by Oxygen-Tolerant Green-Light-Mediated ATRP.

Poly(vinylidene fluoride) (PVDF) shows excellent chemical and thermal resistance and displays high dielectric strength and unique piezoelectricity, which are enabling for applications in membranes, electric insulators, sensors, or power generators. However, its low polarity and lack of functional groups limit wider applications. While inert, PVDF has been modified by grafting polymer chains by atom transfer radical polymerization (ATRP), albeit via an unclear mechanism, given the strong C-F bonds. Herein, we applied eosin Y and green-light-mediated ATRP to modify PVDF-based materials. The method gave nearly quantitative (meth)acrylate monomer conversions within 2 h without deoxygenation and without the formation of unattached homopolymers, as confirmed by control experiments and DOSY NMR measurements. The gamma distribution model that accounts for broadly dispersed polymers in DOSY experiments was essential and serves as a powerful tool for the analysis of PVDF. The NMR analysis of poly(methyl acrylate) graft chain-ends on PVDF-CTFE (statistical copolymer with chlorotrifluoroethylene) was carried out successfully for the first time and showed up to 23 grafts per PVDF-CTFE chain. The grafting density was tunable depending on the solvent composition and light intensity during the grafting. The initiation proceeded either from the C-Cl sites of PVDF-CTFE or via unsaturations in the PVDF backbones. The dehydrofluorinated PVDF was 20 times more active than saturated PVDF during the grafting. The method was successfully applied to modify PVDF, PVDF-HFP, and Viton A401C. The obtained PVDF-CTFE-g-PnBMA materials were investigated in more detail. They featured slightly lower crystallinity than PVDF-CTFE (12-18 vs 24.3%) and had greatly improved mechanical performance: Young's moduli of up to 488 MPa, ductility of 316%, and toughness of 46 × 106 J/m3.

CAT on MOUSE: Control and automation of temperature for single-sided NMR instruments such as NMR-MOUSE.

Temperature-dependent experiments are a rapidly growing area of interest for low-field NMR. In this work, we present a new device for wide-range temperature control for single-sided NMR instruments. The presented device, called CAT, is simple to build, inexpensive, and easy to modify to accommodate different samples. We present the capabilities of the device using a freezing temperature study of acetic acid/water mixtures. Additionally, we present the stability of the device over long measurement times. We believe that by introducing such a device with an open-source design, we allow researchers to use it in a wide range of applications and to fully incorporate variable-temperature studies in the world of single-sided instruments.

Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins.

NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.

Deeper Insight into Photopolymerization: The Synergy of Time-Resolved Nonuniform Sampling and Diffusion NMR.

The comprehensive real-time in situ monitoring of chemical processes is a crucial requirement for the in-depth understanding of these processes. This monitoring facilitates an efficient design of chemicals and materials with the precise properties that are desired. This work presents the simultaneous utilization and synergy of two novel time-resolved NMR methods, i.e., time-resolved diffusion NMR and time-resolved nonuniform sampling. The first method allows the average diffusion coefficient of the products to be followed, while the second method enables the particular products to be monitored. Additionally, the average mass of the system is calculated with excellent resolution using both techniques. Employing both methods at the same time and comparing their results leads to the unequivocal validation of the assignment in the second method. Importantly, such validation is possible only via the simultaneous combination of both approaches. While the presented methodology was utilized for photopolymerization, it can also be employed for any other polymerization process, complexation, or, in general, chemical reactions in which the evolution of mass in time is of importance.

Sensitive, Efficient and Portable Analysis of Molecular Exchange Processes by Hyperpolarized Ultrafast NMR.

Molecular exchange processes are ubiquitous in nature. Here, we introduce a method to analyze exchange processes by using low-cost, portable, single-sided NMR instruments. The inherent magnetic field inhomogeneity of the single-sided instruments is exploited to achieve diffusion contrast of exchange sites and spatial encoding of 2D data. This so-called ultrafast diffusion exchange spectroscopy method shortens the experiment time by two to four orders of magnitude. Furthermore, because full 2D data are measured in a single scan (in a fraction of a second), the sensitivity of the experiment can be improved by several orders of magnitude using so-called nuclear spin hyperpolarization methods (in this case, dissolution dynamic nuclear polarization). As the first demonstration of the feasibility of the method in various applications, we show that the method enables quantification of intra- and extracellular exchange of water in a yeast cell suspension.

Ultrafast methods for relaxation and diffusion.

Relaxation and diffusion NMR measurements offer an approach to studying rotational and translational motion of molecules non-invasively, and they also provide chemical resolution complementary to NMR spectra. Multidimensional experiments enable the correlation of relaxation and diffusion parameters as well as the observation of molecular exchange phenomena through relaxation or diffusion contrast. This review describes how to accelerate multidimensional relaxation and diffusion measurements significantly through spatial encoding. This so-called ultrafast Laplace NMR approach shortens the experiment time to a fraction and makes even single-scan experiments possible. Single-scan experiments, in turn, significantly facilitate the use of nuclear spin hyperpolarization methods to boost sensitivity. The ultrafast Laplace NMR method is also applicable with low-field, mobile NMR instruments, and it can be exploited in many disciplines. For example, it has been used in studies of the dynamics of fluids in porous materials, identification of intra- and extracellular metabolites in cancer cells, and elucidation of aggregation phenomena in atmospheric surfactant solutions.

Photoreactivity of an Exemplary Anthracene Mixture Revealed by NMR Studies, including a Kinetic Approach.

Anthracenes are an important class of acenes. They are being utilized more and more often in chemistry and materials sciences, due to their unique rigid molecular structure and photoreactivity. In particular, photodimerization can be harnessed for the fabrication of novel photoresponsive materials. Photodimerization between the same anthracenes have been investigated and utilized in various fields, while reactions between varying anthracenes have barely been investigated. Here, Nuclear Magnetic Resonance (NMR) spectroscopy is employed for the investigation of the photodimerization of two exemplary anthracenes: anthracene (A) and 9-bromoanthracene (B), in the solutions with only A or B, and in the mixture of A and B. Estimated k values, derived from the presented kinetic model, showed that the dimerization of A was 10 times faster in comparison with B when compounds were investigated in separate samples, and 2 times faster when compounds were prepared in the mixture. Notably, the photoreaction in the mixture, apart from AA and BB, additionally yielded a large amount of the AB mixdimer. Another important advantage of investigating a mixture with different anthracenes is the ability to estimate the relative reactivity for all the reactions under the same experimental conditions. This results in a better understanding of the photodimerization processes. Thus, the rational photofabrication of mix-anthracene-based materials can be facilitated, which is of crucial importance in the field of polymer and material sciences.

Clustered sparsity and Poisson-gap sampling.

Non-uniform sampling (NUS) is a popular way of reducing the amount of time taken by multidimensional NMR experiments. Among the various non-uniform sampling schemes that exist, the Poisson-gap (PG) schedules are particularly popular, especially when combined with compressed-sensing (CS) reconstruction of missing data points. However, the use of PG is based mainly on practical experience and has not, as yet, been explained in terms of CS theory. Moreover, an apparent contradiction exists between the reported effectiveness of PG and CS theory, which states that a "flat" pseudo-random generator is the best way to generate sampling schedules in order to reconstruct sparse spectra. In this paper we explain how, and in what situations, PG reveals its superior features in NMR spectroscopy. We support our theoretical considerations with simulations and analyses of experimental data from the Biological Magnetic Resonance Bank (BMRB). Our analyses reveal a previously unnoticed feature of many NMR spectra that explains the success of "blue-noise" schedules, such as PG. We call this feature "clustered sparsity". This refers to the fact that the peaks in NMR spectra are not just sparse but often form clusters in the indirect dimension, and PG is particularly suited to deal with such situations. Additionally, we discuss why denser sampling in the initial and final parts of the clustered signal may be useful.

Variable-temperature NMR spectroscopy for metabolite identification in biological materials.

Nuclear magnetic resonance is a "workhorse technique" used in metabolomics, complementary to mass spectrometry. Unfortunately, only the most basic NMR methods are sensitive enough to allow fast medical screening. The most common of them, a simple 1H NMR, suffers from low dispersion of resonance frequencies, which often hampers the identification of metabolites. In this article we show that 1H NMR spectra contain previously overlooked parameters potentially helpful in metabolite identification, namely the rates of temperature-induced changes of chemical shifts. We prove that they are reproducible between various metabolite mixtures and can be determined quickly when Radon transform is used to process the data.

Temperature as an Extra Dimension in Multidimensional Protein NMR Spectroscopy.

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time-consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature-dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature-swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non-linearities effectively. Non-linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided.

Accelerating Restricted Diffusion NMR Studies with Time-Resolved and Ultrafast Methods.

Restricted diffusion of fluids in porous materials can be studied by pulsed field gradient nuclear magnetic resonance (NMR) non-invasively and without tracers. If the experiment is repeated many times with varying diffusion delays, detailed information about pore sizes and tortuosity can be recorded. However, the measurements are very time-consuming because numerous repetitions are needed for gradient ramping and varying diffusion delays. In this paper, we demonstrate two different strategies for acceleration of the restricted diffusion NMR measurements: time-resolved diffusion NMR and ultrafast Laplace NMR. The former is based on time-resolved non-uniform sampling, while the latter relies on spatial encoding of two-dimensional data. Both techniques allow similar 1-2 order of magnitude acceleration of acquisition, but they have different strengths and weaknesses, which we discuss in detail. The feasibility of the methods was proven by investigating restricted diffusion of water inside tracheid cells of thermally modified pine wood.

Correction to "Comprehensive NMR Analysis of Pore Structures in Superabsorbing Cellulose Nanofiber Aerogels".

[This corrects the article DOI: 10.1021/acs.jpcc.9b08339.].

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.

TReNDS-Software for reaction monitoring with time-resolved non-uniform sampling.

NMR spectroscopy, used routinely for structure elucidation, has also become a widely applied tool for process and reaction monitoring. However, the most informative of NMR methods-correlation experiments-are often useless in this kind of applications. The traditional sampling of a multidimensional FID is usually time-consuming, and thus, the reaction-monitoring toolbox was practically limited to 1D experiments (with rare exceptions, e.g., single-scan or fast-sampling experiments). Recently, the technique of time-resolved non-uniform sampling (TR-NUS) has been proposed, which allows to use standard multidimensional pulse sequences preserving the temporal resolution close to that achievable in 1D experiments. However, the method existed only as a prototype and did not allow on-the-fly processing during the reaction. In this paper, we introduce TReNDS: free, user-friendly software kit for acquisition and processing of TR-NUS data. The program works on Bruker, Agilent, and Magritek spectrometers, allowing to carry out up to four experiments with interleaved TR-NUS. The performance of the program is demonstrated on the example of enzymatic hydrolysis of sucrose.

Comprehensive NMR Analysis of Pore Structures in Superabsorbing Cellulose Nanofiber Aerogels.

Highly porous cellulose nanofiber (CNF) aerogels are promising, environmentally friendly, reusable, and low-cost materials for several advanced environmental, biomedical, and electronic applications. The aerogels have a complex and hierarchical 3D porous network structure with pore sizes ranging from nanometers to hundreds of micrometers. The morphology of the network has a critical role on the performance of aerogels, but it is difficult to characterize thoroughly with traditional techniques. Here, we introduce a combination of nuclear magnetic resonance (NMR) spectroscopy techniques for comprehensive characterization of pore sizes and connectivity in the CNF aerogels. Cyclohexane absorbed in the aerogels was used as a probe fluid. NMR cryoporometry enabled us to characterize the size distribution of nanometer scale pores in between the cellulose nanofibers in the solid matrix of the aerogels. Restricted diffusion of cyclohexane revealed the size distribution of the dominant micrometer scale pores as well as the tortuosity of the pore network. T 2 relaxation filtered microscopic magnetic resonance imaging (MRI) method allowed us to determine the size distribution of the largest, submillimeter scale pores. The NMR techniques are nondestructive, and they provide information about the whole sample volume (not only surfaces). Furthermore, they show how absorbed liquids experience the complex 3D pore structure. Thorough characterization of porous structures is important for understanding the properties of the aerogels and optimizing them for various applications. The introduced comprehensive NMR analysis set is widely usable for a broad range of different kinds of aerogels used in different applications, such as catalysis, batteries, supercapacitors, hydrogen storage, etc.

SCoT: Swept coherence transfer for quantitative heteronuclear 2D NMR.

Nuclear magnetic resonance (NMR) spectroscopy is frequently applied in quantitative chemical analysis (qNMR). It is easy to measure one-dimensional (1D) NMR spectra in a quantitative regime (with appropriately long relaxation delays and acquisition times); however, their applicability is limited in the case of complex samples with severe peak overlap. Two-dimensional (2D) NMR solves the overlap problem, but at the cost of biasing peak intensities and hence quantitativeness. This is partly due to the uneven coherence transfer between excited/detected 1H nuclei and the heteronuclei coupled to them (typically 13C). In the traditional approach, the transfer occurs via the evolution of a spin system state under the J-coupling Hamiltonian during a delay of a fixed length. The delay length is set on the basis of the predicted average coupling constant in the sample. This leads to disturbances for pairs of nuclei with coupling constants deviating from this average. Here, we present a novel approach based on non-standard processing of the data acquired in experiments, where the coherence transfer delay is co-incremented with non-uniformly sampled evolution time. This method allows us to obtain the optimal transfer for all resonances, which improves quantitativeness. We demonstrate the concept for the coherence transfer and multiplicity-edit delays in a heteronuclear single-quantum correlation experiment (HSQC).

Insight into human insulin aggregation revisited using NMR derived translational diffusion parameters.

The NMR derived translational diffusion coefficients were performed on unlabeled and uniformly labeled 13C,15N human insulin in water, both in neat, with zinc ions only, and in pharmaceutical formulation, containing only m-cresol as phenolic ligand, glycerol and zinc ions. The results show the dominant role of the pH parameter and the concentration on aggregation. The diffusion coefficient Dav was used for monitoring the overall average state of oligomeric ensemble in solution. The analysis of the experimental data of diffusion measurements, using the direct exponential curve resolution algorithm (DECRA) allows suggesting the two main components of the oligomeric ensemble. The 3D HSQC-iDOSY, (diffusion ordered HSQC) experiments performed on 13C, 15N-fully labeled insulin at the two pH values, 4 and 7.5, allow for the first time a more detailed experimental observation of individual components in the ensemble. The discussion involves earlier static and dynamic laser light scattering experiments and recent NMR derived translational diffusion results. The results bring new informations concerning the preparation of pharmaceutical formulation and in particular a role of Zn2+ ions. They also will enable better understanding and unifying the results of studies on insulin misfolding effects performed in solution by diverse physicochemical methods at different pH and concentration.

Joint non-uniform sampling of all incremented time delays for quicker acquisition in protein relaxation studies.

NMR relaxometry plays crucial role in studies of protein dynamics. The measurement of longitudinal and transverse relaxation rates of [Formula: see text]N is the main source of information on backbone motions. However, even the most basic approach exploiting a series of [Formula: see text]N HSQC spectra can require several hours of measurement time. Standard non-uniform sampling (NUS), i.e. random under-sampling of indirect time domain, typically cannot reduce this by more than 2-4[Formula: see text] due to relatively low "compressibility" of these spectra. In this paper we propose an extension of NUS to relaxation delays. The two-dimensional space of [Formula: see text]/[Formula: see text] is sampled in a way similar to NUS of [Formula: see text]/[Formula: see text] domain in 3D spectra. The signal is also processed in a way similar to that known from 3D NUS spectra i.e. using one of the most popular compressed sensing algorithms, iterative soft thresholding. The 2D Fourier transform matrix is replaced with mixed inverse Laplace-Fourier transform matrix. The peak positions in resulting 3D spectrum are characterized by two frequency coordinates and relaxation rate and thus no additional fitting of exponential curves is required. The method is tested on three globular proteins, providing satisfactory results in a time corresponding to acquisition of two conventional [Formula: see text]N HSQC spectra.

Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing.

Nuclear magnetic resonance (NMR) is currently one of the main analytical techniques applied in numerous branches of chemistry. Furthermore, NMR has been proven to be useful to follow in situ reactions occurring on a time scale of hours and days. For complicated mixtures, NMR experiments providing diffusion coefficients are particularly advantageous. However, the inverse Laplace transform (ILT) that is used to extract the distribution of diffusion coefficients from an NMR signal is known to be unstable and vulnerable to noise. Numerous regularisation techniques to circumvent this problem have been proposed. In our recent study, we proposed a method based on sparsity-enforcing l1-norm minimisation. This approach, which is referred to as ITAMeD, has been successful but limited to samples with a 'discrete' distribution of diffusion coefficients. In this paper, we propose a generalisation of ITAMeD using a tailored lp-norm (1 ≤ p ≤ 2) to process, in particular, signals arising from 'polydisperse' samples. The performance of our method was tested on simulations and experimental datasets of polyethylene oxides with varying polydispersity indices. Finally, we applied our new method to monitor diffusion coefficient and polydispersity changes of heparin undergoing enzymatic degradation in real time.

Accelerating diffusion-ordered NMR spectroscopy by joint sparse sampling of diffusion and time dimensions.

Diffusion-ordered multidimensional NMR spectroscopy is a valuable technique for the analysis of complex chemical mixtures. However, this method is very time-consuming because of the costly sampling of a multidimensional signal. Various sparse sampling techniques have been proposed to accelerate such measurements, but they have always been limited to frequency dimensions of NMR spectra. It is now revealed how sparse sampling can be extended to diffusion dimensions.