Basic principles of static proton low-resolution spin diffusion NMR in nanophase-separated materials with mobility contrast

How entanglements determine the morphology of semicrystalline polymers

Crystallization of polymers from entangled melts generally leads to the formation of semicrystalline materials with a nanoscopic morphology consisting of stacks of alternating crystalline and amorphous layers. The factors controlling the thickness of the crystalline layers are well studied; however, there is no quantitative understanding of the thickness of the amorphous layers. We elucidate the effect of entanglements on the semicrystalline morphology by the use of a series of model blends of high-molecular-weight polymers with unentangled oligomers leading to a reduced entanglement density in the melt as characterized by rheological measurements. Small-angle X-ray scattering experiments after isothermal crystallization reveal a reduced thickness of the amorphous layers, while the crystal thickness remains largely unaffected. We introduce a simple, yet quantitative model without adjustable parameters, according to which the measured thickness of the amorphous layers adjusts itself in such a way that the entanglement concentration reaches a specific maximum value. Furthermore, our model suggests an explanation for the large supercooling that is typically required for crystallization of polymers if entanglements cannot be dissolved during crystallization.

Polymer composition optimization approach based on feature extraction of bound and free water using time-domain nuclear magnetic resonance

As global environmental sustainability becomes increasingly emphasized, the development of eco-friendly materials, including solutions to the issue of marine plastics, is thriving. However, the material parameter space is vast, making efficient search a challenge. Time-domain nuclear magnetic resonance offers material property information through the complex T₂ relaxation curves resulting from multiple mobilities. In this research, we used the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence to evaluate the binding state of water (water affinity) in polymers synthesized with various monomer compositions, which were immersed in seawater. We also assessed the T₂ relaxation property of the polymers using the magic sandwich echo, double quantum filter, and magic-and-polarization echo filter techniques. We separated the T₂ relaxation curves of CPMG into free and bound water for polymers by employing semisupervized nonnegative matrix factorization. By employing the features of separated bound water and polymer properties, a polymer composition optimization method offered crucial factors to monomers through random forests, predicted the components of the polymer using generative topography mapping regression, and determined expected values using Bayesian optimization for polymer composition candidates with the desired high water affinity and high rigidity.

Usefulness of Applying Partial Least Squares Regression to T2 Relaxation Curves for Predicting the Solid form Content in Binary Physical Mixtures

This study applied partial least squares (PLS) regression to nuclear magnetic resonance (NMR) relaxation curves to quantify the free base of an active pharmaceutical ingredient powder. We measured the T₂ relaxation of intact and moisture-absorbed physical mixtures of tetracaine free base (TC) and its hydrochloride salt (TC·HCl). The obtained T₂ relaxation curves were analyzed by two methods, one using a previously reported T₂ relaxation time (T₂), and the other using PLS regression. The accuracy of estimating TC was inadequate when using previous T₂ values because the moisture-absorbed physical mixtures showed biphasic T₂ relaxation curves. By contrast, the entire measured whole of the T₂ relaxation curves was used as input variables and analyzed by PLS regression to quantify the content of TC in the moisture-absorbed TC/TC·HCl. Based on scatterplots of theoretical versus predicted TC, the obtained PLS model exhibited acceptable coefficients of determination and relatively low root mean squared error values for calibration and validation data. The statistical values confirmed that an accurate and reliable PLS model was created to quantify TC in even moisture-absorbed TC/TC·HCl. The bench-top low-field NMR instrument used to apply PLS regression to the T₂ relaxation curve may be a promising tool in process analytical technology.

Intensified Nonequilibrium Effect of Polymer Nanocomposites with Decreasing Nanoparticle Size

What are the most important and decisive parameters that determine the structure and the property of polymer nanocomposites (PNCs)? Previous studies answered that controlling the nanoparticle interface is critical, which can be achieved with a choice of a compatible nanoparticle, a proper surface modification, and a change in the polymer chain length. In addition to these parameters, the processing condition of PNCs has recently emerged as an influential parameter for controlling PNC properties, suggesting the existence of the nonequilibrium effect of PNCs. In this regard, we chose the solvent as a main change in the processing condition and investigated the initial solvent-driven nonequilibrium effect of PNCs with varied nanoparticle (NP) sizes. We found that the type of the initial solvent is indeed crucial in determining the ultimate properties of the PNCs, and this becomes more influential as the size of NPs decreases. The decreasing size of NPs causes a conformational change in the adsorbed polymers from tightly packed layers to loosely dangling chains. This results in much greater differences in NP microstructures and rheological properties of PNCs, indicating a stronger nonequilibrium effect with smaller NPs.

Non-Conventional Time Domain (TD)-NMR Approaches for Food Quality: Case of Gelatin-Based Candies as a Model Food

The TD-NMR technique mostly involves the use of T1 (spin-lattice) and T2 (spin-spin) relaxation times to explain the changes occurring in food systems. However, these relaxation times are affected by many factors and might not always be the best indicators to work with in food-related TD-NMR studies. In this study, the non-conventional TD-NMR approaches of Solid Echo (SE)/Magic Sandwich Echo (MSE) and Spin Diffusion in food systems were used for the first time. Soft confectionary gelatin gels were formulated and conventional (T1) and non-conventional (SE, MSE and Spin Diffusion) TD-NMR experiments were performed. Corn syrups with different glucose/fructose compositions were used to prepare the soft candies. Hardness, °Brix (°Bx), and water activity (aw) measurements were also conducted complementary to NMR experiments. Relaxation times changed (p < 0.05) with respect to syrup type with no obvious trend. SE/MSE experiments were performed to calculate the crystallinity of the samples. Samples prepared with fructose had the lowest crystallinity values (p < 0.05). Spin Diffusion experiments were performed by using Goldman−Shen pulse sequence and the interface thickness (d) was calculated. Interface thickness values showed a wide range of variation (p < 0.05). Results showed that non-conventional NMR approaches had high potential to be utilized in food systems for quality control purposes.

Materials informatics approach using domain modelling for exploring structure-property relationships of polymers

In the development of polymer materials, it is an important issue to explore the complex relationships between domain structure and physical properties. In the domain structure analysis of polymer materials, ¹H-static solid-state NMR (ssNMR) spectra can provide information on mobile, rigid, and intermediate domains. But estimation of domain structure from its analysis is difficult due to the wide overlap of spectra from multiple domains. Therefore, we have developed a materials informatics approach that combines the domain modeling (http://dmar.riken.jp/matrigica/) and the integrated analysis of meta-information (the elements, functional groups, additives, and physical properties) in polymer materials. Firstly, the ¹H-static ssNMR data of 120 polymer materials were subjected to a short-time Fourier transform to obtain frequency, intensity, and T₂ relaxation time for domains with different mobility. The average T₂ relaxation time of each domain is 0.96 ms for Mobile, 0.55 ms for Intermediate (Mobile), 0.32 ms for Intermediate (Rigid), and 0.11 ms for Rigid. Secondly, the estimated domain proportions were integrated with meta-information such as elements, functional group and thermophysical properties and was analyzed using a self-organization map and market basket analysis. This proposed method can contribute to explore structure–property relationships of polymer materials with multiple domains.

Design, Synthesis and Characterization of Vitrimers with Low Topology Freezing Transition Temperature

Vitrimers are crosslinked polymeric materials that behave like fluids when heated, regulated by the kinetics of internal covalent bond-exchange that occurs rapidly at or above the topology freezing transition temperature (T_v) of the vitrimer, making these materials readily reprocessable and recyclable. We report two novel multiphase vitrimeric materials prepared by the cross-linking of two polymers, namely poly(triethylene glycol sebacate) and poly(2-hydroxyethyl acrylate), using zinc acetate or tin(II) 2-ethylhexanoate as catalysts, which exhibit significantly low T_v temperatures of 39 °C and 29 °C, respectively. The transesterification reactions allow rapid and pronounced stress relaxation at high temperatures, following the Arrhenius law. The lower T_v of these vitrimers could be attributable to the flexible long chains of these polymers and the significant excess of OH moieties present along the main chain of the polymer. The design of such multiphase vitrimers is not only useful for the practical application of vitrimers to reduce plastic waste but could also facilitate further development of functional polymer materials that can be reprocessed at low temperatures.

Polymer Networks for Enrichment of Calcium Ions

In this study, solvogels containing (2-((2-(ethoxycarbonyl)prop-2-en-1-yl)oxy)-ethyl) phosphonic acid (ECPA) and N,N′-diethyl-1,3-bis-(acrylamido)propane (BNEAA) as the crosslinker are synthesized by UV induced crosslinking photopolymerization in various solvents. The polymerization of the ECPA monomer is monitored by the conversion of double bonds with in situ attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. The morphology of the networks is characterized by in situ photorheology, solid state NMR spectroscopy, and scanning electron microscopy (SEM) of the dried gels. It is demonstrated that the storage modulus is not only determined by the crosslinker content in the gel, but also by the solvent used for preparation. The networks turn out to be porous structures with G′ being governed by a rigid, phase-separated polymer phase rather than by entropic elasticity. The external and internal pK_a values of the poly(ECPA-co-BNEAA) gels were determined by titration with a specially designed method and compared to the calculated values. The polymer-immobilized phosphonic acid groups in the hydrogels induce buffering behavior into the system without using a dissolved buffer. The calcium accumulation in the gels is studied by means of a double diffusion cell filled with calcium ion-containing solutions. The successful accumulation of hydroxyapatite within the gels is shown by a combination of SEM, energy-dispersive X-ray spectroscopy (EDX) and wide-angle X-ray scattering (WAXS).

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

Unravelling Main- and Side-Chain Motions in Polymers with NMR Spectroscopy and Relaxometry: The Case of Polyvinyl Butyral

Polyvinyl butyral (PVB) is an amorphous polymer employed in many technological applications. In order to highlight the relationships between macroscopic properties and dynamics at a microscopic level, motions of the main-chain and of the propyl side-chains were investigated between Tg - 288 °C and Tg + 55 °C, with Tg indicating the glass transition temperature. To this aim, a combination of solid state Nuclear Magnetic Resonance (NMR) methods was applied to two purposely synthesized PVB isotopomers: one fully protonated and the other perdeuterated on the side-chains. 1H time domain NMR and 1H field cycling NMR relaxometry experiments, performed across and above Tg, revealed that the dynamics of the main-chain corresponds to the α-relaxation associated to the glass transition, which was previously characterized by dielectric spectroscopy. A faster secondary relaxation was observed for the first time and ascribed to side-chains. The geometry and rate of motions of the different groups in the side-chains were characterized below Tg by 2H NMR spectroscopy.

Interplay of Structural Factors in Formation of Microphase-Separated or Microphase-Mixed Structures of Polyurethanes Revealed by Solid-State NMR and Dielectric Spectroscopy

A set of aromatic-oxyaliphatic polyurethanes (PUs) with different mass fractions of components also containing fluorinated fragments was synthesized and studied using various solid-state NMR techniques and dielectric spectroscopy. In contrast to the common model suggested by Cooper and Tobolsky in 1966, the rigid domains of microphase separated PUs are formed, not only by units containing urethane bonds, but also by oxyethylene fragments that form a common rigid phase. The urethane bonds and oxyethylene fragments are incorporated into both rigid and soft phases. Good agreement with the Cooper and Tobolsky model is observed only when solubility parameters are significantly different for the hard and soft segments, such as hydrocarbon aromatics and perfluoroaliphatic blocks.

Time-domain NMR analysis for the determination of water content in pharmaceutical ingredients and wet granules

The application of time-domain NMR (TD-NMR) analysis to quantify water content in pharmaceutical ingredients is demonstrated. The initial phase of the study employed a range of disintegrants with defined amounts of added water (0-30% of the total weight) as samples; the disintegrants included croscarmellose sodium, corn starch, low-substituted hydroxypropyl cellulose, and crospovidone. After acquisition of the T₂ relaxation curves of the samples by TD-NMR measurements, these curves were analyzed by partial least squares (PLS) regression. According to the analysis, accurate and reliable PLS models were created that enabled accurate assessment of water content in the samples. A powder blend consisting of acetaminophen (paracetamol) and tablet excipients was also examined. Both a physical mixture of the powder blend and a wet granule prepared with a high-speed granulator were tested as samples in this study. Precise determination of water content in the powder blend was achieved by using the TD-NMR method. The accuracy of water content determination was equivalent to or better than that of the conventional loss on drying method. TD-NMR analysis samples were measured nondestructively and rapidly with low cost; thus, it could be a powerful quantitative method for determining water content in pharmaceuticals.

Sulfobetaine Hydrogels with a Complex Multilength-Scale Hierarchical Structure

Hydrogels with a hierarchical structure were prepared from a new highly water-soluble crosslinker N,N,N',N'-tetramethyl-N,N'-bis(2-ethylmethacrylate)-propyl-1,3-diammonium dibromide and from the sulfobetaine monomer 2-(N-3-sulfopropyl-N,N-dimethyl ammonium)ethyl methacrylate. The free radical polymerization of the two compounds is rapid and yields near-transparent hydrogels with sizes up to 5 cm in diameter. Rheology shows a clear correlation between the monomer-to-crosslinker ratio and the storage and loss moduli of the hydrogels. Cryo-scanning electron microscopy, low-field nuclear magnetic resonance (NMR) spectroscopy, and small-angle X-ray scattering show that the gels have a hierarchical structure with features spanning the nanometer to the sub-millimeter scale. The NMR study is challenged by the marked inhomogeneity of the gels and the complex chemical structure of the sulfobetaine monomer. NMR spectroscopy shows how these complications can be addressed via a novel fitting approach that considers the mobility gradient along the side chain of methacrylate-based monomers.

Dynamic Heterogeneity of Filler-Associated Interphases in Polymer Nanocomposites

Dynamically inhomogeneous polymer systems exhibit interphases with mobility gradients. These are believed to play key roles in the material's performance. A prominent example is particle-filled rubber, a special case of a crosslinked polymer nanocomposite, where favorable rubber-filler interactions may give rise to a nanoscale immobilized layer around the filler, including regions of intermediate mobility. Such intermediate domains may either form a separate shell-like layer or be a manifestation of dynamic heterogeneities, in which case the intermediately mobile material would be dispersed in the form of nanometer-sized subdomains. In this contribution, bidirectional proton NMR spin diffusion (SD) experiments applied to silica-filled acrylate rubber are combined with numerical simulations to provide microscopic insights into this question. While model calculations for different scenarios fit the given data similarly well for longer SD mixing time, the short-time data do support the presence of dynamic heterogeneities.

Decomposition Factor Analysis Based on Virtual Experiments throughout Bayesian Optimization for Compost-Degradable Polymers

Bio-based polymers have been considered as an alternative to oil-based materials for their “carbon-neutral” environmentally degrative features. However, degradation is a complex system in which environmental factors and preparation conditions are involved, and the relationship between degradation and these factors/conditions has not yet been clarified. Moreover, an efficient system that addresses multiple degradation factors has not been developed for practical use. Thus, we constructed a decomposition degree predictive model to explore degradation factors based on analytical data and experimental conditions. The predictive model was constructed by machine learning using a dataset. The objective variable was the molecular weight, and the explanatory variables were the moisture content in a compost environment, degradation period, degree of crystallinity pre-experiment, and features of solid-state nuclear magnetic resonance spectra. The good accuracy of this predictive model was confirmed by statistical variables. The moisture content in the compost environment was a critical factor for considering initial degradation; specific scores revealed the contribution of degradation factors. Furthermore, the optimum decomposition degree, various analytical values, and experimental conditions were predictable when this predictive model was combined with Bayesian optimization. Information obtained from virtual experiments is expected to promote the material design and development of bio-based plastics.

Spatial inhomogeneity, interfaces and complex vitrification kinetics in a network forming nanocomposite

A detailed calorimetric study on an epoxy-based nanocomposite system was performed employing bisphenol A diglycidyl ether (DGEBA) cured with diethylenetriamine (DETA) as the polymer matrix and a taurine-modified MgAL layered double hydroxide (T-LDH) as the nanofiller. The -NH2 group of taurine can react with DGEBA improving the interaction of the polymer with the filler. The combined X-ray scattering and electron microscopy data showed that the nanocomposite has a partially exfoliated morphology. Calorimetric studies were performed using conventional DSC, temperature modulated DSC (TMDSC) and fast scanning calorimetry (FSC) in the temperature modulated approach (TMFSC) to investigate the vitrification and molecular mobility dependent on the filler concentration. First, TMDSC and NMR were used to estimate the amount of the rigid amorphous fraction which consists of immobilized polymer segments at the nanoparticle surface. It was found to be 40 wt% for the highest filler concentration, indicating that the interface dominates the overall macroscopic properties and behavior of the material to a great extent. Second, the relaxation rates of the α-relaxation obtained by TMDSC and TMFSC were compared with the thermal and dielectric relaxation rates measured by static FSC. The investigation revealed that the system shows two distinct α-relaxation processes. Furthermore, two separate vitrification mechanisms were also found for a bulk network-former without geometrical confinement as also confirmed by NMR. This was discussed in terms of the intrinsic spatial heterogeneity on a molecular scale, which becomes more pronounced with increasing nanofiller content.

Fast-forward approach of time-domain NMR relaxometry for solid-state chemistry of chitosan

Chitosans with different average degrees of acetylation and weight molecular weight were analyzed by time-domain NMR relaxometry using the recently proposed pulse sequence named Rhim and Kessemeier - Radiofrequency Optimized Solid-Echo (RK-ROSE) to acquire ¹H NMR signal of solid-state materials. The NMR signal decay was composed of faster (tenths of μs) and longer components, where the mobile-part fraction exhibited an effective relaxation transverse time assigned to methyl hydrogens from N-acetyl-d-glucosamine (GlcNAc) units. The higher intrinsic mobility of methyl groups was confirmed via DIPSHIFT experiments by probing the ¹H-¹³C dipolar interaction. RK-ROSE data were modeled by using Partial Least Square (PLS) multivariate regression, which showed a high coefficient of determination (R² > 0.93) between RK-ROSE signal profile and average degrees of acetylation and crystallinity index, thus indicating that time-domain NMR consists in a promising tool for structural and morphological characterization of chitosan.

Signal Deconvolution and Generative Topographic Mapping Regression for Solid-State NMR of Multi-Component Materials

Solid-state nuclear magnetic resonance (ssNMR) spectroscopy provides information on native structures and the dynamics for predicting and designing the physical properties of multi-component solid materials. However, such an analysis is difficult because of the broad and overlapping spectra of these materials. Therefore, signal deconvolution and prediction are great challenges for their ssNMR analysis. We examined signal deconvolution methods using a short-time Fourier transform (STFT) and a non-negative tensor/matrix factorization (NTF, NMF), and methods for predicting NMR signals and physical properties using generative topographic mapping regression (GTMR). We demonstrated the applications for macromolecular samples involved in cellulose degradation, plastics, and microalgae such as Euglena gracilis. During cellulose degradation, ¹³C cross-polarization (CP)-magic angle spinning spectra were separated into signals of cellulose, proteins, and lipids by STFT and NTF. GTMR accurately predicted cellulose degradation for catabolic products such as acetate and CO₂. Using these methods, the ¹H anisotropic spectrum of poly-ε-caprolactone was separated into the signals of crystalline and amorphous solids. Forward prediction and inverse prediction of GTMR were used to compute STFT-processed NMR signals from the physical properties of polylactic acid. These signal deconvolution and prediction methods for ssNMR spectra of macromolecules can resolve the problem of overlapping spectra and support macromolecular characterization and material design.

Power-optimized, time-reversal pulse sequence for a robust recovery of signals from rigid segments using time domain NMR

Time domain NMR (TD-NMR) has been widely used on the analysis of liquids or liquid components in heterogeneous materials such as food, biological tissues, synthetic and bio polymers, oil-bearing rocks, biomasses and cement-based materials. The use of TD-NMR for studying solid and soft mater has been growing in number and variety of applications, mostly for organic systems where the detection of ¹H signals is highly advantageous. However, the strong ¹H-¹H dipolar interactions in solids make the ¹H FID to decay in the same order of the dead time of most commercially available NMR probe heads. Thus, solid echoes are often used for recovering signals from solid components. In this article we reinvestigate the time-reversal solid-echo pulse sequence proposed by Rhim and Kessemeier, seeking for optimal pulse power and timing conditions that maximize its efficiency on recovering ¹H signals from rigid segments. We show that under these optimized conditions, which we denote as Rhim and Kessemeier - Radiofrequency Optimized Solid-Echo (RK-ROSE), the experiment can be more efficient than its most popular counterparts Solid-Echo (SE) and mixed-Magic Sandwich Echoes (mixed-MSE). Our results also suggest that, despite the finite pulse power, with current probe technology the RK-ROSE experiment is potentially able to provide an accurate estimation of rigid components, without relying on an external calibration using multiple standard samples, as usually done in SFC analysis of the FID signal. At last, we demonstrate that RK-ROSE can be adapted as a simple filter to supress signals from mobile segments in heterogeneous materials.

Initial Solvent-Driven Nonequilibrium Effect on Structure, Properties, and Dynamics of Polymer Nanocomposites

Unusual structures and dynamic properties found in polymer nanocomposites (PNCs) are often attributed to immobilized (adsorbed) polymers at nanoparticle-polymer interfaces, which are responsible for reducing the intrinsic incompatibility between nanoparticles and polymers in PNCs. Although tremendous effort has been made to characterize the presence of immobilized polymers, a systematic understanding of the structure and dynamics under different processing conditions is still lacking. Here, we report that the initial dispersing solvent, which is not present after producing PNCs, drives these nonequilibrium effects on polymer chain dynamics at interfaces. Employing extensive small-angle scattering, proton NMR spectroscopy, and rheometry experiments, we found that the thickness of the immobilized layer can be dependent on the initial solvent, changing the structure and the properties of the PNC significantly. In addition, we show that the outcome of the initial solvent effect becomes more effective at particle volume fractions where the immobile layers begin to interact.

Low-field and benchtop NMR

NMR started at low field. Important discoveries like the first observation of NMR in condensed matter, the spin echo, NMR for chemical analysis, Fourier NMR spectroscopy, 2D NMR spectroscopy and magnetic resonance imaging happened at field strengths considered low today. With time the footprint of the NMR instruments at these field strengths shrunk from the laboratory floor to the tabletop. The first commercial tabletop NMR instruments were compact relaxometers for food analysis followed by mobile relaxometers for materials testing and oil-well exploration culminating in tabletop spectrometers for chemical analysis, capable of performing nearly the whole methodical portfolio of today's high-field instruments. The increasing sensitivity afforded by the lower noise of modern electronics and the unfolding richness of hyperpolarization scenarios along with detection schemes alternative to nuclear induction enable NMR at ultra-low field strengths down to zero applied field, where spin-spin couplings in local fields dominate the residual Zeeman interaction. Miniaturization and cost-reduction of NMR instruments outline current development goals along with the development of smart-phone-like apps to conduct standard NMR analyses.

Time Domain NMR in Polymer Science: From the Laboratory to the Industry

Highly controlled polymers and nanostructures are increasingly translated from the lab to the industry. Together with the industrialization of complex systems from renewable sources, a paradigm change in the processing of plastics and rubbers is underway, requiring a new generation of analytical tools. Here, we present the recent developments in time domain NMR (TD-NMR), starting with an introduction of the methods. Several examples illustrate the new take on traditional issues like the measurement of crosslink density in vulcanized rubber or the monitoring of crystallization kinetics, as well as the unique information that can be extracted from multiphase, nanophase and composite materials. Generally, TD-NMR is capable of determining structural parameters that are in agreement with other techniques and with the final macroscopic properties of industrial interest, as well as reveal details on the local homogeneity that are difficult to obtain otherwise. Considering its moderate technical and space requirements of performing, TD-NMR is a good candidate for assisting product and process development in several applications throughout the rubber, plastics, composites and adhesives industry.

Progress in low-field benchtop NMR spectroscopy in chemical and biochemical analysis

The employment of spectroscopically-resolved NMR techniques as analytical probes have previously been both prohibitively expensive and logistically challenging in view of the large sizes of high-field facilities. However, with recent advances in the miniaturisation of magnetic resonance technology, low-field, cryogen-free "benchtop" NMR instruments are seeing wider use. Indeed, these miniaturised spectrometers are utilised in areas ranging from food and agricultural analyses, through to human biofluid assays and disease monitoring. Therefore, it is both intrinsically timely and important to highlight current applications of this analytical strategy, and also provide an outlook for the future, where this approach may be applied to a wider range of analytical problems, both qualitatively and quantitatively.

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

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

Identifying the Role of Primary and Secondary Interactions on the Mechanical Properties and Healing of Densely Branched Polyimides

We present a systematic study of the role of the aromatic dianhydride structure on the self-healing behavior of dimer diamine-based polyimides. By means of solid-state NMR and rheology, we studied the molecular and microscale dynamics of four polyimides comprising the same aliphatic branched diamine yet with variable dianhydride rigidities and correlated these to their macroscopic healing kinetics measured by tensile testing. Following the two-step kinetics of the healing process, we were able to differentiate and quantify the extent of mechanical strength recovery in each of the healing stages separately. Moreover, the detailed rheology and solid-state NMR allowed us to shed light on the role of the aromatic interactions and branches on the mechanical properties and mechanical integrity during macroscopic healing. The study reveals the relevance and interplay of primary and secondary interactions in the development of non-cross-linked strong and healing polymers able to maintain mechanical integrity during healing.

Reduced-mobility layers with high internal mobility in poly(ethylene oxide)-silica nanocomposites

A series of poly(ethylene oxide) nanocomposites with spherical silica was studied by proton NMR spectroscopy, identifying and characterizing reduced-mobility components arising from either room-temperature lateral adsorption or possibly end-group mediated high-temperature bonding to the silica surface. The study complements earlier neutron-scattering results for some of the samples. The estimated thickness of a layer characterized by significant internal mobility resembling backbone rotation ranges from 2 nm for longer (20 k) chains adsorbed on 42 nm diameter particles to 0.5 nm and below for shorter (2 k) chains on 13 nm particles. In the latter case, even lower adsorbed amounts are found when hydroxy endgroups are replaced by methyl endgroups. Both heating and water addition do not lead to significant changes of the observables, in contrast to other systems such as acrylate polymers adsorbed to silica, where temperature- and solvent-induced softening associated with a glass transition temperature gradient was evidenced. We highlight the actual agreement and complementarity of NMR and neutron scattering results, with the earlier ambiguities mainly arising from different sensitivities to the component fractions and the details of their mobility.

Dynamics of poly(vinyl butyral) studied using dielectric spectroscopy and 1H NMR relaxometry

Dielectric Spectroscopy (DS) and ¹H Fast Field-Cycling (FFC) NMR relaxometry were applied for understanding the dynamic behavior of the amorphous ter-polymer poly(vinyl butyral) (PVB) across the glass transition temperature (T_g = 70 °C by Differential Scanning Calorimetry). Above T_g, main chain segmental motions (α relaxation) were detected and characterized using both DS and FFC NMR relaxometry. The correlation times extracted by the analysis of DS and FFC NMR relaxometry data agreed within a factor of three and showed a Vogel-Fulcher-Tammann temperature dependence, with an associated T_g of 69 °C and a fragility of 155 for PVB glass. Below T_g, a secondary process (β relaxation) was revealed by DS, and was ascribed to reorientations of the vinyl alcohol dipoles due to local twisting motions with an associated activation barrier of 11 kcal mol^-1. The β process was also found to contribute to ¹H NMR relaxation above T_g.

Dipolar filtered magic-sandwich-echoes as a tool for probing molecular motions using time domain NMR

We present a simple ¹H NMR approach for characterizing intermediate to fast regime molecular motions using ¹H time-domain NMR at low magnetic field. The method is based on a Goldmann Shen dipolar filter (DF) followed by a Mixed Magic Sandwich Echo (MSE). The dipolar filter suppresses the signals arising from molecular segments presenting sub kHz mobility, so only signals from mobile segments are detected. Thus, the temperature dependence of the signal intensities directly evidences the onset of molecular motions with rates higher than kHz. The DF-MSE signal intensity is described by an analytical function based on the Anderson Weiss theory, from where parameters related to the molecular motion (e.g. correlation times and activation energy) can be estimated when performing experiments as function of the temperature. Furthermore, we propose the use of the Tikhonov regularization for estimating the width of the distribution of correlation times.

1 H-19 F REDOR-filtered NMR spin diffusion measurements of domain size in heterogeneous polymers

Solid state NMR spectroscopy is inherently sensitive to chemical structure and composition and thus makes an ideal method to probe the heterogeneity of multicomponent polymers. Specifically, NMR spin diffusion experiments can be used to extract reliable information about spatial domain sizes on multiple length scales, provided that magnetization selection of one domain can be achieved. In this paper, we demonstrate the preferential filtering of protons in fluorinated domains during NMR spin diffusion experiments using ¹ H-¹⁹ F heteronuclear dipolar dephasing based on rotational echo double resonance (REDOR) MAS NMR techniques. Three pulse sequence variations are demonstrated based on the different nuclei detected: direct ¹ H detection, plus both ¹ H➔¹³ C cross polarization and ¹ H➔¹⁹ F cross polarization detection schemes. This ¹ H-¹⁹ F REDOR-filtered spin diffusion method was used to measure fluorinated domain sizes for a complex polymer blend. The efficacy of the REDOR-based spin filter does not rely on spin relaxation behavior or chemical shift differences and thus is applicable for performing NMR spin diffusion experiments in samples where traditional magnetization filters may prove unsuccessful. This REDOR-filtered NMR spin diffusion method can also be extended to other samples where a heteronuclear spin pair exists that is unique to the domain of interest.

Molecular Dynamics in the Crystalline Regions of Poly(ethylene oxide) Containing a Well-Defined Point Defect in the Middle of the Polymer Chain

The chain mobility in crystals of a homopolymer of poly(ethylene oxide) (PEO) with 22 monomer units (PEO₂₂) is compared with that of a PEO having the identical number of monomer units but additionally a 1,4-disubstituted 1,2,3-triazole (TR) point defect in the middle of the chain (PEO₁₁-TR-PEO₁₁). In crystals of PEO₂₂, the characteristic α_c-relaxation (helix jumps) is detected and the activation energy of this process is calculated from the pure crystalline ¹H FIDs to 67 kJ/mol. PEO₁₁-TR-PEO₁₁ exhibits a more complex behavior, i.e. a transition into the high temperature phase HTPh is noticed during heating in the temperature range between -5 and 10 °C which is attributed to the incorporation of the TR ring into the crystalline lamellae. The crystal mobility of the low temperature phase LTPh of PEO₁₁-TR-PEO₁₁ is in good agreement with PEO₂₂ since helical jump motions could also be detected by analysis of the ¹H FIDs and the corresponding values of their second moments M₂. In contrast, the high temperature phase of PEO₁₁-TR-PEO₁₁ shows a completely different behavior of the crystal mobility. The crystalline PEO chains are rigid in this HTPh on the time scale of both, the ¹H time-domain technique and in ¹³C MAS CODEX NMR spectroscopy, i.e. the α_c-mobility of PEO in the HTPh of PEO₁₁-TR-PEO₁₁ is completely suppressed and the PEO₁₁ chains are converted into a crystal-fixed polymer due to the incorporation of the TR rings into the crystal structure. However, the TR defect of PEO₁₁-TR-PEO₁₁ shows in the HTPh characteristic π-flip motions with an Arrhenius type activation energy of 223 kJ/mol measured by dielectric relaxation spectroscopy. This motion cannot be observed by corresponding ¹³C MAS CODEX NMR measurements due to an interfering spin-dynamic effect.

Orientation-dependent proton double-quantum NMR build-up function for soft materials with anisotropic mobility

In recent years, the analysis of proton double-quantum NMR build-up curves has become an important tool to quantify anisotropic mobility in different kinds of soft materials such as polymer networks or liquid crystals. In the former case, such data provides a measure of orientation-dependent residual (time-averaged) dipolar couplings arising from anisotropic segmental motions, informing about the length and the state of local stretching of the network chains. Previous studies of macroscopically ordered, i.e. stretched, networks were subject to the limitation that a detailed build-up curve analysis on the basis of a universal "Abragam-like" (A-l) build-up function valid for a proton multi-spin system was only possible for an isotropic orientation-averaged response. This situation is here remedied by introducing a generic orientation-dependent build-up function for an anisotropically mobile protonated molecular segment. We discuss an application to the modeling of data for a stretched network measured at different orientations with respect to the magnetic field, and present a validation by fitting data of different liquid-crystal molecules oriented in the magnetic field.

Elimination of digital and analog artefacts from time-domain signals

A method is described for the elimination of artefacts that arise in time-domain signals because of the presence of digital and analogous filters. Such artefacts are mostly located at the beginning of the free-induction decay (FID). The procedure introduced here is particularly important if at least one signal component decays rather quickly, i.e. if there is only a small number of data containing this component (as for solid-state ¹H or ²H FIDs). The method is able to restore the original signal by deconvolution of the spectrometer output from the transfer function of the spectrometer console. The transfer function is connected to the filter characteristics. Experimental estimation of this function is demonstrated. The estimation applies differentiation of the output signal in the case of a step-like input. This kind of input could be realized either by very slowly decaying FID or by digitizer overflow. The results are discussed with respect to the best approximation of original FID.