Complex Morphology of the Intermediate Phase in Block Copolymers and Semicrystalline Polymers As Revealed by 1H NMR Spin Diffusion Experiments

A Numerical simulation method for analyzing 1H spin diffusion NMR for Multicomponent and multiphase polymer systems

A numerical simulation method, namely, SDNMR-WEBFIT, is reported for simulating proton spin diffusion NMR based on the Levenberg-Marquardt algorithm and a pseudo-2D diffusion model. This method is used for the precise quantification of dynamics heterogeneity of the interphase within multiphase polymer systems. The numerical simulation method provides measurements of spin-lattice relaxation time (T1), proton density (ρH), lamellar thickness (d), and spin diffusion coefficient (D) for each component. The pseudo-2D diffusion model is employed to simulate the proton spin diffusion build-up/decay curves, simultaneously calculating the lateral fraction of island-like structures (x-ratio). Such approach was successfully applied to various polymer systems, such as semi-crystalline polymer (Poly(ε-caprolactone), PCL), block copolymers (Styrene-butadiene-styrene triblock copolymer, SBS), and plasticized semi-polymers (Polvinyl alcohol, PVA).

Evidence for complexation-induced micro-extension of poly(vinyl alcohol) chains in interphase and amorphous domains from solid-state NMR

The three-phase structure of poly(vinyl alcohol) (PVA)-iodine complexes was elucidated by solid-state NMR (SSNMR), of which the micro-extension of the PVA segment in the interphase and amorphous domains was directly confirmed. The three-phase structure of the PVA-iodine complex was decomposed by the inverse ¹³C T₁-filter, where ¹³C NMR resonance lines of a C(H) triplet were observed in all three phases. The chain axis of ∼26% extended chains in the interphase deviates 35°-50° relative to the stretching direction, while there is only a 1° deviation for the extended chains in the crystalline domain. The increasing iodine concentration results in the increment of hydrogen-bonded C(H) fractions in both the amorphous and interphase domains, while the distribution of different C(H) fractions remains almost constant in the crystalline domain. Such an increment results from the locally extended PVA chains induced by polyiodine species (I₃^-/I₅^-), since the hydrogen bond(s) (HBs) required a specific direction. Direct evidence for this comes from the similar ¹³C CP/MAS spectra of C(H) in the three phases between unoriented iodine-doped PVA and highly oriented pure PVA. This supports the aggregation model for the formation mechanism of PVA-iodine complexes, where the PVA chain takes an extended zig-zag conformation.

Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring

Low-cost and user-friendly benchtop low-field nuclear magnetic resonance (NMR) spectrometers are typically used to monitor food processes in the food industry. Because of excessive spectral overlap, it is difficult to characterize food mixtures using low-field NMR spectroscopy. In addition, for standard compounds, low-field benchtop NMR data are typically unavailable compared to high-field NMR data, which have been accumulated and are reusable in public databases. This work focused on NMR parameter visualization of the chemical structure and mobility of mixtures and the use of high-field NMR data to analyze benchtop NMR data to characterize food process samples. We developed a tool to easily process benchtop NMR data and obtain chemical shifts and T2 relaxation times of peaks, as well as transform high-field NMR data into low-field NMR data. Line broadening and time–frequency analysis methods were adopted for data processing. This tool can visualize NMR parameters to characterize changes in the components and mobilities of food process samples using benchtop NMR data. In addition, assignment errors were smaller when the spectra of standard compounds were identified by transferring the high-field NMR data to low-field NMR data rather than directly using experimentally obtained low-field NMR spectra.

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.

An in situ stretching instrument combined with low field nuclear magnetic resonance (NMR): Rheo-Spin NMR

An in situ stretching instrument combined with low field nuclear magnetic resonance (LF-NMR) was designed and developed, namely, Rheo-Spin NMR. The time resolved stress-strain curve together with the corresponding NMR signal can be simultaneously obtained. The Rheo-Spin NMR contains the functional modules, including (1) the in situ stretching module, (2) the NMR signal acquisition module, and (3) the cavity of the NMR positioning module. The unique ring-like shape of the sample is used to replace the traditional dumbbell sample due to limited space in the NMR probe, and the whole ring-like sample will be deformed during the uniaxial stretching process, which avoids the generation of interference signals from the undeformed sample. The designed stretching assembly made by zirconia ceramics is manufactured to match and stretch the ring-like samples. The strain rate can be tuned within the range of 10^-5-10^-2 s^-1 with the maximum stretching ratio λ_max of ∼3.8. The in situ stretching experiments combined with LF-NMR were carried out successfully with natural rubber of different fractions of carbon black. The time-resolved T₂ relaxometry was adopted to evaluate segmental relaxation during uniaxial deformation which, for the first time, provides the direct and in situ molecular dynamics information. The Rheo-Spin NMR is promising to provide more in-depth insights into the structure and dynamics evolution of polymer products under real service conditions.

The underestimated contribution of the solvent to the phase behavior of highly drug loaded amorphous solid dispersions

In spite of the fact that spray drying is widely applied for the formulation of amorphous solid dispersions (ASDs), the influence of the solvent on the physical properties of the ASDs is still not completely understood. Therefore, the impact of organic solvents on the kinetic stabilization of drug components in a polymer matrix prepared by either film casting or spray drying was investigated. One polymer, PVPVA 64, together with one of four poorly water soluble drugs, naproxen, indomethacin, fenofibrate or diazepam, were film casted and spray dried using either methanol, ethanol, isopropanol, acetonitrile, acetone, dichloromethane or ethyl acetate. For every combination, the highest drug loading that could be formulated as a single amorphous phase was established. The solvent determined the maximum amount of drug that could be kinetically trapped in the polymer matrix and thereby the extent of kinetic stabilization. These maximum drug loadings were compared to the thermodynamic solubilities of the drugs in the seven solvents. Generally, there was no relation between the thermodynamic solubility of a drug and its highest drug loading attained using the same solvent. Hence, the contribution of the solvent to the generation of a supersaturated state should not be underestimated.

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.

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.

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.

Elucidating Relayed Proton Transfer through a His-Trp-His Triad of a Transmembrane Proton Channel by Solid-State NMR

Proton transfer through membrane-bound ion channels is mediated by both water and polar residues of proteins, but the detailed molecular mechanism is challenging to determine. The tetrameric influenza A and B virus M2 proteins form canonical proton channels that use an HxxxW motif for proton selectivity and gating. The BM2 channel also contains a second histidine (His), H27, equidistant from the gating tryptophan, which leads to a symmetric H¹⁹xxxW²³xxxH²⁷ motif. The proton-dissociation constants (pK_a's) of H19 in BM2 were found to be much lower than the pK_a's of H37 in AM2. To determine if the lower pK_a's result from H27-facilitated proton dissociation of H19, we have now investigated a H27A mutant of BM2 using solid-state NMR. ¹⁵N NMR spectra indicate that removal of the second histidine converted the protonation and tautomeric equilibria of H19 to be similar to the H37 behavior in AM2, indicating that the peripheral H27 is indeed the origin of the low pK_a's of H19 in wild-type BM2. Measured interhelical distances between W23 sidechains indicate that the pore constriction at W23 increases with the H19 tetrad charge but is independent of the H27A mutation. These results indicate that H27 both accelerates proton dissociation from H19 to increase the inward proton conductance and causes the small reverse conductance of BM2. The proton relay between H19 and H27 is likely mediated by the intervening gating tryptophan through cation-π interactions. This relayed proton transfer may exist in other ion channels and has implications for the design of imidazole-based synthetic proton channels.

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.

Self-Assembly of Triblock Copolymers from Cyclic Esters as a Tool for Tuning Their Particle Morphology

This paper presents the effect of end groups, chain structure, and stereocomplexation on the microparticle and nanoparticle morphology and thermal properties of the supramolecular triblock copolyesters. Therefore, the series of the triblock copolymers composed of l,l- and d,d-lactide, trimethylene carbonate (TMC), and ε-caprolactone (CL) with isopropyl ( iPr) or 2-ureido-4-[1 H]-pyrimidinone (UPy) end groups at both chain ends were synthesized. In addition, these copolymers were intermoleculary stereocomplexed by polylactide (PLA) blocks with an opposite configuration of repeating units to promote their self-assembly in various organic solvents. The combination of two noncovalent interactions of the end groups and PLA enantiomeric chains leads to stronger interactions between macromolecules and allows for alteration of their segmental mobility. The simple tuning of the copolymer microstructure and functionality induced the self-assembly of macromolecules at liquid/liquid interfaces, which consequently leads to their phase separation in the form of particles with diameters ranging from 0.1 μm to 10 μm. This control is essential for their potential applications in the biomedical field, where biocompatible and well-defined microparticles and nanoparticles are highly desirable.