Morphology of Industrially Relevant Polymers by 1 H NMR Spin-Diffusion

Applied Magnetic Resonance(2023)

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摘要
Applications of time-domain 1 H NMR spin-diffusion experiments for studying morphology of industrially relevant polymers are reviewed. The method exploits the contrast in molecular mobility in different phases in multi-phase organic materials, which could be in some cases advantageous to traditional morphological methods. A brief overview of different time-domain spin-diffusion methods and data analysis is provided. The effect of domain size distributions and their clustering, which were previously analyzed by numerical simulations of spin-diffusion curves, is discussed. Examples of different types of morphology in polymers with hard and soft domains are presented, namely, lamellar morphology and its changes during annealing; interfacial layers in different types of polymers; fragmented structure of crystal lamellae in isotactic polybutene-1 and its copolymer with form I crystals; fibrillar morphology of melt-spun Nylon 6 and poly(ethylene terephthalate) fibers; morphology of gel-spun ultra-high-molecular-weight polyethylene fibers; ionic clusters in polymeric ionomers; the rubber–filler interface in filled rubbers; the structure of network of physical junctions in filled rubbers and ionomers; and morphology of thermoplastic polyurethanes. Domain sizes from the NMR method are compared with those determined for the same materials by small-angle X-ray scattering and transmission electron microscopy. All results are in good agreement. In addition to domain sizes, the NMR method provides several details of polymer morphology, namely, morphological heterogeneities, the type and the thickness of interfacial layers, the presence of (sub)nano-domains, and molecular mobility in different phases. Thus, the method offers information that is complementary to the conventional methods. The effect of structural heterogeneities on macroscopic properties is briefly discussed.
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industrially relevant polymers,nmr,spin-diffusion
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