Using Taylor dispersion profiles to characterize polymer molecular weight distributions
文献信息
Brad Kelly, Derek G. Leaist
Optical interferometry and NMR spectroscopy can be used to characterize polymer molecular weight distributions from diffusion measurements. The present work develops the relatively simple Taylor dispersion technique for this purpose. Small volumes of polymer solution are injected into laminar carrier streams of solvent flowing through a long capillary tube. The broadened distribution of the dispersed polymer sample is monitored at the tube outlet by a liquid-chromatography differential refractometer detector. Moments analysis of the refractive-index profiles generated by the dispersion of dilute nonionic i-mers with diffusion coefficients Di shows that the profile height and first moment divided by the profile area provide the mass-average values of Di1/2 and Di−1/2, respectively. This information can be used to estimate molecular weight distributions if the form of the distribution (Poisson, log-normal etc.) is known. Alternatively, a linear combination ∑aiP(Mi*) of a small basis set of dispersion profiles P(Mi*) for monodisperse solutes of molecular weight Mi* spanning the molecular weight range of the polydisperse sample can be fitted to measured profiles. The number-average and mass-average molecular weights (MN and MM) are evaluated using MN = ∑ai/(∑ai/Mi*) and MM = (∑aiMi*)/∑ai. The proposed methods for studying molecular weight distributions are tested by measuring dispersion profiles for aqueous solutions of mixed glycols with accurately known weight distributions prepared by mixing ethylene glycol and pure ethylene glycol oligomers.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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