Deep Learning for Determination of Properties of Semidilute Polymer Solutions AITranslate

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DOI：https://doi.org/10.1021/acsapm.3c01282

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The ability to predict polymer solution viscosity is essential for polymer characterization and processing. Here, we use a synergistic approach combining the scaling theory of polymer solutions and convolutional neural network (CNN) models to obtain system-specific parameters and describe semidilute solution viscosity in the unentangled and entangled solution regimes. The scaling approach relies on the existence of a characteristic microscopic length scale─the solution correlation length (correlation blob size) ξ─which uniquely defines macroscopic solution properties. It is based on a relationship between the solution correlation length ξ = lgν/B and the number of monomers g per correlation volume for polymers with the monomer projection length l. The system-specific set of parameters Bg, Bth, and 1 in the corresponding solution regime with the scaling exponent ν = 0.588, 0.5, and 1, respectively. Applying two CNN models, we obtained the sets Bg and Bth from the solution specific viscosity, ηsp, as a function of concentration, c, and weight-average degree of polymerization, Nw. The CNN was trained on theoretically generated datasets converted to sparse images representing the normalized specific viscosity ηsp/Nw (cl3)1/(3ν–1) in the unentangled Rouse regime. The trained CNN was utilized in automated data analysis of the solution viscosity of polystyrene, poly(ethylene oxide), poly(methyl methacrylate), poly(acrylonitrile-co-itaconic acid), cellulose, sodium hyaluronate, hydroxypropyl methyl cellulose, methyl cellulose, hydroxypropyl cellulose, cellulose tris(phenyl carbamate), xanthan gum, galactomannan, and sodium κ-carrageenan in water, organic solvents, and ionic liquids. This approach produced values of the B-parameters with mean absolute percentage differences of less than 6% from the corresponding values determined by the manual data analysis. The B-parameters are then used to obtain the packing number Pe defining the onset of entanglements in polymer solutions and to describe semidilute solution viscosity as a function of concentration and Nw.