Year: 2023
Type: article
Abstract: 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 = lg ν / B and the number of monomers g per correlation volume for polymers with the monomer projection length l . The system-specific set of parameters B g, B th, 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 B g and B th from the solution specific viscosity, η sp, as a function of concentration, c, and weight-average degree of polymerization, N w . The CNN was trained on theoretically generated datasets converted to sparse images representing the normalized specific viscosity η sp / N w ( cl 3 ) 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 P e defining the onset of entanglements in polymer solutions and to describe semidilute solution viscosity as a function of concentration and N w .
Source: ACS Applied Polymer Materials
Authors: Ryan Sayko, Michael Jacobs, Marissa Dominijanni, Andrey V. Dobrynin
Language: English
Subfield: Fluid Flow and Transfer Processes
Field: Chemical Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4386439824