Modeling the Additive Effects of Nanoparticles and Polymers on Hydrogel Mechanical Properties Using Multifactor Analysis

Author:

Barrett-Catton Emma,Pedersen Kyle,Mobed-Miremadi MaryamORCID,Asuri PrashanthORCID

Abstract

Interpenetrating networks (IPN)s have been conceived as a biomimetic tool to tune hydrogel mechanical properties to the desired target formulations. In this study, the rheological behavior of acrylamide (AAm) [2.5–10%] hydrogels crosslinked with N,N′-methylenebis(acrylamide) (Bis) [0.0625–0.25%] was characterized in terms of the saturation modulus affected by the interaction of silica nanoparticle (SiNP) nanofillers [0–5%] and dextran [0–2%] at a frequency of 1 Hz and strain rate of 1% after a gelation period of 90 min. For single-network hydrogels, a prominent transition was observed at 0.125% Bis for 2.5% AAm and 0.25% Bis for 5% AAm across the SiNP concentrations and was validated by retrospective 3-level factorial design models, as characterized by deviation from linearity in the saturation region (R2 = 0.86). IPN hydrogels resulting from the addition of dextran to the single network in the pre-saturation region, as outlined by the strong goodness of fit (R2= 0.99), exhibited a correlated increase in the elastic (G’) and viscous moduli (G”). While increasing the dextran concentrations [0–2%] and MW [100 kDa and 500 kDa] regulated the increase in G’, saturation in G” or the loss tangent (tan(δ)) was not recorded within the observed operating windows. Results of multifactor analysis conducted on Han plots in terms of the elastic gains indicate that amongst the factors modulating the viscoelasticity of the IPN hydrogels, dextran concentration is the most important (RDex = 35.3 dB), followed by nanoparticle concentration (RSiNP = 7.7 dB) and dextran molecular weight (RMW = 2.9 dB). The results demonstrate how the Han plot may be systematically used to quantify the main effects of intensive thermodynamic properties on rheological phase transition in interpenetrating networks where traditional multifactor analyses cannot resolve statistical significance.

Funder

School of Engineering at Santa Clara University

Publisher

MDPI AG

Subject

General Materials Science,General Chemical Engineering

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