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Numerical modeling of viscoelastic properties is critical to developing thestructure-property relationship of polymer nanocomposites. While it isrecognized that the altered polymer region near filler particles, theinterphase, significantly contributes to enhancements of composite properties,the spatial distribution of interphase properties is rarely considered due tolack of local property measurements. In recent years, the Atomic ForceMicroscopy (AFM) technique has begun to make local property measurements of theinterphase available. In the light of the increasing availability of AFM data,in this work a new interphase representation for modeling the viscoelasticproperties of polymer nanocomposites is proposed. The proposed interphaserepresentation disentangles the interphase behavior by two separate components-- single-body interphase gradient and multi-body compound effect, whosefunctional forms are learned via data mining. The proposed interphaserepresentation is integrated into a Finite Element model, and the effects ofeach component of the interphase representations are numerically studied. Inaddition, the advantages of the proposed interphase representation aredemonstrated by comparison to a prior simulation work in which only a uniformeffective property of the interphase is considered. Moreover, the proposedinterphase representation is utilized to solve the inverse problem of inferringspatial distribution of local properties using Bayesian Inference onexperimental data.

Rethinking Interphase Representations for Modeling Viscoelastic Properties for Polymer Nanocomposites