| Literature DB >> 27524957 |
Curt M Breneman1, L Catherine Brinson2, Linda S Schadler3, Bharath Natarajan3, Michael Krein1, Ke Wu1, Lisa Morkowchuk1, Yang Li2, Hua Deng2, Hongyi Xu2.
Abstract
Accelerated insertion of nanocomposites into advanced applications is predicated on the ability to perform a priori property predictions on the resulting materials. In this paper, a paradigm for the virtual design of spherical nanoparticle-filled polymers is demonstrated. A key component of this "Materials Genomics" approach is the development and use of Materials Quantitative Structure-Property Relationship (MQSPR) models trained on atomic-level features of nanofiller and polymer constituents and used to predict the polar and dispersive components of their surface energies. Surface energy differences are then correlated with the nanofiller dispersion morphology and filler/matrix interface properties and integrated into a numerical analysis approach that allows the prediction of thermomechanical properties of the spherical nanofilled polymer composites. Systematic experimental studies of silica nanoparticles modified with three different surface chemistries in polystyrene (PS), poly(methyl methacrylate) (PMMA), poly(ethyl methacrylate) (PEMA) and poly(2-vinyl pyridine) (P2VP) are used to validate the models. While demonstrated here as effective for the prediction of meso-scale morphologies and macro-scale properties under quasi-equilibrium processing conditions, the protocol has far ranging implications for Virtual Design.Entities:
Year: 2013 PMID: 27524957 PMCID: PMC4981086 DOI: 10.1002/adfm.201301744
Source DB: PubMed Journal: Adv Funct Mater ISSN: 1616-301X Impact factor: 18.808