Over the last decade, smart polymer nanocomposites have been extremely sought for designing next generation gadgets in a wide range of industries (i.e., aerospace, electronics, automotive, biomedical, household)[1][2]. Smart materials respond to slight changes in their environment (i.e., temperature, mechanical stress, pH, light) by changing their properties dramatically [3]. Recently, polymer nanocomposites are reinforced with nanostructured fillers[4-7], e.g., Graphene (Gr), Graphene oxide (GO), reduced Graphene oxide (rGO) and Carbon nanotube (CNT) because of their exceptional mechanical, thermal, and electrical capabilities. Thus, in this study, a multiscale modeling framework [8] that incorporates data spanning from atomistic to mesoscopic to continuum techniques were performed. We investigate thermo-physical properties such as density, glass transition temperature, specific heat capacity, elastic constant, Poisson’s ratio, and thermal conductivity of carbon nanofiller reinforced thermoset and thermoplastic polymers and experimentally validated.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Initially, the Coarse-Grained (CG) potentials of neat polymers (thermoplastic: Polypropylene (PP), Polylactic acid (PLA), and thermoset: Epoxy resin) are determined by upscaling the atomistic information. The CG potentials are used to develop the most suitable mesoscopic model that imitates the thermo-physical properties determined experimentally. Furthermore, the nanofillers (Gr, GO and rGO) are also coarse-grained and then CG Molecular Dynamic (MD) simulations were performed to determine the effect of nanostructure fillers on thermal-physical properties of polymers. Second, to bridge mesoscopic and macroscopic scales, continuum finite element simulations were accomplished by using the output of CG MD simulations as input for the finite element and mean field analysis. Finally, an experimental thermo-mechanical characterization of nanocomposites has been carried out to validate the proposed approach and highlight its advantages over consolidated modeling strategies. Our study predicts that increasing carbon percentage in polymers results in improved mechanical and thermal behaviour of nanocomposite.The authors acknowledge the European Union’s Horizon 2020 research and innovation program SMARTFAN under grant agreement N. 760779 for financial support.References[1]. Mohamed El Mehdi Mekhzom et al., ‘Introduction: different smart materials and their practical applications’ in Polymer Nanocomposites-Based Smart Materials, 2020, Pages 1-19.[2]. Asim Ali Yaqoob et al., ‘Introduction of smart polymer nanocomposites’ in Smart Polymer Nanocomposites, 2021, Pages 1-25.[3]. Myleidi et al., Thermoresponsive Polymer Nanocomposite, Encyclopedia of Materials:Composites, 2021, 510-526.[4]. Tapas Kuilla et al., Recent advances in graphene based polymer composites, Progress in Polymer Science, 2010, 35 (11), 1350-1375.[5]. Ayesha Kausar et al., Review of Applications of Polymers/Carbon Nanotubes and Epoxy/CNT Composites, Polymer-Plastics Technology and Engineering in Polymer Science, 2016, 55 (11), 1167-1191.[6]. Chiavazzo Elio et al., Reconstruction and modeling of 3D percolation networks of carbon fillers in a polymer matrix, International Journal of&nbsp; Thermal Science 2010, 49(12), 2272-2281.[7]. Fasano Matteo et al., Thermal transimittance of carbon nanotube networks:Guidelines for novel thermal storage systems and polymeric material of thermal interest, Renewable and Sustainable Energy Reviews&nbsp; 2015, 41, 1028-1036.[8]. Rajat Srivastava et al., ‘Modeling carbon-based smart materials’ in Carbon Based Smart Materials, 2020, Pages 33-80.

Thermo-Physical Properties of Carbon-Based Smart Polymer Nanocomposites: A Multiscale Modeling Approach

Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2021/volume/85543

ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021)

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