Cyber-Enabled Predictive Models for Polymer Nanocomposites: Multiresolution Simulations and Experiments

Purdue University, West Lafayette IN

Investigators

Abstract

CMMI 0826356 Cyber-enabled predictive models for polymer nanocomposites: multiresolution simulations and experiments PI: Alejandro Strachan, School of Materials Engineering, Purdue University This CMMI project will develop an experimentally-validated, predictive modeling framework to describe the mechanical response of polymer nanocomposites. While the framework will be applicable to a wide range of materials this effort will focus on polyimides reinforced with carbon nanotubes and graphene sheets and the fundamental phenomena that govern the mechanical properties of these materials, including: i) the role of particle functionalization on dispersion and interfacial strength; ii) changes in polymer structure and properties near the particles; and iii) nucleation and propagation of mechanisms of inelastic deformation and failure. To achieve these objectives this project will utilize multi-resolution theoretical and experimental techniques starting with electrons and atoms via ab initio and molecular dynamics simulations and atomic force microscopy and also capturing mesoscale and macroscopic phenomena via phase field micromechanical modeling and mechanical characterization experiments. This project will seek to maximize its impact and outreach to the research and educational communities by cyber-enabling the simulation tools and deploying educational content online via nanoHUB.org (developed by NSF?s Network for Computational Nanotechnology). nanoHUB enables users to run live simulations using simply a web-browser. Such a cyber-enabled, predictive tool for the simulation of polymer nanocomposites has the potential to help design next-generation materials with improved strength that will impact established industries including aerospace and automobile as well as emerging applications like micro electro-mechanical systems (MEMS). It is expected that this resource will be used by a large number of scientists and engineers in industry and national labs thus facilitating the technology transfer from academia to the end users who can transform it into products that benefit society.