Synergistic Modeling: Manufacture and Design of 'Nano' Microstructures

University South Carolina Research Foundation, Columbia SC

Investigators

Abstract

The objective of this grant is to develop mathematical models describing the design and manufacture of multi-functional polymer nanocomposites. The models will quantify the physics behind the use of electric and magnetic force fields to manipulate and precisely position nanoscale particles; creating designed "nano" microstructures. Models will also be developed to predict bulk effective properties, mechanical, electrical and magnetic, resulting from the designed microstructures, which can be used to tailor composite design to application. The models will be based on input and insight from an experimental team (supported separately) performing parallel work with similar goals; this approach will harness the synergistic power of the combination of modeling (mathematics) and multi-scale experiment (visualization). This work addresses one of the fundamental challenges to achieving the promise of nanomaterials; specifically, how to achieve precise spatial positioning of nanoscale materials and use this as a mechanism to bring the science of the nanoscale to realization at the macroscale. If the underlying physics can be effectively linked to a sequence of manufacturing stages, precision engineering of nanoscale elements could enable a cascade of paradigm shifting technologies, e.g. electronically, optically or environmentally-smart thin film nanocomposites. This work also emphasizes the effectiveness of building models around experimental insight; the use of experiments to suggest models and build a visual physical intuition in modelers, and the use of models to suggest and guide experiments. This grant will also develop visualization based engineering case studies for pre-engineering or introductory engineering design courses. Applying the same synergistic approach, linking mathematics and visualization, in the venue of introductory engineering will allow beginning students to explore more sophisticated design problems, bring them into "real" engineering earlier, and help increase retention rates by providing hem with a physical intuition on which to build their mathematical intuition.