Professor Shujun Zhang
Institute for Superconducting and Electronic Materials, University of Wollongong, Australia.
Professor Timon Rabczuk
Machine Learning for Microstructures and Materials
However, modeling flexoelectricity is challenging due to the C1 requirement of the underlying discretization. This presentation will propose an efficient computational formulation for flexoelectric nano-structures which exploits the higher continuity of the underlying discretization and therefore avoids a complex mixed formulation. Furthermore, an efficient level-set based topology optimization will be presented. The formulation will subsequently be extended to multi-materials and it will be shown that adding soft materials can significantly enhance the energy conversion efficiency of a composite energy harvester.