Modelling approaches for Percolating Nanoparticle/Nanotube Networks

Networks made from nanoparticles show interesting properties when prepared close to the percolation threshold. At this threshold the particle density just allows that conducting pathways can be formed. We will look at networks made from carbon nanoparticles or nanotubes embedded in a polymer matrix. Those networks have possible applications as stretch sensors and for neuromorphic computing. This project aims to develop a modelling framework describing the complicated but sought-after, highly nonlinear electric properties of the networks. It builds on modelling work describing the piezoresistivity of 2D carbon nanoparticles in an elastomer under stretching or compression that explains the complex electric strainresponse evidenced by huge spikes in piezoresistivity. The ability to predictmacroscopic properties from the nanocomponents’ interactions leads the way to the design of intelligent materials.

We are looking for a student with a strong Honours or Master’s degree in physics, theoretical chemistry, engineering or a related field with a background in computational modelling.

This PhD project, supported through the MacDiarmid Institute, comes with a stipend and paid fees.

Page expires: 12 March 2026