This PhD project will investigate next-generation epoxy resin composite insulation materials to facilitate the use of clean energy and power. The project will focus on how filler type, filler concentration and filler-interface structure influence charge transport, electric-field distribution, thermal performance, mechanical stability and ageing behaviour.

A key scientific challenge in material optimisation is improving one property could compromise another, such as thermal conductivity/toughness versus dielectric strength/processability/long-term stability. Therefore, the student will develop a physics-guided materials selection framework combining finite-element electric-field modelling, molecular dynamics simulation, laboratory-scale material characterisation and data-efficient machine learning.

This PhD project will investigate next-generation epoxy resin composite insulation materials to facilitate the use of clean energy and power. The project will focus on how filler type, filler concentration and filler-interface structure influence charge transport, electric-field distribution, thermal performance, mechanical stability and ageing behaviour.

A key scientific challenge in material optimisation is improving one property could compromise another, such as thermal conductivity/toughness versus dielectric strength/processability/long-term stability. Therefore, the student will develop a physics-guided materials selection framework combining finite-element electric-field modelling, molecular dynamics simulation, laboratory-scale material characterisation and data-efficient machine learning.