Profile

Nathan Ellmer is a PhD researcher in Computational Mechanics at Swansea University, where he also supports undergraduate teaching as a Teaching Assistant across a range of Engineering modules. He previously completed a BEng in Aerospace Engineering with a Year in Industry at Swansea University.

His research focuses on the application of Machine Learning to the development of advanced constitutive models for complex materials, particularly those used in smart material systems. His work aims to enhance the predictive modelling of hyperelastic, electromechanically coupled materials with intricate microstructures – key components in emerging technologies such as soft robotics.

Of particular interest are Electroactive Polymers (EAPs), which show great potential for use in soft actuators, sensors, and energy harvesting devices. Given the complexity of EAP behaviour, the research is driven by the need for accurate, simulation-based design tools to support innovation in this growing field.

Furthermore, Nathan contributes to the Smart Materials and Soft Robotics (SMaSR) Lab at Swansea University, where he is involved in the development of advanced fabrication techniques through additive manufacturing. The labs work is interested in creating custom 3D printing feedstock for highly flexible dielectric and conductive materials. This will enable the production of intricate dielectric elastomer actuator (DEA) devices, supporting the next generation of soft robotic systems through integrated design and manufacturing workflows.

Area of Expertise

• Computational Modelling
• Gaussian Process Regression (Machine Learning)
• Multi-physics and Multi-scale Modelling
• 3D Printing