Grantham Scholar Aidan Miller’s project seeks to apply cutting edge process systems and Machine Learning approaches to enable an effective fuel cycle in nuclear fusion reactors.
Aidan is a PhD researcher based in the Chemical and Biological Engineering department. He is supervised by Prof. Solomon Brown and is a member of the Brown Group. For his PhD he is working in collaboration with the UKAEA.
A net zero future demands low carbon energy. Nuclear power has always offered a solution however, traditional nuclear power generates significant amounts of long term radioactive waste which is dangerous and costly to dispose of. Nuclear fusion lacks this huge caveat but it still requires huge advancements in research and technology before it can be implemented in a commercial setting.
An area of research that needs to be developed in fusion is the isotopic separation of Tritium as it is used as fuel in nuclear fusion reactors. Aidan’s research will focus on the modelling Tritium separation from the other hydrogen isotopes using pressure swing adsorption. The models used will then be adapted and applied to different sorbent materials to determine the materials that will be selected for fusion plants.