About the project
This project combines advanced molecular modelling, machine learning, and quantum chemistry to predict how energetic compounds interact with ionic liquids—unlocking lightweight, adaptable sensing systems for defence. It includes collaboration with industrial sponsor, and interdisciplinary CDT training.
Explosives detection is critical for defence and security, yet current physicochemical sensors are often bulky and power-hungry. Biological systems, by contrast, offer exceptional sensitivity and adaptability with far lower size, weight, and power demands. Unlocking this potential requires overcoming a major challenge: enabling biological sensing elements to interact with energetic compounds that are poorly soluble in water and chemically complex.
This project will tackle that challenge by developing a computational pipeline to identify optimal ionic liquids (ILs) and deep eutectic solvents (DESs) for dissolving and stabilising explosives. Using advanced molecular modelling, machine learning, and large-scale quantum chemistry, the project will predict solubility and stability, validate models against experimental data, and ultimately enable rational design of novel solvents tailored for biosensing applications.
The research is highly interdisciplinary, combining chemistry, data science, and defence technology. It includes close collaboration with an industrial partner, offering unique access to defence expertise and experimental validation, as well as opportunities for placements and networking. You'll also benefit from cohort-based learning, specialist modules, and professional skills training.
This project will be supervised by Professor Chris‑Kriton Skylaris and Professor Jonathan Essex through the University of Southampton’s EPSRC Centre for Doctoral Training in Complex Integrated Systems for Defence and Security (CISDnS). It also includes Dr Thomas J. Piggot as an external supervisor.
