PhD Studentship: Machine Learning Accelerated Design of Composite Materials for Hydrogen Economy

Supervisors:

Supervisors: Dr. Lukasz Figiel (Warwick Manufacturing Group (WMG), Prof. James Sprittles (Maths), Dr. Gabriele Sosso (Chemistry)

Summary:

Hydrogen is a zero-carbon emission fuel with the potential to decarbonise automotive and aerospace industries. Design of super-durable composite materials that can sustain harsh hydrogen environments is critical to achieving decarbonisation goals for the benefit of our planet. Multi-scale modelling methodologies that integrate modelling concepts from chemistry, physics, and engineering, and are accelerated with Machine Learning (ML), are crucial for accurate and efficient design of composites. This project will develop a radically-new predictive platform by combining mechanistic and data-driven approaches within the Bayesian framework. The platform will generate new knowledge and computer design tools, enabling wider exploitation of composite materials in hydrogen economy.

Project Outcomes:

• Experimentally-validated multiscale modelling platform to predict reversible and irreversible physico-chemo-mechanical phenomena for composites under real-world conditions
• Surrogate models with uncertainty quantification of input parameters across the scales
• New understanding and design guidelines for the certification of composite materials for applications in hydrogen economy

The successful candidate will be part of the Figiel Research Group and will collaborate closely with co-supervisors at Mathematics and Chemistry Departments at the University of Warwick. The candidate will also have opportunity to interact closely with industry (e.g. Baker Hughes Ltd, National Composites Centre).

https://warwick.ac.uk/fac/sci/hetsys/themes/projectopportunities/

Additional Funding Information

Awards for both UK residents and international applicants pay a stipend to cover maintenance as well as paying the university fees and a research training support. The stipend is at the standard UKRI rate.

For more details visit: https://warwick.ac.uk/fac/sci/hetsys/apply/funding/