Skip to main content Skip to navigation

Dr J R Kermode

Atomistically Informed Fatigue Crack Growth Models

Supervisor: Dr James Kermode (Engineering) and Tyler London (TWI, Cambridge). The demanding conditions experienced by welded structures create significant challenges for design and assessment. Due to their reliance on empirical criteria, existing fracture mechanics assessment codes and standards are insufficient.

Advanced Boundary Conditions to Enable Quantification of Uncertainty in Atomistic Simulation of Defects

Supervisors: Dr James Kermode (Engineering) and Prof. Christoph Ortner (Mathematics). Accurate models for energy barriers involved in material defect evolution are essential to understanding many processes in high-performance alloys, for example, thermal evolution of radiation damage in nuclear reactor shields.

Predictive Modelling of Chemomechanical Materials Failure Processes

A highly motivated PhD candidate is sought to join the group of Dr James Kermode in the Warwick Centre for Predictive Modelling at the University of Warwick. Despite the potential for significant technological and economic impact, remarkably little is known about the fundamental mechanisms that cause many materials to fail. The proposed PhD research will use atomistic simulations of processes such as fracture and dislocation creep to not only improve our understanding of materials failure but also suggest strategies to control it.

Accurate simulations of these “chemomechanical” processes where stress and chemistry are tightly coupled have only recently been made practical using novel multiscale techniques developed by Dr Kermode [1-3]. This PhD project will use these techniques together with High Performance Computing to carry out simulations of materials failure processes. The ultimate goal is to address the heavy reliance of current continuum models on empirical failure criteria, by replacing these with atomistically informed criteria including reliable probabilistic “error bars” that describe the effects of model error and limited data. This is expected to lead to predictive models of great interest to industry.

Several different real-world application areas are possible:
1. Helping to address the unsustainably high energy cost of breaking up mineral ores
2. Developing sharper diamond cutting tools
3. Improving the resilience of submerged pipelines where the cost of inspection is very high

The Warwick Centre for Predictive Modelling ( provides a rich interdisciplinary research environment focussed on providing a framework for the application of predictive modelling and uncertainty quantification tools in science and engineering research.

If you have any questions or would like more information on the above, please contact Dr James Kermode.

Note: Should your application for admission be accepted you should be aware that this does not constitute an offer of financial support. Please refer to the scholarships & funding pages.