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PhD Studentship: Understanding Shale Rock Swelling for Energy Systems: Novel Integrated Modelling and Experimental Approaches

The University of Manchester - Chemistry

Qualification Type: PhD
Location: Manchester
Funding for: UK Students, EU Students, International Students
Funding amount: £18,622
Hours: Full Time
Placed On: 16th January 2024
Closes: 31st May 2024

A fully funded PhD position is available in the group of Professor Carbone (Department of Chemistry) and Professor Taylor (Department of Earth Science) at the University of Manchester starting from September 2024. Tuition fees will be covered and you will receive tax free stipend at the UKRI rate (£18,622 for 2023/24). This is for UK students only.

When immersed in solution or exposed to high relative humidity, natural and synthesised porous materials tend to swell. The swelling occurs not only in the macro- and mesoscopic pores, but also in the nanometer-scale ones, where the fluid molecules are confined and pressure can build up very rapidly affecting the mechanical stability of the entire structure. Swelling in response to interaction with water is a particular critical issue in subsurface engineering as shales (fine-grained sedimentary rocks with low porosity and ultra-low permeability) in contact with water, expand. In the case of waste disposal, swelling can provide important barriers around the waste and enhance the sealing ability of rocks. For shale gas exploration purpose, however, swelling may cause wellbore instability. Therefore, a careful study of shale swelling is critical for subsurface energy related applications such as carbon capture or shale gas exploration.

In this project we will use a novel combination of molecular dynamics and grand canonical montecarlo simulations [1] and state-of-art experiments [2] to investigate the swelling mechanism of shale rocks. The student will have the opportunity to not only develop the molecular model for the rocks and perform the simulations but also to integrate the simulation results with the experimental data for validation and model optimization.

The student will join two active and multidisciplinary groups and work across departments using cutting edge modelling and experimental techniques. Pre-knowledge on simulation methods or programming is desirable but not necessary.

Please contact the supervisors before you apply: Prof Carbone and Prof Taylor: paola.carbone@manchester.ac.uk kevin.taylor@manchester.ac.uk

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