Modelling of fluid flow through perfectly ordered 3D printed structures
In my group, we employ 3D printing methods to produce perfectly ordered structures and novel materials with applications in a range of industries, e.g. bioprocessing, biotechnology, pharmaceutical and food. We have already demonstrated that ordered 3D structures and smart materials can substantially increase the performance of key steps in such industries, for example in the purification of biomolecules such as proteins, DNA, and viruses.
In this project, you will identify and test novel geometries with superior performances in operations such as purification of biomolecules and microbial bioreactors. You will capitalize on the modelling expertise held in the group to simulate the fluid flow through perfectly ordered porous media, including mass transfer characteristics of the key molecules present in the system, e.g. proteins, DNA, viruses and cells.
You will employ the Lattice Boltzmann method and the supercomputing facilities available at the University of Edinburgh. Through this project, you will learn practical aspects in bioprocessing and biotechnology. You will collaborate with research students and postdoctoral fellows working on other aspects of perfectly ordered 3D printed porous media.
Good troubleshooting, communication and team-working skills are necessary for this project.
Minimum entry qualification
Honours degree at 2:1 or above (or International equivalent) in chemical engineering, chemistry, materials science, biomedical engineering, biochemistry or biotechnology. For further information on English language requirements for EU/Overseas applicants: https://www.ed.ac.uk/studying/international/english/postgraduate
EPSRC funding to cover tuition fees and stipend might be available for Home/EU students, but applications are also welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.
How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)
FTE Category A staff submitted: 91.80
Research output data provided by the Research Excellence Framework (REF)
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