Modelling atmospheric plasma processes for biofunctionalization in additive manufacturing

Summary

This project will develop multiphysics models of atmospheric pressure plasma systems to engineer interfaces and biofunctionalised scaffolds in 3D bioprinting.  
The Applied Physics and Plasma Surface Engineering group is seeking applications from highly motivated PhD candidates with strong communication skills, a demonstrated ability to work independently, and a desire to make meaningful contribution to state-of-the-art biomedical and plasma technologies. Potential candidates with backgrounds in plasma physics, computational fluid dynamics/finite element modelling, nanotechnology, chemical engineering, mechanical engineering, chemistry, or surface engineering are encouraged to apply. Selected candidates will be supported to apply for suitable scholarships where eligible.  
A complimentary scholarship for this project may be available through a competitive process. To find out more, refer to the Faculty of Science Postgraduate Research Excellence Award and contact Prof Marcela Bilek directly.

Supervisors

Professor Marcela Bilek, Dr Mark Baldry.

Research location

School of Physics

Program type

PHD

Synopsis

3D bioprinting, also known as biofabrication, promises highly patient-specific disease models and biomedical implants. However, an ability to tailor surface biocompatibility and interfacial bonding between printed components, such as polymers and hydrogels, is currently lacking. We are developing atmospheric pressure plasma processes that can locally activate polymeric surfaces for the reagent-free covalent attachment of proteins and hydrogel in a single-step process at desired locations throughout the printed structures. To develop the process further we need a deep understanding of the mechanisms that underpin the surface activation we observed.
This multidisciplinary project will offer candidates the opportunity to develop and optimise finite element models of the complex physical phenomena occurring within an experimental atmospheric pressure plasma jet. Plasma dynamics will be investigated using drift-diffusion and heavy species transport models to understand the strong spatial and temporal gradients formed during operation, whilst fluid-particle models will be used to monitor atmospheric entrainment in plasma jets. Candidates will work closely with experimentalists to apply the knowledge gained from the modelling to guide atmospheric plasma process design and 3D printing biofunctionalisation experiments.

Additional information

A complimentary scholarship for this project may be available through a competitive process. To find out more, refer to the Faculty of Science Postgraduate Research Excellence Award and contact Prof Marcela Bilek directly.    
HDR Inherent Requirements: In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include: 

• Confidential disclosure and registration of a disability that may hinder your performance in your degree;
• Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
• Ability to perform independently and/or with minimal supervision;
• Ability to undertake certain physical tasks (e.g. heavy lifting);
• Ability to undertake observatory, sensory and communication tasks;
• Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
• Ability to work in confined spaces or at heights; Ability to operate heavy machinery (e.g. farming equipment);
• Hold or acquire an Australian driver’s licence;
• Hold a current scuba diving license; 
• Hold a current Working with Children Check;
• Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Opportunity ID

The opportunity ID for this research opportunity is 2820

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