Modelling plasma surface functionalisation of additively manufactured, porous, prosthetic implants

Summary

This project will develop multiphysics models of plasma surface treatment to enable the creation of prosthetic implants with controllable surface properties and long-term biostability.
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, 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

Conventional prosthetic implants suffer from poor long-term stability in the body, along with suboptimal material properties such as stiffness. Additive manufacturing has enabled the production of porous implants with mechanical properties that can be tuned to match the host environment. Low temperature plasmas can be used to functionalise the surfaces of these materials for the immobilisation of cell adhesion and signalling proteins and/or antimicrobials, thereby enabling cell attachment and tissue integration for robust biocompatibility. 
Careful control of the plasma treatment process, which is dependent on local fluid pressure and electric field strength throughout the porous matrix, is critical to ensure consistent surface functionalisation. This multidisciplinary project will offer candidates the opportunity to develop and optimise finite element models of the complex physical phenomena occurring within a range of plasma reactors. Fluid flow and electric field modelling will be used to survey candidate materials and structures, whilst plasma dynamics will be investigated using drift-diffusion and heavy species transport models to understand the strong spatial and temporal gradients typical of low temperature plasmas. 
Candidates will work closely with experimentalists to apply the knowledge gained from the modelling to guide surface treatment 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 RequirementsIn 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 2818

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