Enhancing the predictability and reliability of mechanical machining on the nanoscale via a novel modelling approach
The development of novel nano-scale manufacturing technologies is a research area of high importance.
This project is advertised as part of the EPSRC Doctoral Training Partnership. It is currently not available to self-funded applicants. Find out more information about the DTP including how to apply.
Although vacuum and mask-based lithography techniques are already employed in industry for small-scale manufacturing of semi-conductor devices, they still have a number of limitations associated with them. In particular, these fabrication technologies rely on capital-intensive equipment while being restricted to the fabrication of planar features and constrained to a limited set of processed materials. Besides, there are also increased concerns over their environmental friendliness as they are energy and resource intensive and generate significant waste.
In this context, the remit of this PhD project is on the investigation of an alternative mechanical machining process at nano-scale which can potentially address these technological gaps. As demonstrated by the main supervisor of this PhD project, this process can be successfully realised on an Atomic Force Microscope (AFM) where the AFM probe is simply used as a nano-scale cutting tool.
The current research issue affecting the wider utilisation of AFM probe-based nanomachining is the lack of a suitable modelling approach to predict the process output. Indeed, the majority of research efforts in this field rely on experimental trial and error strategies. Overall, these provide limited insight into the machining phenomena and limited scope for predicting the machining response when new processing conditions are investigated. For this reason, this PhD project is proposing to model this particular process using Smooth Particle Hydrodynamics (SPH). SPH is a particle based method which is very effective in modelling materials subjected to large deformation and fracture.
The supervisory team will provide complementary expertise to address specific challenges for this project. Dr Brousseau has ample knowledge in the implementation of this process while Dr Kulasegaram has been developing SPH codes for many years to solve a range of engineering problems.