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Mykyta Chubynsky

University of Warwick

Understanding and Optimising 3D Printing Processes Via Modelling

Despite many successes in developing and improving additive manufacturing techniques, many challenges remain and resolving them requires better understanding of the underlying physical and chemical processes. While experimental analytical techniques help in this regard, they have a limited space and time resolution and not all quantities are measurable. Computational modelling can provide missing information; it can also help optimise the processes without repeated costly and time-consuming experiments. In this talk I will discuss how we as modellers hope to make an impact, our progress so far and the challenges we face. In particular, for inkjetting with molten metal drops (MetalJet), an important practical issue is sometimes poor bonding of solidified drops to each other and to the substrate, particularly in the multimaterial case. It is not well-understood why some pairs of materials bond poorly; an even more important practical question is how to optimise bonding given the materials, by changing the temperatures of the drop and the substrate, as well as jetting speed and surface roughness. One challenge here is modelling drop solidification and arrest of spreading, particularly when taking surface roughness into account. For laser nanoprinting via two-photon polymerisation, a modelling challenge is in devising a model that is computationally tractable for samples consisting of millions of voxels. I will also discuss the work of P. Zhao et al. on a model of UV curing in polymer inkjet printing that was used to optimise the printing strategy to improve the uniformity of curing.

Biography

Mykyta V. Chubynsky is a Research Fellow in the Mathematics Institute at the University of Warwick, where he has been since 2016. After an undergraduate degree from Taras Shevchenko National University of Kyiv in Ukraine and a Ph.D. from Michigan State University (both in physics), he held postdoctoral positions at Arizona State University, Université de Montréal, and University of Ottawa. He has done theoretical and computational research on a large variety of topics, including rigidity percolation in elastic networks with application to covalent glasses, models of diffusion in complex systems and for drug release applications, methods of Monte Carlo and molecular dynamics simulations, and electrophoresis of biopolymers. At Warwick, in addition to his work on modelling AM processes, he has been involved in research on micro- and nanoscale effects in liquid drop dynamics.

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