Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  New modelling tools for interfaces and liquid crystals


   Department of Chemical Engineering

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof Andrew Masters, Dr Thomas Rodgers  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Dissipative particle dynamics (DPD) is a meso-scale simulation technique that allows for the rapid modelling of complex structures and complex flows. It has been used to study polymers, gels and emulsions and has important industrial applications for health-care and agricultural products.

The standard technique assumes the molecules are composed of beads that interact via a soft, repulsive potential. For many applications, however, this is too restrictive. One problem is that you cannot model a gas-liquid interface. Another is that you cannot model structured phases, such as liquid crystals. A very promising way to get round this is to use many-body DPD. While the basic ideas are published (see below) we aim to add several new features.

Firstly, conventional DPD models show no dielectric effects. We have recently developed new, polar DPD models that get round this problem. These models, however, cannot not be used for vapour-liquid interfaces, so we cannot study water droplets or how molecules structure at a water-air interface. The first part of this project will be to combine these dielectric models with the many-body DPD technique so we can study these effects and can also look at such phenomena as the effect of an electric field on a water droplet.

Secondly current methods do not allow us to investigate liquid crystals. We thus cannot model liquid crystal devices using DPD. We wish to get round this by extending the many-body DPD formalism to include the contributions of molecular orientation. We can then use this method to model devices but also to model the interface between air and a liquid crystal, which is not easy to do with other current techniques.

Finally, in order to parameterise the models for real use, it is very convenient to have a robust, accurate theory. In our previous research we have found liquid state theories, such as the hypernetted chain equation and random phase approximation, to work very well. We can thus obtain good parameters using theory rather than by running many simulations. Another aim of this project is to provide the underlying theory to describe the properties of these model fluids.

This project will be carried out in association with Dr Patrick Warren (Unilever Research), Dr Michael Seaton (Daresbury Laboratories) and Professor Ignacio Pagonabarraga (Barcelona). The student will receive training in the use of high-performance computers and will become proficient in the use and development of sophisticated liquid state theories. It is anticipated that the results of the research will have high impact both in the scientific and industrial arenas.

The successful applicant should have a strong background in mathematics and computer programming. A good background in thermodynamics and statistical mechanics would also be advantageous.

Funding Notes

The University of Manchester offers a very limited number of presidential doctoral scholarships. The competition for these is intense and only exceptional candidates stand a chance, To succeed you will need outstanding examination results (e.g. a very high first class degree) and, ideally, evidence of prizes, publications and conference presentations. If you are a UK student, there may be other possible soiurces of funding. If you are self-funded, then you are naturally most welcome to apply.

References

P. B. Warren, L. Anton, A. Yu. Vlasov and A. J. Masters. Screening properties of Gaussian electrolyte models, with application to dissipative particle dynamics, J. Chem. Phys. 138, 204907 (2013)

P. B. Warren and A. J. Masters. Phase behavior and the random phase approximation for ultra-soft restricted primitive models, J. Chem. Phys. 138, 074901 (2013)

P. B. Warren, Phys. Rev. E 68, 066702 (2003);