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New methods to model water - polymer and water-membrane interactions using dissipative particle dynamics.

Project Description

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. Thus one may wish to investigate charged ions or study solvent hydration and dielectric effects. Because of this, we have been investigating new DPD models, where ions are treated as Gaussian smeared charges and polar molecules as two smeared charges connected by springs. We have found that liquid state integral equation theories, such as the hypernetted chain equation, are very good for predicting the properties of such fluids without the need for simulation. Thus we are able to optimize the properties of these fluids to suit our needs, using these theoretical methods.

The model so far, however, does not capture hydrogen bonding effects. The first step of this project will be to study a smeared charge trimer, representing the structure of a water molecule, and to see how well this model can reproduce the properties of water – both short range hydrogen bonding and long-range dielectric properties. The second step will be to further tune this model so that it can successfully model important hydrophobic interactions – e.g. the interface between water and hydrocarbon/aromatic groups. This will then permit the use of DPD to model biological systems, where both hydrophobic and hydrophilic interactions are of key importance. The interaction of a shampoo with hair comes into this category.

Sometimes, however, one needs to model an air/liquid interface and this is impossible using the DPD approach described above. A promising alternative is “many-body DPD”, which does indeed allow one to model vapour-liquid co-existence and the corresponding interface. The final part of the project will be to combine this approach with the new dielectric methodology described above, so one can then study, for example, the water-air interface and how the surfactant molecules congregate there to form thin films. Again such modelling is important in the health-care industry and for the modelling of foams.

This project will be carried out in association with Dr Patrick Warren (Unilever Research) and Dr Michael Seaton (Daresbury Laboratories). 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.


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)

How good is research at University of Manchester in Aeronautical, Mechanical, Chemical and Manufacturing Engineering?
Chemical Engineering

FTE Category A staff submitted: 33.90

Research output data provided by the Research Excellence Framework (REF)

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