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Macromolecular Diffusion in Crowded Colloidal Suspensions

  • Full or part time
  • Application Deadline
    Sunday, March 31, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Highlight.
The present research has two key goals: (i) understanding the effect of order on the diffusion of macromolecules in crowded colloidal suspensions, and (ii) developing a new computational method to investigate the dynamics of these systems under the most general conditions, which can include transitory unsteady states and density inhomogeneities. We are interested in employing a simulation technique, originally conceived in our group and known as Dynamic Monte Carlo (DMC), to unravel the macromolecular diffusion in colloidal suspensions exhibiting ordered crowding and whose dynamics fully unfolds over time scales that are especially challenging for traditional simulation strategies.

Background
Colloids consist of particles dispersed in a solvent, usually water. They are ubiquitous in Nature (blood is a colloid) and in everyday life (milk is a colloid). Many relevant biological systems are colloids, often characterised by a significantly high density. The cytoplasm of living cells, for instance, is an especially crowded colloid, comprising organelles immersed in a fluid (cytosol) where lipids, proteins and other macromolecules diffuse. The diffusion of macromolecules within the cell and across the cellular membrane regulates most of the cellular processes and is therefore crucial for life.

Although macromolecular diffusion in crowded media has been the object of an intense research, very little attention has been given to understand the impact of ordering on its dynamics. The above-mentioned cellular membrane, for instance, consists of bi-layers of highly aligned lipid molecules and display a significant internal organisation. A relevant degree of order is also observed in the intracellular organelles, precisely in the Golgi apparatus and endoplasmic reticulum, through which the proteins must diffuse. Ordering is therefore an important ingredient to gain a full insight into the dynamics of macromolecular diffusion in crowded environments and should not a priori be disregarded.

It is however a challenge to investigate macromolecular diffusion in highly dense and ordered systems as it is expected to be influenced by the dynamics of host particles, which generally unfolds over at least microseconds and micrometers. Consequently, simplified models that disregard unnecessary chemical details and efficient simulation techniques that speed up calculations are required. Over the last years, our group has designed an efficient simulation technique (DMC) to investigate the dynamics of dense colloids. This method was shown to be significantly more efficient than other simulation techniques that are employed to describe the dynamics of colloids.

Aims.
The aims of this research are essentially two: (A1) investigating the diffusion of macromolecules in crowded and ordered colloidal suspensions, and (A2) developing the DMC simulation technique to efficiently simulate the behaviour of these systems under the most general conditions. The PhD student will focus on A1, while a PDRA will focus on A2. However, the two researchers will work closely and exchange information on a daily basis.

The knowledge resulting from A1 is of crucial importance in a number of interdisciplinary processes that are regulated by the timescale of macromolecular diffusion through constricted regions. The knowledge resulting from A2 will allow us to apply efficient computer simulation techniques to investigate the dynamics of macromolecular diffusion in the long-time regime and in the most general case of space inhomogeneities and/or transitory unsteady states. Space- and time-dependent fluctuations are very frequent events in colloidal suspensions and deeply determine their equilibrium status and dynamics.

Methodology
The PhD student will perform DMC simulations to investigate macromolecular diffusion in crowded colloids showing a degree of ordering. Systems of anisotropic particles are especially attractive as they provide a wide spectrum of packing architectures and thus the basis to gain a full understanding of macromolecular diffusion in ordered media. The main objective of this PhD project is providing a more complete insight into the physics of macromolecular diffusion under complex, but more realistic, conditions, including unsteady-state processes, which alter the thermodynamic equilibrium over time, and inhomogeneous systems, whose physical properties, such as density and ordering, are space-dependent. In Year 1, the student will investigate the diffusion of macromolecules, initially modelled as spherical tracers, in liquid crystals of board-like particles. In Year 2, the student will study the effect of an external field forcing the reorientation of the board-like particles and influencing the trajectory of macromolecules. In Year 3, spatial homogeneities (e.g. density gradients resulting from phase coexistence) will be investigated. This study will promote an understanding of macromolecular diffusion in especially complex environments whose properties are often time and space-dependent.

Funding Notes

This research project is funded by the Leverhulme Trust Research Project Grant RPG-2018-415.

Applicants should have a first honours degree (or equivalent if non-UK) in Physics, Chemical Engineering, Physical Chemistry or related subjects. Proven experience in molecular simulation and modelling or programming is highly desirable.

The starting date of the project is 1st May 2019.

References

A. Patti, A. Cuetos, Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study, Phys. Rev. E 86, 011403, 2012

A. Cuetos, A. Patti, Equivalence of Brownian Dynamics and Dynamic Monte Carlo Simulations in Binary Mixtures of Colloidal Fluids, Phys. Rev. E 92, 022302, 2015

A. Cuetos, M. Dennison, A. Masters, A. Patti, Phase Behaviour of Hard Board-like Particles, Soft Matter 13, 4270, 2017

A. Patti, A. Cuetos, Monte Carlo simulation of binary mixtures of hard colloidal cuboids, Mol. Simul. 44, 516, 2018

D. Corbett, A. Cuetos, M. Dennison, A. Patti, Dynamic Monte Carlo algorithm for out-of- equilibrium processes in colloidal dispersions, Phys. Chem. Chem. Phys. 20, 15118, 2018

A. Cuetos, N. Morillo, and A. Patti, Fickian Yet Non-Gaussian Diffusion is not Ubiquitous in Soft Matter, Physical Review E, 98, 042129, 2018

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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