Colloidal suspensions are two-phase systems of droplets or particles dispersed in a continuous medium that find wide use in the formulation industry as paints, pharmaceutics, cosmetics and food products. This ubiquitous impact has fuelled an increasing interest in their properties, especially since experimental techniques to make ad-hoc building blocks have become available. The possibility of manufacturing intriguing particle shapes has significantly enriched the variety of the existing phases and unveiled the existence of many exotic phases, so far almost exclusively predicted by theory or computer simulation.
Molecular simulation has significantly contributed to unveil the effects of particle shape on the phase behaviour of colloids, often offering key guidance and preliminary insight to experiments. However, most of the computational work has so far prevalently focussed on their phase behaviour, while dynamics and rheology have been almost completely limited to systems of rods and platelets. The aim of this PhD is to study the dynamics and rheology of colloidal suspensions of cuboidal colloidal particles in the bulk and in a spectrum of confined environments. Under specific conditions, these particles can orient and form very intriguing liquid crystalline phases, whose dynamical and rheological properties are still far from being completely understood.
In particular, we will apply a technique, referred to as microrheology (MR), that reveals the rheology of a soft material by studying the dynamics of a colloidal probe-particle (or tracer) either freely diffusing in the host medium (passive MR) or subjected to external forces (active MR). To this end, we will employ our in-house-developed Dynamic Monte Carlo simulation technique, which can quantitatively reproduce the Brownian dynamics of colloids under the most general conditions, including transitory unsteady states and phase coexistence [1-4], and very recently applied to study the dynamics of cuboids and curved rods in uniaxial and twist-bend nematic liquid crystals [5-6].
Applicants should have or expect to achieve a first-class honours degree in Chemical Engineering, Materials Science, Physics, Chemistry or related disciplines. A familiarity with stochastic molecular simulation techniques (Monte Carlo) and experience programming is especially welcome.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
All appointments are made on merit.
Continue with Facebook
