EPCC explores Soft Condensed Matter
Posted: 11 Nov 2013 | 10:55
Today computer simulation is firmly established as the third pillar of science beside theory and experiment. As part of its research activities on modelling and large-scale simulation of soft condensed matter, EPCC maintains a long-standing collaboration with the Institute for Condensed Matter and Complex Systems (ICMCS) at the University of Edinburgh and the Centre for Computational Science at University College London.
A recent article featuring this collaboration was highlighted on the cover of the RSC journal 'Soft Matter'. The article presents first insights into the complex bulk flow behaviour of a specific kind of liquid crystal, so-called Blue Phases. They constitute a particularly fascinating example of liquid-crystalline phases, featuring a network of defect lines where for topological reasons the local order is strongly suppressed. This gives Blue Phases unique optical properties, making them very attractive for novel photonic materials and optical switch gear.
Liquid crystals are states of matter with properties between those of a simple Newtonian liquid and a solid crystal. At high temperature or low-volume fraction, most liquid crystals have an isotropic phase, but undergo an ordering transition to anisotropic phases with positional and/or orientational order upon cooling or densification. Today, they are well-known for their technological applications. Nonetheless they play also an important role for living systems as they combine structural with functional properties.
It seems logical to find out more about these promising materials, however some of their properties are notoriously difficult to study. This is particularly true for their flow behaviour. But advances in supercomputing have dramatically increased our capabilities during the last two decades, enabling us to study problems that were previously inaccessible. This progress has been paralleled by the development of sophisticated models of complex fluids, which allow us to understand and predict their dynamical behaviour. It appears viable to try to gain understanding and to provide experimental guidance by tapping into these resources.
The project drew on EPSRC grants (EP/E045316/1, EP/I034661/1), the national high performance computing facilities HECToR and BlueGene/Q, and on EPCC’s lattice Boltzmann application ‘Ludwig’ for simulating complex fluids. The code, which was authored by EPCC’s Dr Kevin Stratford and colleagues, had already been used in a number of substantial contributions to soft matter science. The lattice Boltzmann method - named after the Austrian physicist and founder of Statistical Mechanics Ludwig Boltzmann (1844-1906) - allows to model hydrodynamic flow in complex geometries, composite materials and suspensions. The method's superior scaling properties allows the dynamics of complex fluids to be simulated and quantitatively predicted at unprecedented length scales.
Everything flows, but how?
It was possible to identify a number of distinct flow regimes in both cubic Blue Phases, Blue Phase I and II. Some feature very regular flow patterns with oscillatory stress response, whereas others seem to be more prone to ‘rheochaos’. The latter forms an instance of deterministic chaos where, according to the discoverer of the butterfly effect Edward Lorenz, the present determines the future, but the approximate present does not approximately determine the future.
The different flow behaviour of both Blue Phases is intimately related to the topology of their order structure and exists only in anisotropic liquids such as liquid crystals. The practical implications of these findings are numerous, reaching from manufacturing and processing aspects to micro- and opto-fluidic applications based on Blue Phases and other liquid-crystalline materials. Although direct experimental evidence to support these results is currently not available, the ability to predict and understand the structure and dynamical behaviour of complex liquid-crystalline systems by means of careful computer simulation has been already demonstrated. The team hopes that such experiments will be inspired by this work.
Soft Matter, 2013, 9, 10243-10256, DOI: 10.1039/C3SM50228G