Details of Grant 

EPSRC Reference:	EP/G004765/1
Title:	DEFECTS IN FRUSTRATED SYTEMS
Principal Investigator:	Branford, Dr WR
Other Investigators:
Researcher Co-Investigators:
Project Partners:	London Centre for Nanotechnology
Department:	Physics
Organisation:	Imperial College London
Scheme:	Career Acceleration Fellowship
Starts:	01 October 2008	Ends:	31 March 2014	Value (£):	969,795
EPSRC Research Topic Classifications:	Materials Synthesis & Growth
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:	Panel Date Panel Name Outcome 26 Jun 2008 Fellowship Allocation Panel Meeting Announced 10 Jun 2008 Fellowships 2008 Interviews - Panel B Deferred
Summary on Grant Application Form
In a complex system made up of many smaller units, each element will interact with all of its neighbours, and the system tries to arrange itself so that the most favourable bond is formed with each neighbour. However, sometimes the neighbours have requirements that are mutually incompatible and a compromise must be found. If this is the case we describe the system as being frustrated. Frustration occurs widely in nature and is thought to be critical to our understanding of such questions as how do our brains work? and how do proteins fold? The frustrated biological systems described are so complex and so important that the science of frustration has become a major research area and there is great demand for simpler model systems where the interaction strength can be tuned, the model system size can be varied, defects can be introduced in a controlled manner and individual elements can be manipulated, removed or their individual state recorded. In such an ideal system one could unite theory and experiment and begin to understand the underlying physics within this complexity. Magnetic frustration has proved to be the most successful area for finding model systems. Traditionally these were magnetic crystals prepared by solid-state chemistry. However it has recently been shown that it is possible to use nanotechnology to make arrays of magnetic bars sufficiently small and sufficiently close together that the magnetic interactions between them becomes very significant, and that novel geometries can be designed where the magnetic interactions cannot all be satisfied. This development opens up broad new avenues of research in model frustrated systems. In solid-state chemistry one is limited by nature in the geometrical arrangements that are possible, whereas with nanotechnology any pattern that will tessellate can be fabricated into an array, on any length-scale down to the minimum feature size of the lithography. Here I propose to study such ideal systems that are based on frustrated magnetic nanostructures. Our experience from frustrated magnetic chemical structures tells us that triangles and hexagons are the building blocks that favour magnetic frustration. The initial work was done on arrays of magnetic bars that were isolated from one another, but I plan to focus on electrically continuous lattices, such as the hexagonal honeycomb structure so that electrical current can pass through it. The electrical properties of magnetic materials are sensitive to the magnetic structure and so this gives a direct probe of the frustrated structure and one can study its dynamic response to changes in temperature and magnetic field. Magnetic force microscopy (MFM) and scanning Hall probe imaging will be used to image the magnetic structure during these experiments. These in-situ measurements will allow the change in electrical response to be correlated directly with the change in magnetic structure, and will provide important information of the nature of the coupling between the magnetic and electrical properties of ferromagnetic metals, and the role of topology, which is currently very important for new spin-based electronics or spintronics technology. In addition to improving knowledge of diverse other fields, the magnetic arrays that I will make are exciting in their own right. Their unusual and sensitive response to magnetic fields might be useful in sensors. Furthermore the strong coupling between all the elements, and the fact that the magnetic state of individual elements can be both written (changed by applying a magnetic field) and read, means they could potentially be used for novel types of computation, often described as neural networks because they work more like the brain than like a conventional computer.
Key Findings
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