Details of Grant 

EPSRC Reference:	EP/J010057/1
Title:	Collaborative Computational Project on Computational Electronic Structure of Condensed Matter
Principal Investigator:	Payne, Professor MC
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	Physics
Organisation:	University of Cambridge
Scheme:	Standard Research
Starts:	15 March 2012	Ends:	14 September 2015	Value (£):	382,592
EPSRC Research Topic Classifications:	Condensed Matter Physics High Performance Computing
EPSRC Industrial Sector Classifications:	R&D
Related Grants:
Panel History:	Panel Date Panel Name Outcome 23 Aug 2011 Collaborative Computational Projects Announced
Summary on Grant Application Form
It was claimed in the late 1920's that quantum mechanics chould predict every property of any molecule or material - essentially that quantum mechanics explained the whole of physics, chemistry, materials science and biology. However, it took over 50 years before computers became powerful enough to solve the equations of quantum mechanics to begin to prove that this claim was correct. These first tests were only for atoms or very small molecules that contained only 2 or 3 electrons or for crystalline materials that contained only 1 or 2 atoms in basic crystal unit cell. Over the last 30 years the combination of more powerful computers combined with better theoretical and numerical methods has brought us to the point where we can routinely compute a vast range of properties of molecules and materials. For instance we can now determine the most stable crystal structures for a particular combination of atoms even when this in not known experimentally. In addition we can calculate vibrational frequencies, activation energies of chemical reactions, surface energies and many more properties for systems containing hundreds of atoms. However, computers continue to get more powerful. We will now be able to use our powerful quantum mechanical computational methods on these increasingluy powerful computers to generate huge amounts of information about a vast number of materials. These will be both known materials and, much more interestingly, materials that have not yet been made. Using these vast databases we will, in the future, be able to choose a material for a particular application by identifying candidates in the databases. We also expect that the data in our databases will allow us to help design the fabrication route that will create not just the required materials but entire devices. Thus in creating the infrastructure to create and provide access to these databases we are taking the first step on the route to computional materials and device design. Many products we use every day are designed using computers and it has been found that replacing real design by virtual design on a computer can reduce the development time for a product, make it higher quality and/or safer (this has been particularly true in the case of cars) and thus produce a significant socio-economic benefit.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Further Information:
Organisation Website:	http://www.cam.ac.uk