Collaborative Computational Project on Computational Electronic Structure of Condensed Matter

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.

The whole of our flagship project and many of the Core Support functions are aimed initially at the academic community to carry out the relevant research and development in order to provide 'Proof of Principle' for the various elements and stages of the project. However, once such 'Proof of Principle' has been demonstrated we intend to ensure that our work moves into an industrial context. Thus we foresee a number of possible commercial impacts of our work as follows:

Once academic researchers have proved the effectiveness of simple descriptors for identifying useful materials systems we would expect that this approach would be adopted very rapidly by industry. We will enable this process to occur rapidly and smoothly by ensuring that there are no barriers (such as software licencing restrictions) to commercial use of the database tools we develop. If there is industrial demand for these database tools to be supported by a company then we will work with Cambridge Enterprise to enable this. This could be by licensing the software to a company that wishes to sell and support it or by starting a company to do this.

Daresbury is highly experienced in selling database services. If there is commercial demand for access to the ab initio databases that are created in this and associated projects we shall ask them to provide this service. In this case we shall play an active role in developing charging policies and negotiating terms and conditions with other researchers who wish to make their ab initio databases available through the Daresbury portal.

We expect that there will be a demand for ab initio databases to be assessed for the quality of the data before commercial users pay to access the data. If this proves to be the case then we will, again with Cambridge Enterprise, take steps to create a commercial organisation to do this.

The largest potential impacts of this work, however, are designing, and finding efficient fabrication routes for, new materials, nanostructures and devices which can address the vast range of challenges confronting us such as energy generation, clean chemistry, extending the lifetimes of components, etc.. This will not be achieved within the present project but the move into the information rich age of ab initio data is a critical first step towards these goals which will have an immense economic and societal benefit.