Support for the UKCP consortium

Lead Research Organisation: University College London
Department Name: Physics and Astronomy


Many technological advances in modern day life are dependent upon the development of new materials or better control and understanding of existing materials. Understanding the detailed properties of materials has therefore never been more important. The development of high quality computer simulation techniques has played an increasing significant role in this endeavour over recent years. The UK has been at the forefront of this new wave, and the UKCP consortium has played an important part, in both developing computer codes and algorithms, and exploiting these new advances to increase our understanding of many industrially relevant materials and processes.

The preferred mechanism for providing computational resources on HECToR is via HPC Consortia, and UKCP is onesuch, containing 19 different nodes. Each node is a different University Department and is represented by one key academic - see the "Linked Proposals" or the Track Record for a complete list of current members of UKCP. This proposal seeks computational support for a large body of research (see "Other Support") with a substantial allocation of HECToR resources and also the support of a named PDRA. The PDRA will assist with training and supporting different members of the consortium in using the principle codes used within the consortium (e.g. CASTEP), and also develop some of the new code features required to complete some of these projects.

The research described in this proposal will make significant impacts on many areas of future technology, such as the development of improved materials for battery electrodes, solar cells and hydrogen-storage materials, each of which will help the move towards zero-pollution cars in the future. Some very applied parts of the proposal will study superalloys for use in engine turbine blades, or the properties of glasses used for storing nuclear waste materials. Other parts of the proposal will study the structure of materials with high accuracy, including subtle effects like dispersion forces and quantum nuclear effects, which may lead to better materials in the future. Other projects focus on a better understanding of existing materials, such as the interaction of proteins and DNA, or the operation of ligand-gated ion channels in cells.

As part of this proposal, the researchers will have to develop new algorithms and theoretical improvements that will increase our simulation abilities, either by increasing the accuracy and reliability of calculations, or by enabling us to simulate bigger systems for longer. These will enable the next generation of simulations and further widen our computational horizons.

The research proposed does not easily fit into any of the traditional categories of 'physics' or 'chemistry' etc. Instead, the UKCP is a multi-disciplinary consortium using a common theoretical foundation to advance many different areas of materials-based science which has the potential for significant impact both in the short and long-term.


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Reilly AM (2016) Report on the sixth blind test of organic crystal structure prediction methods. in Acta crystallographica Section B, Structural science, crystal engineering and materials

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Hart M (2017) Encapsulation and Polymerization of White Phosphorus Inside Single-Wall Carbon Nanotubes. in Angewandte Chemie (International ed. in English)

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Terranova U (2013) ? Self-Consistent Field Method for Natural Anthocyanidin Dyes. in Journal of chemical theory and computation

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Smith R (2014) Hydrogen adsorption and diffusion around Si(0 0 1)/Si(1 1 0) corners in nanostructures. in Journal of physics. Condensed matter : an Institute of Physics journal

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Smith RL (2017) Alane adsorption and dissociation on the Si(0 0 1) surface. in Journal of physics. Condensed matter : an Institute of Physics journal

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Smith R (2018) Reaction paths of alane dissociation on the Si(0 0 1) surface. in Journal of physics. Condensed matter : an Institute of Physics journal

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O'Rourke C (2018) Structural properties of silicon-germanium and germanium-silicon core-shell nanowires. in Journal of physics. Condensed matter : an Institute of Physics journal

Description See Lead Organisation report for EP/K013564/1
Exploitation Route See Lead Organisation report for EP/K013564/1
Sectors Chemicals,Electronics,Energy,Environment,Manufacturing, including Industrial Biotechology

Title AIRSS 
Description Ab initio Random Structure Searching (AIRSS) is a very simple, yet powerful and highly parallel, approach to structure prediction. The concept was introduced in 2006 and its philosophy more extensively discussed in 2011. Random structures - or more precisely, random "sensible" structures - are generated and then relaxed to nearby local energy minima. Particular success has been found using density functional theory (DFT) for the energies, hence the focus on "ab initio" random structure searching. The sensible random structures are constructed so that they have reasonable densities, and atomic separations. Additionally they may embody crystallographic, chemical or prior experimental/computational knowledge. Beyond these explicit constraints the emphasis is on a broad, uniform, sampling of structure space. AIRSS has been used in a number of landmark studies in structure prediction, from the structure of SiH4 under pressure to providing the theoretical structures which are used to understand dense hydrogen (and anticipating the mixed Phase IV), incommensurate phases in aluminium under terapascal pressures, and ionic phases of ammonia. The approach naturally extends to the prediction clusters/molecules, defects in solids, interfaces and surfaces (interfaces with vacuum). The AIRSS package is tightly integrated with the CASTEP first principles total energy code. However, it is relatively straightforward to modify the scripts to use alternative codes to obtain the core functionality, and examples are provided. The AIRSS package is released under the GPL2 licence. 
Type Of Technology Software 
Year Produced 2017 
Impact It appears that researcher are routinely using AIRSS.