Support for the UKCP consortium
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Physics and Astronomy
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
Publications
Terranova U
(2013)
? Self-Consistent Field Method for Natural Anthocyanidin Dyes.
in Journal of chemical theory and computation
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
Murata K
(2017)
Atomic layer doping of Mn magnetic impurities from surface chains at a Ge/Si hetero-interface.
in Nanoscale
Bowler D
(2019)
Building bridges: matching density functional theory with experiment
in Contemporary Physics
Pickard C
(2016)
Carbon Nitride Frameworks and Dense Crystalline Polymorphs
Pickard C
(2016)
Carbon nitride frameworks and dense crystalline polymorphs
in Physical Review B
Cruz-Cabeza A
(2016)
Crystal structure prediction: are we there yet?
in Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials
Martinez-Canales M
(2017)
Dirac cones in Two-dimensional Borane
Martinez-Canales M
(2017)
Dirac cones in two-dimensional borane
in Physical Review B
Murata K
(2017)
Dopant activation mechanism of Bi wire-d-doping into Si crystal, investigated with wavelength dispersive fluorescence x-ray absorption fine structure and density functional theory.
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. |
| URL | https://www.mtg.msm.cam.ac.uk/Codes/AIRSS |