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
Monserrat B
(2016)
Hexagonal structure of phase III of solid hydrogen
Martinez-Canales M
(2017)
Dirac cones in Two-dimensional Borane
Monserrat B
(2016)
Hexagonal structure of phase III of solid hydrogen
O'Rourke C
(2014)
Intrinsic Oxygen Vacancy and Extrinsic Aluminum Dopant Interplay: A Route to the Restoration of Defective TiO 2
in The Journal of Physical Chemistry C
O'Rourke C
(2015)
Linear scaling density matrix real time TDDFT: Propagator unitarity and matrix truncation.
in The Journal of chemical physics
Novello AM
(2017)
Stripe and Short Range Order in the Charge Density Wave of 1T-Cu_{x}TiSe_{2}.
in Physical review letters
Brázdová V
(2017)
Exact location of dopants below the Si(001):H surface from scanning tunneling microscopy and density functional theory
in Physical Review B
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 |