skip to content

Materials Theory Group

 

AIRSS Banner

Ab Initio Random Structure Searching

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.

Contact: airss@msm.cam.ac.uk

 

Obtaining AIRSS

The AIRSS package is released under the GPL2 licence. You can download the full source code below. Note that you will require a Unix-like environment in order to build the code. Windows users can install a Linux subsystem if required. Build instructions are contained within the source:

Download current version

As well as the full source, you can access an online version of the AIRSS code which lets you try some of the AIRSS examples in-browser. Read more about this online version in the associated news item, or access it below:

Access the online version of AIRSS

 

Documentation

The AIRSS source contains a number of worked examples to assist the user in learning how to use the code. Online AIRSS documentation is also under construction at https://airss-docs.github.io/ (with thanks to James Walsh, UMass Amherst)

 

History

Earlier versions of AIRSS:

AIRSS Version 0.9.1

AIRSS Version 0.9.0

 

Latest news

Machine learning shows how hydrogen becomes a metal inside giant planets

10 September 2020

By combining machine learning and quantum mechanics, researchers have carried out simulations to discover how hydrogen becomes a metal under extreme pressures.

MSM-AIMR Joint Online Workshop 2020

8 September 2020

In the week of 24-28 August 2020, the Department of Materials Science and Metallurgy held a Joint Online Workshop with Tohoku University in Japan.

Hierarchically Structured Allotropes of Phosphorus from Data-Driven Exploration

22 June 2020

Researchers discover new elemental phosphorus structures by using 'fragments' of phosphorus as building blocks.

New academic license for CASTEP

6 March 2020

The CASTEP developers announce a new cost-free worldwide source code license to CASTEP and NMR CASTEP for academic use.

Dr Chuck Witt joins the MTG

6 March 2020

The Materials Theory Group welcomes its newest research associate, Dr Chuck Witt.

Welcome to Dr Bartomeu Monserrat

10 January 2020

The Materials Theory Group welcomes new faculty member and new group member Bartomeu Monserrat.

CASTEP: From research code to software product with Professor Chris Pickard

9 January 2020

On 22 January 2020, Chris Pickard will give a talk followed by a Q&A session on commercialising software.