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Materials Theory Group

Read more at: Castep


CASTEP is a leading code based on planewave-pseudopotential density functional theory. CASTEP can calculate a plethora of properties from first-principles, including energies, vibrational properties (such as infra-red and Raman spectra), electronic response properties, NMR parameters and more. A...

Read more at: AIRSS


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...

Read more at: EDDP


Ephemeral Data Derived Potentials The ddp package contains a suite of tools to construct and test data derived interatomic potentials. They were originally designed to be used with the a irss first principles structure prediction package. Ab initio random structure searching (AIRSS) can be used to...

Read more at: GIPAW


GIPAW GIPAW (Gauge Including Projector Augmented Waves) is a DFT based method to calculate magnetic resonance properties, exploiting the full translational symmetry of crystals. The use of pseudopotentials and plane waves provides an excellent balance of speed and accuracy.

Read more at: Optados


For high quality theoretical DOS, Projected-DOS, Joint-DOS, Optics and core-loss spectroscopy.

Read more at: SHEAP


sheap-small.png Stochastic Hyperspace Embedding And Projection Stochastic Hyperspace Embedding And Projection ( SHEAP ) is a dimensionality reduction method designed for visualising potential energy surfaces. Computational structure prediction can assist the discovery of new materials. One searches...

Latest news

Fast and easy exploration of crystal properties using machine-learned Ephemeral Data-derived Potentials

12 January 2024

Machine learning is quickly gaining prominence in the field of computational materials science. In the Materials Theory Group, we develop so-called ‘machine learned interatomic potentials’ (MLIPs), which can describe the...

Structure and colour in nitrogen-doped lutetium hydride

19 December 2023

Superconducting materials have a wide range of applications - from efficient power transmission to the advanced electromagnetics used in MRI machines - due to their loss-free conductivity. Current practical superconductors...

Quantum-induced hydrogen hopping in high-temperature superconducting lanthanum polyhydride

14 April 2023

Figure caption : Quantum effects are essential for hydrogen to dynamically explore different configurations. On the left, we see how the hydrogen atoms cover much larger distances at all temperatures when quantum effects are...

Flat water and ice

26 September 2022

Figure Caption : Pentagonal ice – a two-dimensional form of ice predicted to form when water is squeezed between graphene sheets. Water can be found trapped in nanoscale cavities, for example in biological membranes, or in...

Congratulations Ben Shires!

2 August 2022

Ben completed his PhD viva last week, covering his work on SHEAP , and he will soon be Dr Shires. Congratulations! shires.jpg

Quicker Crystals

14 July 2022

First-principles structure prediction has enabled the computational discovery of materials with extreme, or exotic properties. For example, the dense hydrides, which following computational searches have been found to...

New carbonates uncovered

7 January 2022

A study by Joseph Nelson and Chris Pickard of the Department of Materials Science and Metallurgy, University of Cambridge and the AIMR, Tohoku University, uses structure prediction to exhaustively explore the Ti-C-O and Al-C-O ternary systems.