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Materials Theory Group



MSci Imperial College London
PhD Harvard University


Interface Structure Prediction

Structure prediction of bulk materials is now routinely performed, however the field of predicting the atomic structure of interfaces and other defects is still in its infancy. A detailed understanding of and ability to predict the atomic structure of interfaces is however of crucial importance for many technologies. Interfaces are very hard to predict due to the complicated geometries, crystal orientations and possible non-stoichiometric conditions involved and provide a major challenge to structure prediction. We have shown that the ab initio random structure searching (AIRSS) method can be used to predict the structure of interfaces. Our approach relies on generating random structures in the vicinity of the interface and relaxing them within the framework of density functional theory. The method is simple, requiring only a small set of parameters that can be easily connected to the physics of the system of interest, and efficient, allowing for high-throughput first-principles calculations on modern parallel architectures. We have studied several grain boundary defects in technologically important materials such as grain boundaries in graphene, the prototypical two-dimensional material and grain boundaries in transition metal oxides, such as SrTiO3. 

Relevant publications:

G Schusteritsch, C J Pickard, "Predicting interface structures: From SrTiO3 to graphene", Physical Review B, 90(3), Article No. 035424 (2014) DOI: 10.1103/PhysRevB.90.035424


Structure Prediction of Clusters

Metallic nanoparticles are of great importance in many chemistry applications, in particular for catalysis. By defining an appropriate randomization region, ab inito random structure searching can be used to efficiently search for the structure of small clusters. As part of the TOUCAN project, I have been studying various types of clusters, in particular focusing on approaches to study bi- and multi-metallic nanomaterials (nanoalloys). We consider both clusters in vacuum and how deposition on surfaces can affect the structure and properties of nanoalloy cluster. 


Two-Dimensional Materials 

I have been working on applying the ab inito random structure searching approach to the problem of finding the crystal structures of two-dimensional material. We have for instance used AIRSS to find the stable structures of two-dimensional ice. Our results revealed several models for 2D ice, including a hexagonal, a Cairo tiling pentagonal, a square and a rhombic structure.

Many two-dimensional materials exhibit interesting novel physics and enhanced physical properties that are expected to find application in future technologies. I am considering a wide range of materials and areas of applications: For instance we have found that the single-layered form of Hittorf’s or violet phosphorus – hittorfene - is predicted to be a wide band gap material with a very high mobility.

Relevant publications:

J. Chen, G. Schusteritsch, C.J. Pickard, C.G. Salzmann, and A. Michaelides, "Two Dimensional Ice from First Principles: Structures and Phase Transitions", Phys. Rev. Lett. 116, 025501 – Published 13 January 2016 - DOI: 10.1103/PhysRevLett.116.025501 

Georg Schusteritsch, Martin Uhrin and Chris J. Pickard, "Single-Layered Hittorf’s Phosphorus: A Wide-Bandgap High Mobility 2D Material", Nano Lett. 16 (5), (2016) pp 2975–2980 DOI: 10.1021/acs.nanolett.5b05068



Postdoctoral Research Associate
Dr Georg  Schusteritsch

Contact Details

+44 (0)1223 334335