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Materials Theory Group


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 for the most stable configurations of a given set of atomic building blocks, which correspond to the deepest regions of an energy landscape—the system's energy as a function of the relative positions of its atoms. To explore these landscapes efficiently, it is important to understand their topologies. However, they exist in spaces with very large numbers of dimensions, making them difficult to visualise. SHEAP uses dimensionality reduction through manifold learning to effectively visualise the distribution of stable structures across a high-dimensional energy landscape.


Latest news

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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!

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

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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.

Postdoc in High Temperature Conventional Superconductivity

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Applications are invited for a postdoctoral research position with Professor Chris Pickard at the University of Cambridge. Recent advances in computational methods have raised the prospect of the in silico design of high...

Visualising potential energy surfaces using dimensionality reduction

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Computational structure prediction has emerged as a highly successful approach to the discovery of new materials. Candidate structures are created by constructing the most stable configurations that can be adopted by a given...

The elements of life under pressure

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First-principles structure prediction sheds light on high-pressure compounds formed from carbon, hydrogen, nitrogen and oxygen.