Materials Theory Group
Se Hun is a PDRA in the MTG in the Department of Materials Science & Metallurgy.
His research interests have been focused on fundamental understanding of structure-property relationships and reaction mechanisms for energy storage materials using multi-scale simulation approaches. His current research with Prof. Chris Pickard focuses on the computational design and characterization of cathode materials and interfaces for next generation lithium batteries.
Personal website: https://sites.google.com/view/sehunjoo/home
Key publications:
See Google Scholar for an up-to-date list
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...
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...
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
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...
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.
Postdoc in High Temperature Conventional Superconductivity
5 January 2022
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
25 November 2021
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...
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