Dr. Christopher Race
Research Area Lead: Modelling and Simulation
Chris Race is a Royal Society University Research Fellow and leads the Atomistic Simulation of Materials group within the Department of Materials at the University of Manchester. His group uses the tools of atomistic simulation to investigate the behaviour of a variety of materials and material evolution processes.
Chris joined the University of Manchester in April 2013 as a Dalton Research Fellow within the Dalton Nuclear Institute and the School of Materials. Before coming to Manchester he spent three years in the Department of Computational Materials Design of the Max Planck Institute for Iron Research (Eisenforschung) (MPIE) in Dusseldorf Germany, latterly as an Alexander von Humboldt Research Fellow. He completed his PhD in 2010, in the Department of Physics, Imperial College London, under the supervision of Adrian Sutton and Matthew Foulkes. His thesis – “The modelling of radiation damage in metals using Ehrenfest dynamics“- was published in the Springer Theses Series and won the 2011 Winton Capital Prize for the best PhD Thesis in Physics. Chris obtained First Class undergraduate degrees (BA and MSci) in Natural Sciences from Cambridge University in 1998.
Chris is a physicist by training and a materials scientist by inclination: attracted to materials science by the links it draws between the behaviour of real materials – things we experience and use in our everyday macroscopic lives – and what happens in the microscopic world of atoms and electrons. His research is focussed on the fundamental properties and behaviour of grain boundaries in polycrystalline materials and on the degradation of materials in demanding environments. In the latter category, recent and current projects have tackled problems such as precipitate embrittlement of reactor pressure vessel steels, stress corrosion cracking of aluminium alloys for aerospace applications, and a wide variety of phenomena in zirconium alloy nuclear fuel cladding tubes. The group uses a broad range of modelling techniques: in particular density functional theory and classical molecular dynamics. Chris is particularly interested in finding ways that modelling and experiment can work together to improve results and is also developing several projects looking at applying modern data science and image analysis methods to materials science problems.
