Dr Joseph Nelson

Algorithms to navigate structure space

Computational structure prediction and data mining approaches are now widely used to predict crystal structure and to reveal a material's underlying properties. These approaches include random sampling, genetic algorithms, simulated annealing (and more), as well as the use of chemically sensible substitutions of elements in crystal structures contained in existing structural databases. Typically, all these techniques give rise to enormous numbers of relaxed crystal structures, each one corresponding to a local minimum in a material's potential energy surface. I am working jointly with Chris Pickard (University of Cambridge) and Kazuto Akagi (AIMR, Tohoku University) on developing techniques to use, visualize and understand ('navigate') this vast quantity of data. Examples of the tools that could be applied include the use of persistent homology, a geometrical technique originating in applied mathematics, and the use of complex atomic networks.