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New directions for random search

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DNM - The mathematical design of new materials

Genuinely new knowledge and scientific insight can be obtained about matter by combining random numbers with reliable and efficient first principles methods. Diverse ensembles of initial structures can be generated, and structurally optimised. The resulting low energy structures are candidates for stable, and metastable, phases and/or defects that might be experimentally realised. This, of course, depends on a sufficiently broad and thorough sampling of configuration space. Algorithms which attempt to learn from (computational) experience are necessarily sequential, and correlated. A purely random strategy, as employed by Ab Initio Random Structure Searching (AIRSS),[1,2] is entirely parallel, and a natural fit to the high throughput computation (HTC) paradigm. The absence of correlation between the independent random samples ensures that it is possible to estimate when a sufficiently dense sampling has been achieved (or at least, has not been achieved). Challenging cases can be tackled by designing the initial random structures so that they focus the search in regions of configuration space that are anticipated to yield success. The design of these random “sensible” structures will be explored, along with some new directions which promise to accelerate random search,[3] and recent applications to materials.
[1] C. J. Pickard, and R. J. Needs, Phys. Rev. Lett., 97 (4), 045504 (2006) & Journal of Physics-Condensed
Matter, 23(5), 053201 (2011)
[2] Released under the GPL2 license:
[3] C. J. Pickard, “Hyperspatial optimization of structures”, Phys. Rev. B, 99, 054102 (2019)
*C.J.P. is supported by the Royal Society through a Royal Society Wolfson Research Merit award
and the EPSRC through Grants No. EP/P022596/1.
Chris Pickard is the Sir Alan Cottrell Professor of Materials Science in the Department of Materials
Science and Metallurgy, University of Cambridge. Previously he was Professor of Physics, University
College London (2009-2015), and Reader in Physics, University of St Andrews (2006-2008). He
has held both EPSRC Advanced and Leadership Research Fellowships, and is currently a Royal
Society Wolfson Research Merit Award holder (2015). He is a lead developer of the widely used
CASTEP code, and introduced both the GIPAW approach to the prediction of magnetic resonance
parameters and Ab Initio Random Structure Searching (AIRSS). In 2015 he won the Rayleigh Medal
and Prize of the Institute of Physics, awarded for distinguished research in theoretical, mathematical
or computational physics.
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