Structure prediction of crystals, surfaces and nanoparticles
Scott M. Woodley, Graeme M. Day, C. Richard A. Catlow
2020Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences57 citationsDOIOpen Access PDF
Abstract
We review the current techniques used in the prediction of crystal structures and their surfaces and of the structures of nanoparticles. The main classes of search algorithm and energy function are summarized, and we discuss the growing role of methods based on machine learning. We illustrate the current status of the field with examples taken from metallic, inorganic and organic systems. This article is part of a discussion meeting issue ‘Dynamic in situ microscopy relating structure and function’.
Topics & Concepts
NanoparticleField (mathematics)Computer scienceFunction (biology)NanotechnologyCurrent (fluid)Materials sciencePhysicsMathematicsThermodynamicsPure mathematicsBiologyEvolutionary biologyMachine Learning in Materials ScienceX-ray Diffraction in Crystallographynanoparticles nucleation surface interactions