Issue 22, 2016

Computational materials design of crystalline solids

Abstract

The modelling of materials properties and processes from first principles is becoming sufficiently accurate as to facilitate the design and testing of new systems in silico. Computational materials science is both valuable and increasingly necessary for developing novel functional materials and composites that meet the requirements of next-generation technology. A range of simulation techniques are being developed and applied to problems related to materials for energy generation, storage and conversion including solar cells, nuclear reactors, batteries, fuel cells, and catalytic systems. Such techniques may combine crystal-structure prediction (global optimisation), data mining (materials informatics) and high-throughput screening with elements of machine learning. We explore the development process associated with computational materials design, from setting the requirements and descriptors to the development and testing of new materials. As a case study, we critically review progress in the fields of thermoelectrics and photovoltaics, including the simulation of lattice thermal conductivity and the search for Pb-free hybrid halide perovskites. Finally, a number of universal chemical-design principles are advanced.

Graphical abstract: Computational materials design of crystalline solids

Supplementary files

Article information

Article type
Tutorial Review
Submitted
08 nóv. 2015
First published
18 mar. 2016
This article is Open Access
Creative Commons BY license

Chem. Soc. Rev., 2016,45, 6138-6146

Computational materials design of crystalline solids

K. T. Butler, J. M. Frost, J. M. Skelton, K. L. Svane and A. Walsh, Chem. Soc. Rev., 2016, 45, 6138 DOI: 10.1039/C5CS00841G

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