9. Toward the Nanoscale

  1. Aron Walsh3,
  2. Alexey A. Sokol4 and
  3. C. Richard A. Catlow5
  1. Phuti E. Ngoepe1,
  2. Rapela R. Maphanga1 and
  3. Dean C. Sayle2

Published Online: 25 APR 2013

DOI: 10.1002/9781118551462.ch9

Computational Approaches to Energy Materials

Computational Approaches to Energy Materials

How to Cite

Ngoepe, P. E., Maphanga, R. R. and Sayle, D. C. (2013) Toward the Nanoscale, in Computational Approaches to Energy Materials (eds A. Walsh, A. A. Sokol and C. R. A. Catlow), John Wiley & Sons Ltd, Oxford, UK. doi: 10.1002/9781118551462.ch9

Editor Information

  1. 3

    Department of Chemistry, University of Bath, UK

  2. 4

    Department of Chemistry, University College London, UK

  3. 5

    Department of Chemistry, University College London, UK

Author Information

  1. 1

    Materials Modelling Centre, University of Limpopo, Sovenga, South Africa

  2. 2

    Defence College of Management and Technology, Cranfield University, Shrivenham, UK

Publication History

  1. Published Online: 25 APR 2013
  2. Published Print: 14 APR 2013

ISBN Information

Print ISBN: 9781119950936

Online ISBN: 9781118551462

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Keywords:

  • global minimization (GM);
  • nanoscale;
  • quantum mechanical (QM);
  • simulation methods

Summary

In general, four main classes of technique have been employed in the current literature on nanoscaled energy materials: atomistic (static lattice), quantum mechanical (QM), global minimization (GM) and simulated amorphization and recrystallization (A+R) methods. A brief overview of two such methods, GM and simulated A+R, is given in this chapter. MnO2 seeds observed during nucleation and crystallization are discussed. The presence of the four to eight-membered ring structure alludes to similarity of structures whether spontaneously built bottom up from small clusters with a few atoms by GM or top down using A+R, which involves tens of thousands of atoms; this demonstrates agreement on predictive capabilities of evolutionary simulation methods at the nanoscale. Accordingly, at the nanoscale, the authors argue that the quenching of surface dipoles drives the evolution of particular polymorphs.