Jump to main content
Jump to site search


Structure prediction of aluminum nitride combining data mining and quantum mechanics

Abstract

Aluminum nitride (AlN) is a compound with wide technological applications from optics to electronics. At ambient pressure and temperature AlN exhibits a hexagonal wurtzite type of structure, while the zinc blende (ZnS) type of structure is found in very thin films. At high pressures, a first-order phase transformation from the wurtzite structure to a rock salt type structure has been observed. This study covers the experimentally observed modifications of AlN, investigates their relations and searches for new possible modifications. Therefore, data mining of over 140.000 structure candidates has been performed, followed by local optimizations on ab initio level with Hartree-Fock, LDA, and B3LYP functionals. Finally, twelve structure candidates have proven to be the most promising ones. These include novel metastable AlN polytypes, and the 5-5-type as a possible high pressure candidate of AlN.

Back to tab navigation

Supplementary files

Publication details

The article was received on 02 Jun 2017, accepted on 01 Aug 2017 and first published on 01 Aug 2017


Article type: Paper
DOI: 10.1039/C7CE01039G
Citation: CrystEngComm, 2017, Accepted Manuscript
  •   Request permissions

    Structure prediction of aluminum nitride combining data mining and quantum mechanics

    J. Zagorac, D. Zagorac, M. Rosic, J. C. Schon and B. Matovic, CrystEngComm, 2017, Accepted Manuscript , DOI: 10.1039/C7CE01039G

Search articles by author

Spotlight

Advertisements