Genetic algorithm prediction of two-dimensional group-IV dioxides for dielectrics

Arunima K. Singh, Benjamin C. Revard, Rohit Ramanathan, Michael Ashton, Francesca Tavazza, Richard G. Hennig

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Two-dimensional (2D) materials present a new class of materials whose structures and properties can differ from their bulk counterparts. We perform a genetic algorithm structure search using density-functional theory to identify low-energy structures of 2D group-IV dioxides AO2 (A=Si, Ge, Sn, Pb). We find that 2D SiO2 is most stable in the experimentally determined bi-tetrahedral structure, while 2D SnO2 and PbO2 are most stable in the 1T structure. For 2D GeO2, the genetic algorithm finds a new low-energy 2D structure with monoclinic symmetry. Each system exhibits 2D structures with formation energies ranging from 26 to 151 meV/atom, below those of certain already synthesized 2D materials. The phonon spectra confirm their dynamic stability. Using the HSE06 hybrid functional, we determine that the 2D dioxides are insulators or semiconductors, with a direct band gap of 7.2 eV at Γ for 2D SiO2, and indirect band gaps of 4.8-2.7 eV for the other dioxides. To guide future applications of these 2D materials in nanoelectronic devices, we determine their band-edge alignment with graphene, phosphorene, and single-layer BN and MoS2. An assessment of the dielectric properties and electrochemical stability of the 2D group-IV dioxides shows that 2D GeO2 and SnO2 are particularly promising candidates for gate oxides and 2D SnO2 also as a protective layer in heterostructure nanoelectronic devices.

Original languageEnglish (US)
Article number155426
JournalPhysical Review B
Issue number15
StatePublished - Apr 18 2017
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics


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