Dimensional control of defect dynamics in perovskite oxide superlattices

Isaac Bredeson, Lipeng Zhang, P. R.C. Kent, Valentino R. Cooper, Haixuan Xu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Point defects play a critical role in the structural, physical, and interfacial properties of perovskite oxide superlattices. However, understanding of the fundamental properties of point defects in superlattices, especially their transport properties, is rather limited. Here, we report predictions of the stability and dynamics of oxygen vacancies in SrTiO3/PbTiO3 oxide superlattices using first-principles calculations in combination with the kinetic Monte Carlo method. By varying the stacking period, i.e., changing of n in nSTO/nPTO, we discover a crossover from three-dimensional diffusion to primarily two-dimensional planar diffusion. Such planar diffusion may lead to novel designs of ionic conductors. We show that the dominant vacancy position may vary in the superlattices, depending on the superlattice structure and stacking period, contradicting the common assumption that point defects reside at interfaces. Moreover, we predict a significant increase in room-temperature ionic conductivity for 3STO/3PTO relative to the bulk phases. Considering the variety of cations that can be accommodated in perovskite superlattices and the potential mismatch of spin, charge, and orbitals at the interfaces, this paper identifies a pathway to control defect dynamics for technological applications.

Original languageEnglish
Article number035401
JournalPhysical Review Materials
Volume2
Issue number3
DOIs
StatePublished - Mar 8 2018

Funding

This research is sponsored by The University of Tennessee (UT) Science Alliance Joint Directed Research and Development Program (L.Z., I.B., and H.X.) and the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (V.R.C. and P.R.C.K.), managed by UT-Battelle, LLC, for the U.S. Department of Energy (DOE). This paper has been authored by UT-Battelle, LLC, under Contract No. DE-AC05- 00OR22725 with the DOE. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the DOE under Contract No. DE-AC02-05CH11231 and the National Institute for Computational Sciences at UT under Contract No. UT-TENN0112. This research is sponsored by The University of Tennessee (UT) Science Alliance Joint Directed Research and Development Program (L.Z., I.B., and H.X.) and the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (V.R.C. and P.R.C.K.), managed by UT-Battelle, LLC, for the U.S. Department of Energy (DOE). This paper has been authored by UT-Battelle, LLC, under Contract No. DE-AC05- 00OR22725 with the DOE. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the DOE under Contract No. DE-AC02-05CH11231 and the National Institute for Computational Sciences at UT under Contract No. UT-TENN0112.

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