Abstract
NiO is a canonical Mott (or charge-transfer) insulator and, as such, is notoriously difficult to describe using density functional theory (DFT)-based electronic structure methods. Doped Mott insulators such as NiO are of interest for various applications but rigorous theoretical descriptions are lacking. Here, we use quantum Monte Carlo methods, which very accurately include electron-electron interactions, to examine energetics, charge structures, and spin structures of NiO with various point defects, such as vacancies and substitutional doping with potassium. The formation energy of a potassium dopant is significantly lower than that of a Ni vacancy, making potassium an attractive monovalent dopant for NiO. We compare our results with DFT results that include an on-site Hubbard U (DFT+U) to account for correlations and find relatively large discrepancies for defect formation energies as well as for charge and spin redistributions in the presence of point defects. Beyond fitting to a single property, it is unlikely that single-parameter tuning of the DFT+U will be able to obtain accurate accounts of complex properties in these materials. Responses that depend in subtle and complex ways on ground-state properties, such as charge and spin densities, are likely to contain quantitative and qualitative errors.
Original language | English |
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Article number | 073603 |
Journal | Physical Review Materials |
Volume | 1 |
Issue number | 7 |
DOIs | |
State | Published - Dec 28 2017 |
Funding
We thank Luke Shulenburger (Sandia National Laboratory) for fruitful discussions. This work was supported by the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC02-06CH11357. This research also used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC05-00OR22725. 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 US Department of Energy under Contract No. DE-AC02-05CH11231.