Abstract
The properties of LaMO 3 (M: 3d transition metal) perovskite crystals are significantly dependent on point defects, whether introduced accidentally or intentionally. The most studied defects in La-based perovskites are the oxygen vacancies and doping impurities on the La and M sites. Here, we identify that intrinsic antisite defects, the replacement of La by the transition metal, M, can be formed under M-rich and O-poor growth conditions, based on results of an accurate many-body ab initio approach. Our fixed-node diffusion Monte Carlo (FNDMC) calculations of LaMO 3 (M = Mn , Fe, and Co) find that such antisite defects can have low formation energies and are magnetized. Complementary density functional theory (DFT)-based calculations show that Mn antisite defects in LaMnO 3 may cause the p-type electronic conductivity. These features could affect spintronics, redox catalysis, and other broad applications. Our bulk validation studies establish that FNDMC reproduces the antiferromagnetic state of LaMnO 3, whereas DFT with PBE (Perdew–Burke–Ernzerhof), SCAN (strongly constrained and appropriately normed), and the LDA+U (local density approximation with Coulomb U) functionals all favor ferromagnetic states, at variance with experiment.
| Original language | English |
|---|---|
| Article number | 6703 |
| Journal | Scientific Reports |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2023 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). We would like to thank Ho Nyung Lee for a critical reading of the manuscript and for references. We would like to thank Erica Heinrich for a technical editing and related corrections. Work by T.I., K.S., J.T.K., and F.A.R. (original idea, project management, manuscript writing) was supported by the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. P.R.C.K and Y.L. (code development, analysis, manuscript contributions) were supported via the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials by Materials Sciences and Engineering Division. We acknowledge computational resources provided by the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which is a user facility of the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725, and by the Compute and Data Environment for Science (CADES) at Oak Ridge National Laboratory. We acknowledge computational resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No. DE-AC02-06CH11357. We acknowledge computational resources of the Research Center for Advanced Computing Infrastructure (RCACI) at JAIST.
| Funders | Funder number |
|---|---|
| Compute and Data Environment for Science | |
| U.S. Department of Energy | |
| Office of Science | DE-AC02-06CH11357 |
| Basic Energy Sciences | |
| Oak Ridge National Laboratory | |
| Division of Materials Sciences and Engineering | DE-AC05-00OR22725 |