Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides
Abstract
Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles–based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCoO2 and LiNiO2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA + U), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3d and O 2p orbitals as compared to GGA, resulting inmore »
- Authors:
-
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials Science and Engineering
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials Science and Engineering; Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Engineering; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division
- Publication Date:
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Org.:
- USDOE; National Research Foundation of Korea (NRF)
- OSTI Identifier:
- 1505755
- Alternate Identifier(s):
- OSTI ID: 1214339
- Grant/Contract Number:
- FG02-96ER45571
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Physical Review. B, Condensed Matter and Materials Physics
- Additional Journal Information:
- Journal Volume: 92; Journal Issue: 11; Journal ID: ISSN 1098-0121
- Publisher:
- American Physical Society (APS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE
Citation Formats
Seo, Dong-Hwa, Urban, Alexander, and Ceder, Gerbrand. Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides. United States: N. p., 2015.
Web. doi:10.1103/physrevb.92.115118.
Seo, Dong-Hwa, Urban, Alexander, & Ceder, Gerbrand. Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides. United States. https://doi.org/10.1103/physrevb.92.115118
Seo, Dong-Hwa, Urban, Alexander, and Ceder, Gerbrand. Tue .
"Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides". United States. https://doi.org/10.1103/physrevb.92.115118. https://www.osti.gov/servlets/purl/1505755.
@article{osti_1505755,
title = {Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides},
author = {Seo, Dong-Hwa and Urban, Alexander and Ceder, Gerbrand},
abstractNote = {Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles–based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCoO2 and LiNiO2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA + U), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3d and O 2p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCoO2. We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α = 0.0) and HSE06 (α = 0.25) calculations. Our results also show that G0 W0 @ GGA + U band gaps of TM oxides ( M O , M = Mn , Co , Ni ) and LiCoO2 agree well with experimental references, suggesting that G0 W0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been reported.},
doi = {10.1103/physrevb.92.115118},
journal = {Physical Review. B, Condensed Matter and Materials Physics},
number = 11,
volume = 92,
place = {United States},
year = {Tue Sep 08 00:00:00 EDT 2015},
month = {Tue Sep 08 00:00:00 EDT 2015}
}
Web of Science
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