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Assessing cathode property prediction via exchange-correlation functionals with and without long-range dispersion
Olivia Y Long1,2, Gopalakrishnan Sai Gautam3,4, Emily A Carter3,5
1Department of Physics, Princeton University, Princeton, New Jersey 08544, USA.
Physical Chemistry Chemical Physics : PCCP
|October 28, 2021
Summary
The strongly constrained and appropriately normed (SCAN) functional offers more accurate predictions for layered transition-metal oxides used in lithium-ion batteries compared to the Perdew-Burke-Ernzerhof (PBE) functional, especially when including dispersion corrections.
Area of Science:
- Materials Science
- Computational Chemistry
- Electrochemistry
Background:
- Layered lithium transition-metal oxides (TMOs) are critical positive electrode materials for lithium-ion batteries.
- Accurate theoretical prediction of their properties is essential for designing next-generation energy storage solutions.
- Density functional theory (DFT) is a key computational tool, but the choice of exchange-correlation functional impacts accuracy.
Purpose of the Study:
- To benchmark the accuracy of various DFT functionals for calculating properties of layered TMOs and their de-lithiated forms.
- To compare the performance of the SCAN functional against PBE and their Hubbard-U and dispersion-corrected variants.
- To assess the suitability of these functionals for predicting interlayer spacings, voltages, stabilities, and band gaps relevant to battery performance.
Main Methods:
- Calculated interlayer spacings, topotactic voltages, thermodynamic stabilities, and band gaps for layered TMOs using DFT.
- Employed eight exchange-correlation treatments: PBE, SCAN, PBE+U, SCAN+U, PBE+D, SCAN+D, PBE+U+D, SCAN+U+D.
- Included van der Waals interactions using rVV10 for SCAN and DFT-D3 for PBE.
Main Results:
- SCAN-based functionals predicted smaller interlayer spacings and, due to underestimating MO2 stability, larger voltages than PBE-based ones.
- Dispersion corrections significantly impacted PBE predictions more than SCAN, suggesting SCAN captures some dispersion effects inherently.
- Both SCAN and PBE provided qualitatively similar band gap predictions, with no significant quantitative improvement from SCAN.
Conclusions:
- SCAN-based functionals are expected to provide more accurate predictions for most TMO properties than PBE-based functionals.
- SCAN's theoretical foundation and observed trends in interlayer spacings, voltages, and band gaps support its superior predictive power.
- This work provides guidance on selecting appropriate DFT functionals for accurate materials design in lithium-ion battery research.
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