Computational Materials Science2022,Vol.2029.DOI:10.1016/j.commatsci.2021.110948

2D Ni0.25Mn0.75O2: A high-performance cathode for multivalent ion batteries

Liepinya, Diana Shepard, Robert Smeu, Manuel
Computational Materials Science2022,Vol.2029.DOI:10.1016/j.commatsci.2021.110948

2D Ni0.25Mn0.75O2: A high-performance cathode for multivalent ion batteries

Liepinya, Diana 1Shepard, Robert 1Smeu, Manuel1
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作者信息

  • 1. SUNY Binghamton
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Abstract

Although Li-ion batteries have driven portable energy storage in recent decades, there is increasing concern about their safety, cost, and abundance of constituents. Multivalent ion batteries (MVIBs) have the potential to remedy these issues, but they are limited by the currently known MVIB cathodes, which fail to deliver unanimously favorable voltage, energy density, and diffusion kinetics. We used density functional theory (DFT) to model the performance of Li, Na, Mg, Ca, and Al ions when paired with 2D Ni0.25Mn0.75O2 , a novel cathode that uses increased layer separation to improve on the kinetics of its 3D analog. Our calculations yielded maximum voltages of 3.38 V for Na and 2.7 V for Ca, outperforming 2D NaxMnO2 and NaxNiO2. Diffusion barriers for Li, Na, and Ca are below 300 meV, comparable to existing battery technology and the endpoint 2D cathodes; meanwhile, Mg and Al have prohibitively high diffusion barriers, implying their incompatibility with this cathode. Lastly, density of states calculations and Bader charge analysis show that the cathode becomes conducting following ion adsorption, which is necessary for high-rate performance. 2D Ni0.25Mn0.75O2 maintains performance seen with other 2D transition metal oxides while increasing cathode conductivity, indicating that it is a promising candidate for experimental investigation with Li, Na, and Ca ions.

Key words

Density functional theory/2D Nickel manganese oxide/Mono-/di-/trivalent ions/Secondary battery/INITIO MOLECULAR-DYNAMICS/METAL/TRANSITION/DENSITY/MNO2/INTERCALATION/ALUMINUM/PHASE/OXIDE

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量4
参考文献量46
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