Abstract
Fast cationic conduction is necessary for a number of solid-state technologies and is particularly critical for solid-state batteries as solid electrolytes are typically poor conductors. This article illustrates the concept of low-dimensional networked (low-DN) anti-perovskite via first-principles computations and shows that superionicity (i.e. the conductivity is above 1 mS cm−1 at room temperature) can be achieved by lowering the dimensionality of the connected octahedra of the anti-perovskite. In particular, we use the Li–O–Cl model system and study the diffusion of Li in 3DN-Li3OCl, 2DN-Li4OCl2, 1DN-Li5OCl3, and 0DN-Li6OCl4. We find that the lower the dimensionality, the lower the Li migration barriers and the higher the diffusion coefficients are. We attribute this improved ionic conduction to the decreased size of the bottlenecks and the softening of the rotation modes of the octahedra in the structure. To further explore the concept of low-DN anti-perovskites, we screen 256 model materials in the I-VI-VII group chemical space by computing the phase stability and bandgap of 3DN-X3BA, 2DN-X4BA2, 1DN-X5BA3, and 0DN-X6BA4 (X = Li, Na, K, Rb; B = O, S, Se, Te; and A = F, Cl, Br, I). The calculations suggest that 20% of the structures might be synthesized and a number of them possess reasonable cationic migration barriers (<400 meV). This study puts forward a new principle for designing solid superionic conductors by lowering the dimensionality of the primitive structural units.
| Original language | English |
|---|---|
| Pages (from-to) | 146-152 |
| Number of pages | 7 |
| Journal | Energy Storage Materials |
| Volume | 28 |
| DOIs | |
| Publication status | Published - Jun 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Elsevier B.V.
Keywords
- Density functional theory
- Lattice softening
- Solid state batteries
- Superionic conductors
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Dive into the research topics of 'Superionic conduction in low-dimensional-networked anti-perovskites'. Together they form a unique fingerprint.Projects
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Chemically and electrochemically driven nanoparticle egress from A-site-deficient perovskites: A computational and experimental study of nanoparticle growth
CIUCCI, F. (PI) & SHAO, Z. (CoI)
1/01/18 → 31/12/20
Project: Research
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Ba segregation in La-substituted BaFeO3: in-situ and ex-situ characterization and computational modeling
CIUCCI, F. (PI) & JUNG, W. C. (CoI)
1/01/17 → 31/12/19
Project: Research
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