Projects per year
Abstract
Fast ion conducting garnet materials have been identified as promising electrolytes for all solid-state batteries. However, reliable synthetic routes to materials with fully elucidated cation site occupancies where an enhancement in lithium conductivity is observed remains a challenge. Ca-Incorporation is developed here as a promising approach to enhance the ionic conductivity of garnet-type Li7−xLa3Zr2−xTaxO12 phases. Here we present a new sol–gel synthetic strategy as a facile route to the preparation of materials of a desired stoichiometry optimized for Li+ conductivity. We have found that the ionic conductivity of Li6.4La3Zr1.4Ta0.6O12 is increased by a factor of four by the addition of 0.2 mol of Ca per formula unit. Ca is incorporated in the garnet lattice where it has no effect on the sinterability of the material and is predominately located at the La sites. We anticipate that the ease of our synthetic route and the phases presented here represents a starting point for the further realization of solid state electrolyte compositions with similarly high Li+ conductivities using this methodology.
Original language | English |
---|---|
Pages (from-to) | 9415-9419 |
Number of pages | 5 |
Journal | Dalton Transactions |
Volume | 46 |
Issue number | 29 |
Early online date | 3 Jul 2017 |
DOIs | |
Publication status | Published - 7 Aug 2017 |
Keywords
- fast ion conducting
- electrolytes
Fingerprint
Dive into the research topics of 'Enhancement of the lithium ion conductivity of Ta-doped Li7La3Zr2O12 by incorporation of calcium'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Design and high throughput microwave synthesis of Li-ion battery materials
Cussen, E.
EPSRC (Engineering and Physical Sciences Research Council)
1/10/15 → 30/09/19
Project: Research
Datasets
-
Enhancement of the lithium ion conductivity of Ta-doped Li7La3Zr2O12 by incorporation of calcium
Cussen, E. (Creator), Corr, S. (Creator) & El-Shinawi, H. (Creator), University of Glasgow, 2017
DOI: 10.5525/gla.researchdata.435
Dataset