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Elucidating the nature of grain boundary resistance in lithium lanthanum titanate

  • Adam R. Symington
  • , Marco Molinari
  • , James A. Dawson
  • , Joel M. Statham
  • , John Purton
  • , Pieremanuele Canepa
  • , Stephen C. Parker
  • University of Huddersfield
  • Newcastle University
  • Science and Technology Facilities Council
  • National University of Singapore

Research output: Contribution to journalArticlepeer-review

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Abstract

Solid electrolytes for all-solid-state batteries are generating remarkable research interest as a means to improve the safety, stability and performance of rechargeable batteries. Solid electrolytes are often polycrystalline and the effect that grain boundaries have on the material properties is often not fully characterised. Here, we present a comprehensive molecular dynamics study that quantifies the effect of grain boundaries on Li-ion transport in perovskite Li3xLa(2/3)−xTiO3(0 <x< 0.16) (LLTO). Our results predict that grain boundaries hinder Li-ion conductivity by 1 to 2 orders of magnitude compared to the bulk. We attribute the poor Li-ion conductivity of the grain boundaries to significant structural alterations at the grain boundaries. Our detailed analysis provides important insight into the influence of grain boundary structure on transport of Li-ions in solid electrolyte materials.

Original languageEnglish
Pages (from-to)6487-6498
Number of pages12
JournalJournal of Materials Chemistry A
Volume9
Issue number10
Early online date29 Jan 2021
DOIs
Publication statusPublished - 14 Mar 2021

Bibliographical note

Funding Information:
Computations were run on Balena HPC facility at the University of Bath and the ARCHER UK National Supercomputing Service via our membership of the High-End Computing Materials Chemistry Consortium (HEC MCC) funded by the EPSRC (EP/ L000202, EP/R029431). We are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by the EPSRC (EP/P020194/1). P. C. acknowledges funding from the National Research Foundation under his NRF Fellowship NRFF12-2020-0012 and the ANR-NRF NRF2019-NRF-ANR073 Na-MASTER. The Monte Carlo calculations used computing resources provided by STFC Scientic Computing Department's SCARF cluster.

Funding

Computations were run on Balena HPC facility at the University of Bath and the ARCHER UK National Supercomputing Service via our membership of the High-End Computing Materials Chemistry Consortium (HEC MCC) funded by the EPSRC (EP/ L000202, EP/R029431). We are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by the EPSRC (EP/P020194/1). P. C. acknowledges funding from the National Research Foundation under his NRF Fellowship NRFF12-2020-0012 and the ANR-NRF NRF2019-NRF-ANR073 Na-MASTER. The Monte Carlo calculations used computing resources provided by STFC Scientic Computing Department's SCARF cluster.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

ASJC Scopus subject areas

  • General Chemistry
  • Renewable Energy, Sustainability and the Environment
  • General Materials Science

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