Literature DB >> 24123661

Visualizing lithium-ion migration pathways in battery materials.

Mette Ø Filsø1, Michael J Turner, Gerald V Gibbs, Stefan Adams, Mark A Spackman, Bo B Iversen.   

Abstract

The understanding of lithium-ion migration through the bulk crystal structure is crucial in the search for novel battery materials with improved properties for lithium-ion conduction. In this paper, procrystal calculations are introduced as a fast, intuitive way of mapping possible migration pathways, and the method is applied to a broad range of lithium-containing materials, including the well-known battery cathode materials LiCoO2 , LiMn2 O4 , and LiFePO4 . The outcome is compared with both experimental and theoretical studies, as well as the bond valence site energy approach, and the results show that the method is not only a strong, qualitative visualization tool, but also provides a quantitative measure of electron-density thresholds for migration, which are correlated with theoretically obtained activation energies. In the future, the method may be used to guide experimental and theoretical research towards materials with potentially high ionic conductivity, reducing the time spent investigating nonpromising materials with advanced theoretical methods.
Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  conducting materials; ion-migration mechanisms; lithium; materials science; procrystal analysis

Year:  2013        PMID: 24123661     DOI: 10.1002/chem.201301504

Source DB:  PubMed          Journal:  Chemistry        ISSN: 0947-6539            Impact factor:   5.236


  3 in total

Review 1.  Charge density analysis for crystal engineering.

Authors:  Anna Krawczuk; Piero Macchi
Journal:  Chem Cent J       Date:  2014-12-16       Impact factor: 4.215

2.  Low Dimensional String-like Relaxation Underpins Superionic Conduction in Fluorites and Related Structures.

Authors:  Ajay Annamareddy; Jacob Eapen
Journal:  Sci Rep       Date:  2017-03-27       Impact factor: 4.379

3.  CAVD, towards better characterization of void space for ionic transport analysis.

Authors:  Bing He; Anjiang Ye; Shuting Chi; Penghui Mi; Yunbing Ran; Liwen Zhang; Xinxin Zou; Bowei Pu; Qian Zhao; Zheyi Zou; Da Wang; Wenqing Zhang; Jingtai Zhao; Maxim Avdeev; Siqi Shi
Journal:  Sci Data       Date:  2020-05-22       Impact factor: 6.444

  3 in total

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