Quantifying the Effect of Electronic Conductivity on the Rate Performance of Nanocomposite Battery Electrodes

Ruiyuan Tian, Nolito Alcala, Stephen J.K. O'Neill, Dominik V. Horvath, João Coelho, Aideen J. Griffin, Yan Zhang, Valeria Nicolosi, Colm O'Dwyer, Jonathan N. Coleman

Research output: Contribution to journalArticlepeer-review

84 Scopus citations

Abstract

While it is well-known that the electronic conductivity of electrodes has a critical impact on rate performance in batteries, this relationship has been quantified only by computer simulations. Here we investigate the relationship between electrode electronic conductivity and rate performance in a model cathode system of lithium-nickel-manganese-cobalt-oxide (NMC) filled with various quantities of carbon black, single-walled carbon nanotubes, and graphene. We find extreme conductivity anisotropy and significant differences in the dependence of conductivity on mass fraction among the different fillers. Fitting capacity versus rate curves yielded the characteristic time associated with charge/discharge. This parameter increased linearly with the inverse of the out-of-plane electronic conductivity, with all data points falling on the same master curve. Using a simple mechanistic model for the characteristic time, we develop an equation that matches the experimental data almost perfectly with no adjustable parameters. This implies that increasing the electrode conductivity improves the rate performance by decreasing the RC charging time of the electrode and shows rate performance to be optimized for any electrode once σOOP > 1 S/m, a condition achieved by including <1 wt % single-walled carbon nanotubes in the electrode.

Original languageEnglish
Pages (from-to)2966-2974
Number of pages9
JournalACS Applied Energy Materials
Volume3
Issue number3
DOIs
StatePublished - 23 Mar 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 American Chemical Society.

Funding

The authors acknowledge the SFI-funded AMBER research centre (SFI/12/RC/2278) and Nokia-Bell Laboratories for support. J.N.C. thanks Science Foundation Ireland (SFI, 11/PI/1087) and the Graphene Flagship (grant agreement no. 785219) for funding. C.O.D. acknowledges SFI under grants 14/IA/2581 and 15/TIDA/2893 and the SmartVista project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under the grant agreement 825114.

FundersFunder number
Horizon 2020 Framework Programme825114, 785219
Science Foundation Ireland15/TIDA/2893, 11/PI/1087, 14/IA/2581

    Keywords

    • analytic model
    • anode
    • cathode
    • electrical limitations
    • rate limitations

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