Few-layer graphene as an 'active' conductive additive for flexible aqueous supercapacitor electrodes

R.E. Williams, S. Sukumaran, Q. Abbas, M.R.C. Hunt

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    Abstract

    We demonstrate that few layer graphene (FLG), formed by high-shear exfoliation into an aqueous suspension, can be successfully employed as an ‘active’ conductive additive in flexible activated carbon-based aqueous electric double layer capacitor (supercapacitor) electrodes if introduced by a novel ‘vacuum infiltration’ technique. The effectiveness of the FLG can be optimised by tailoring its size distribution and loading. It is found that best performance is achieved using FLG with the broadest size distribution and, moreover, that the larger size distribution is effective over the broadest range of loading. With optimum size distribution and loading, FLG is shown to outperform a commercial carbon black conductive additive (Timcal C65). Electrodes containing 8 wt% infiltrated FLG have an equivalent series resistance (ESR) of 1.3 ± 0.4 Ω, and a specific capacitance of 142.3 ± 0.1 F g-1 over a voltage window of 1.2 V, compared with an ESR of 3 ± 1 Ω and a specific capacitance of 96.81 ± 0.02 F g-1 for equivalent electrodes produced with an optimal loading of carbon black additive. As a result, the specific energy density of electric double layer capacitors (EDLCs) produced with a vacuum infused FLG additive is demonstrated to be an average of 47 ± 3% superior to those containing carbon black measured at similar power densities. In contrast to vacuum infiltration, direct mixing of FLG suspension into the electrodes is found to be ineffective, resulting in limited improvement relative to electrodes without conductive additive, the reasons for which are discussed.
    Original languageEnglish
    Article number118744
    Number of pages8
    JournalCarbon
    Volume218
    Early online date16 Dec 2023
    DOIs
    Publication statusPublished - 31 Jan 2024

    Keywords

    • supercapacitor
    • EDLC
    • few-layer graphene
    • conductive additive

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