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Research Data for paper: Explosive percolation yields highly conductive nanocomposites

dataset
posted on 18.11.2022, 09:39 authored by Matthew LargeMatthew Large, Sean OgilvieSean Ogilvie

Data for paper published in Nature Communications 11/11/2022

This dataset comprises all numerical results used in the plotted figures of the paper entitled "Explosive percolation yields highly conductive nanocomposites". The data are given in a single Excel workbook, with each figure panel supplied in a separate sheet: the sheets are labelled according to the figure panel in the main text of the paper. The data are in x-y format, with column headings giving the axis labels/quantities from the figure along with the units.


Abstract

Explosive percolation is an experimentally-elusive phenomenon where network connectivity coincides with onset of an additional modification of the system; materials with correlated localisation of percolating particles and emergent conductive paths can realise sharp transitions and high conductivities characteristic of the explosively-grown network. Nanocomposites present a structurally- and chemically-varied playground to realise explosive percolation in practically-applicable systems but this is yet to be exploited by design. Herein, we demonstrate composites of graphene oxide and synthetic polymer latex which form segregated networks, leading to low percolation threshold and localisation of conductive pathways. In situ reduction of the graphene oxide at temperatures of <150 °C drives chemical modification of the polymer matrix to produce species with phenolic groups, which are known crosslinking agents. This leads to conductivities exceeding those of dense-packed networks of reduced graphene oxide, illustrating the potential of explosive percolation by design to realise low-loading composites with dramatically-enhanced electrical transport properties. 



Funding

Graphene-based nanomaterials for touchscreen technologies: Comprehension, Commerce and Communication

European Commission

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Sussex EPSRC Capital Award in Support of Early Career Researchers

Engineering and Physical Sciences Research Council

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Spanish MCIN/AEI PID2019-104272RB-C51/AEI/10.13039/501100011033

Government of Aragon (DGA) " Grupos Consolidados" T03-20R

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