A Near-Isotropic Proton-Conducting Porous Graphene Oxide Membrane

A graphene oxide (GO) membrane is an ideal separator for multiple applications due to its morphology, selectivity, controllable oxidation, and high aspect ratio of the 2D nanosheet. However, the anisotropic ion conducting nature caused by its morphology is not favorable toward through-plane conductivity, which is vital for solid-state electrolytes in electrochemical devices. Here, we present a strategy to selectively enhance the through-plane proton conductivity of a GO membrane by reducing its degree of anisotropy with pore formation on the nanosheets through the sonication-assisted Fenton reaction. The obtained porous GO (pGO) membrane is a near-isotropic, proton-conducting GO membrane, showing a degree of anisotropy as low as 2.77 and 47% enhancement of through-plane proton conductivity as opposed to the pristine GO membrane at 25 °C and 100% relative humidity. The anisotropic behavior shows an Arrhenius relationship with temperature, while the water interlayer formation between nanosheets plays a pivotal role in the anisotropic behavior under different values of relative humidity (RH); that is, as low RH increases, water molecules tend to orient in a bimodal distribution clinching the nanosheets and forming a subnanometer, high-aspect-ratio, water interlayer, resulting in its peak anisotropy. Further increase in RH fills the interlayer gap, resulting in behaviors akin to near-isotropic, bulk water. Lastly, implementation of the pGO membrane, as the solid proton-conductive electrolyte, in an alcohol fuel cell sensor has been demonstrated, showcasing the excellent selectivity and response, exceptional linearity, and ethanol detection limits as low as 25 ppm. The amalgamation of excellent performance, high customizability, facile scalability, low cost, and environmental friendliness in the present method holds considerable potential for transforming anisotropic GO membranes into near-isotropic ion conductors to further membrane development and sensing applications