Ultrathin\nBioelectrode Array with Improved Electrochemical\nPerformance for Electrophysiological Sensing and Modulation

To achieve high accuracy and effectiveness\nin sensing and modulating\nneural activity, efficient charge-transfer biointerfaces and a high\nspatiotemporal resolution are required. Ultrathin bioelectrode arrays\nexhibiting mechanical compliance with biological tissues offer such\nbiointerfaces. However, their thinness often leads to a lack of mechano-electrical\nstability or sufficiently high electrochemical capacitance, thus deteriorating\ntheir overall performance. Here, we report ultrathin (∼115\nnm) bioelectrode arrays that simultaneously enable ultraconformability,\nmechano-electrical stability and high electrochemical performance.\nThese arrays show high opto-electrical conductivity (2060 S cm<sup>–1</sup>@88% transparency), mechanical stretchability (110%\nstrain), and excellent electrochemical properties (24.5 mC cm<sup>–2</sup> charge storage capacity and 3.5 times lower interfacial\nimpedance than commercial electrodes). The improved mechano-electrical\nand electrochemical performance is attributed to the synergistic interactions\nwithin the poly(3,4-ethylenedioxythiophene) sulfonate (PEDOT:PSS)/graphene\noxide (GO) interpenetrating network (PGIN), where π–π\nand hydrogen bonding interactions improve conductive pathways between\nPEDOT chains and enhance the charge-transfer mobility. This ultrathin\nbioelectrode is compatible with photolithography processing and provides\nspatiotemporally precise signal mapping capabilities for sensing and\nmodulating neuromuscular activity. By capturing weak multichannel\nfacial electromyography signals and applying machine learning algorithms,\nwe achieve high accuracy in silent speech recognition. Moreover, the\nhigh transparency of the bioelectrode allows simultaneous recording\nof electroencephalography (EEG) and functional near-infrared spectroscopy\n(fNIRS) signals, facilitating dual-mode brain activity analysis with\nboth high temporal and high spatial resolution.