Graphene-based Flexible Electrode Array with Nanowires and PEDOT Improving Neural Recordings

Abstract

Neural electrode array have been used to exchange electrical signals to neurons in the brain for decades. In this respect, the electrode-tissue interface plays an important role in neural recordings and stimulating. For small tissue damage and high selective of signals, smaller electrode size is required. However, there is a trade-off between electrode size and impedance of electrode-brain interface. As electrodes size is smaller, the impedance is sharply increased. Therefore, there is a major challenge to reducing electrode size while retaining electrode functionality. Furthermore, the mechanical mismatch between stiff electrodes and soft tissues causes reactive tissue responses. It is considered that reactive tissue response to electrode array should be minimized for long-term reliability to record neural signals. Flexible electrode design can be one of the solution without degradation under dynamic motion constantly. In this thesis, new probe designs are suggested and its electrical characteristics are studied. A Graphene-based flexible electrode array with nanowires and poly(3,4-ethylenedioxythiophene) PEDOT on the flexible substrate was fabricated. ZnO nanowires were used in a pillar structure, which expanded effective surface area to decrease dramatically electrode impedance. Furthermore, metallic nanowires were coated with PEDOT to enhance charge storage capacity and to record both electronic and ionic current. Graphene, which has high electrical conductivity and flexibility, is a good candidate as interconnects. The neural electrode array on flexible polyimide film enables to reduce mechanical mismatch for its long-term performance in comparison with electrodes fabricated on silicon. Due to a low impedance, a flexibility, and a low noise of the neural probe system, high signal-to-noise ratio (SNR) was achieved at in vitro and in vivo brain signal recordings. Therefore, the neural probe can be employed to various brain-electrical interface systems with high performances. ⓒ 2016 DGIST