PolyGraph—Biocompatible and Flexible Graphene Composites for Microneedle-Based Neural Interfacing Devices

Brain-computer interfaces (BCIs), specialized electrodes capable of delivering electrical stimulation to and recording signals from the brain, have been used as novel treatments for epilepsy, Parkinson’s, and other neurological disorders. Looking beyond medical treatment to biological enhancement, BCIs may allow the integration of prosthetic and communication technologies with neural signaling, making their development an area of investigation with the potential for significant medical and societal impact. However, they are faced with the challenge of balancing biocompatibility, degradation, and neuroinflammation with electrical performance, device design, and stiffness. Optimizing the many facets of these devices involves trade-offs, for example between neurocompatibility and electroconductivity, which compromises the performance of existing BCIs. Therefore, the hypothesis of this study is that by developing a multi-phase material which combines highly electroconductive graphene with a biocompatible polymer, a conductive, non-inflammatory, and flexible microneedle-based neural interface could be developed. To achieve this, polymer-graphene composites were fabricated, and a novel fabrication method was used to manufacture flexible, electrically isolated microneedle arrays capable of delivering electrical stimulation to neuronal cells - key outcomes for successful BCIs.<br/>The graphene (Gr) formulation was first optimized, with polyvinylpyrrolidone (PVP) found to be the optimal stabilizer for liquid phase exfoliation of thin graphene nanosheets with high conductivity (&gt;1000 S/m), yield (&gt;1g) and hydrophilicity. The culture of mouse motor neuron cells in medium containing PVPGr suspensions showed robust proliferation and healthy metabolic activity, indicative of excellent biocompatibility. PVPGr was then further characterized using SEM, AFM and Raman spectroscopy, to establish its optical and morphological properties, before being combined with polycaprolactone (PCL) to form conductive and processable graphene-polymer composites (PolyGraph). Electrode materials require optimal electrical performance, so PolyGraph was enhanced by NaOH treatment to increase specific surface area, followed by coating with a thin AuPd layer to reduce charge transfer resistance. This brought the charge storage capacity (~8.66 mC/cm²) and charge transfer resistance (~6.3 Ω) into line with requirements for BCI devices. Finally, the stiffness and biocompatibility of PolyGraph were assessed and compared to traditional electrode materials. PolyGraph yielded a tensile modulus of ~92 MPa, several orders of magnitude lower than metals, and human iPSC-derived neurons grown on the surface of the material exhibited robust axonal extension across the surface. With the graphene and composite materials optimized, electrical stimulation and the fabrication of microelectrode arrays was then investigated. To this end, freestanding electrodes fabricated using custom microneedle molds and by leveraging the material’s 3D printability were connected using a bioresorbable collagen-based backing to form a flexible device. This design aims to minimize foreign body response on implantation, while maintaining electrical performance. Finally, to demonstrate the capacity of these PolyGraph microelectrode arrays to interface with neurons, flat PolyGraph electrodes were used to stimulate human neurons in 3D culture in a biomimetic hyaluronic acid-based hydrogel.<br/>These data demonstrate the development of biocompatible, flexible and versatile graphene composites for the fabrication of BCI devices, with the capacity to effect neural stimulation and recording, while overcoming key limitations of existing microelectrode designs. Beyond microelectrode applications, PVPGr and PolyGraph composites also have the potential to act as highly conductive, biocompatible materials across a diverse range of applications, such as tissue engineering, implantable electronics, and wearable devices.