PhD: Nathan Schaefer
Directors: ICREA Prof. Jose Antonio Garrido, Advanced Electronic Materials and Devices Group Leader at ICN2 and Dr. Anton Guimerà, Permanent Researcher at Grupo de Aplicaciones Biomédicas at IMB-CNM, CSIC
Short Abstract: The experimental discovery of graphene marked the advent of a new research field based on two-dimensional materials, investigating their properties for applications in electronics, photonics and optoelectronics and, recently, also biomedical technology. Neurotechnology, in particular, is a subject which could strongly benefit from these new materials, as their mechanical and chemical nature allows them to form a stable, conformable interface with the brain.
The graphene solution-gated field-effect transistor (gSGFET) is one of several emerging sensing devices utilizing thin materials, and has shown great potential for brain-machine interfaces (BMIs), as it is able to record neural activity with high accuracy. The use of sensors with a transistor design was found to be beneficial for specific applications as they unveil mostly unexplored slow oscillatory activity and reduce the technologic complexity of fabricating sensor arrays with a large number of recording sites.
To develop a dense and highly accurate gSGFET cortical implant array, this thesis addresses two primary challenges. First, the geometric nature of graphene and other two-dimensional materials exposes them to degrading influences from their surroundings, resulting in high intrinsic noise which is detrimental to the quality of the neural recordings. Technological improvements to shield the gSGFET sensor from such influences and to lower the intrinsic device noise are presented. Second, the size of the connector footprint rapidly increases with the number of sensors, posing restrictions on the count and density of recording sites achievable on the array. This can be overcome by the employment of multiplexed readout schemes e.g. by integrating molybdenum disulfide field-effect transistors (MoS2-FETs) as flexible switches, which enable the combination of multiple streams of information into a single signal and would thereby overcome connectivity limitations.
Multiplexed cortical arrays of up to 256 recording sites are showcased as a first prototype towards a new generation of BMIs and a roadmap for the technology's scale-up is presented.