Graphene is an emerging nano-material that has garnered immense research interest due to its exotic electrical properties. It is believed to be a potential candidate for post-Si nanoelectronics due to high carrier mobility and extreme scalability. Recently, a new graphene nanoribbon crossbar (xGNR) device was proposed which exhibits negative differential resistance (NDR). In this paper, we present an approach to realize multistate memories, enabled by these graphene crossbar devices.
As semiconductor scaling leads to high-density nanoscale computing fabrics, reconfigurable computing shows promise due to design flexibility, post-manufacturing programmability and fault-tolerance. Traditional CMOS FPGA fabrics have order of magnitude inefficiencies in power, performance and density due to emulated logic and interconnect reconfigurability with look-up tables. This calls for new paradigms enabled by emerging nano-materials, devices and physical phenomena.