Abstract

The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather than a transient one. Two-dimensional (2D) materials, with atomically thin geometries, electrically tunable carrier densities, and large optical responses, offer a unified platform on which to build devices that compute where they store, process events rather than clock cycles, and shift workload into the optical domain. This perspective surveys progress along three converging thrusts, graphene and graphene nanoribbon transistors as scalable channel materials, oxide and 2D-integrated memristors for in-memory analog compute, and silicon-compatible 2D photonic and thermal-emitter structures for optical computing primitives. Our central argument is that the 2D-materials community has spent a decade producing record devices, and the next decade will be decided by who first integrates three of them on a single semiconductor wafer.

Abstract

The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather than a transient one. Two-dimensional (2D) materials, with atomically thin geometries, electrically tunable carrier densities, and large optical responses, offer a unified platform on which to build devices that compute where they store, process events rather than clock cycles, and shift workload into the optical domain. This perspective surveys progress along three converging thrusts, graphene and graphene nanoribbon transistors as scalable channel materials, oxide and 2D-integrated memristors for in-memory analog compute, and silicon-compatible 2D photonic and thermal-emitter structures for optical computing primitives. Our central argument is that the 2D-materials community has spent a decade producing record devices, and the next decade will be decided by who first integrates three of them on a single semiconductor wafer.

Abstract

The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather than a transient one. Two-dimensional (2D) materials, with atomically thin geometries, electrically tunable carrier densities, and large optical responses, offer a unified platform on which to build devices that compute where they store, process events rather than clock cycles, and shift workload into the optical domain. This perspective surveys progress along three converging thrusts, graphene and graphene nanoribbon transistors as scalable channel materials, oxide and 2D-integrated memristors for in-memory analog compute, and silicon-compatible 2D photonic and thermal-emitter structures for optical computing primitives. Our central argument is that the 2D-materials community has spent a decade producing record devices, and the next decade will be decided by who first integrates three of them on a single semiconductor wafer.

Abstract

The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather than a transient one. Two-dimensional (2D) materials, with atomically thin geometries, electrically tunable carrier densities, and large optical responses, offer a unified platform on which to build devices that compute where they store, process events rather than clock cycles, and shift workload into the optical domain. This perspective surveys progress along three converging thrusts, graphene and graphene nanoribbon transistors as scalable channel materials, oxide and 2D-integrated memristors for in-memory analog compute, and silicon-compatible 2D photonic and thermal-emitter structures for optical computing primitives. Our central argument is that the 2D-materials community has spent a decade producing record devices, and the next decade will be decided by who first integrates three of them on a single semiconductor wafer.