Topological Frustration in Graphene Nanoflakes: Magnetic Order and Spin Logic Devices

TL;DR

This paper classifies finite graphene nanoflakes based on topological frustration, revealing how their magnetic properties can be harnessed to design ultra-fast, room-temperature spintronic logic gates with low error rates.

Contribution

It introduces a rigorous classification scheme for graphene nanoflakes and proposes their use as fundamental spintronic logic gates, supported by ab initio calculations.

Findings

Nanoflakes can exhibit large net spin or antiferromagnetic coupling.

Proposed structures can function as NOR and NAND logic gates.

Devices can operate at room temperature with low error rates.

Abstract

Magnetic order in graphene-related structures can arise from size effects or from topological frustration. We introduce a rigorous classification scheme for the types of finite graphene structures (nano-flakes) which lead to large net spin or to antiferromagnetic coupling between groups of electron spins. Based on this scheme, we propose specific examples of structures that can serve as the fundamental (NOR and NAND) logic gates for the design of high-density ultra-fast spintronic devices. We demonstrate, using ab initio electronic structure calculations, that these gates can in principle operate at room temperature with very low and correctable error rates.