Brain-inspired computing: can 2D materials bridge the gap between biological and artificial neural networks?

Abstract

This modern era of technology with data flood actively demands the development of excellent non-volatile storage (NVS) and computing devices, which can overcome the memory bottleneck of the traditional von-Neumann structure-based devices. Memristors, as potent and promising NVS devices, can efficiently mimic the biological synapse of a neuron, and therefore, have been immensely explored in recent years. In this context, the emergence and development of two-dimensional layered materials (2DLMs) have led to a multifold acceleration in the advancement of memory devices, owing to their atomically thin structures and superior electronic properties, in comparison to those of the conventional metal oxides. However, unlocking the full potential of 2DLMs in neuromorphic applications demands creative approaches. Here, we discuss in depth the challenges and limitations associated with these neuromorphic devices and finally conclude by outlining future perspectives and directions for this evolving field of next-generation electronics.