Neuromorphic Devices Based on Two-Dimensional Materials and Their Applications

Abstract

Neuromorphic computing, inspired by the human brain, utilizes thin 2D materials like graphene for their unique electronic properties. These materials are crucial in creating efficient, high-performance computing devices. This paper discusses the synthesis methods for 2D materials, including chemical vapor deposition and mechanical exfoliation, and their integration into neuromorphic device architectures such as transistors and memristors. The paper explores how these devices emulate synaptic behaviors and neuronal activities through charge transport mechanisms, ion migration, and the exploitation of material defects. Applications in artificial intelligence, edge computing, sensor networks, and robotics are highlighted, showcasing the potential of 2D materials to revolutionize these fields. The paper also addresses the challenges related to scalability, uniformity, and energy efficiency, and concludes by offering perspectives on future research directions in this burgeoning field. This comprehensive study underscores the significance of 2D materials in advancing neuromorphic computing, paving the way for more efficient, powerful, and brain-like artificial intelligence systems.