Van der Waals materials-based floating gate memory for neuromorphic computing

Abstract

With the advent of the “Big Data Era”, improving data storage density and computation speed has become more and more urgent due to the rapid growth in different types of data. Flash memory with a floating gate (FG) structure is attracting great attention owing to its advantages of miniaturization, low power consumption and reliable data storage, which is very effective in solving the problems of large data capacity and high integration density. Meanwhile, the FG memory with charge storage principle can simulate synaptic plasticity perfectly, breaking the traditional von Neumann computing architecture and can be used as an artificial synapse for neuromorphic computations inspired by the human brain. Among many candidate materials for manufacturing devices, van der Waals (vdW) materials have attracted widespread attention due to their atomic thickness, high mobility, and sustainable miniaturization properties. Owing to the arbitrary stacking ability, vdW heterostructure combines rich physics and potential 3D integration, opening up various possibilities for new functional integrated devices with low power consumption and flexible applications. This paper provides a comprehensive review of memory devices based on vdW materials with FG structure, including the working principles and typical structures of FG structure devices, with a focus on the introduction of various high-performance FG memories and their versatile applications in neuromorphic computing. Finally, the challenges of neuromorphic devices based on FG structures are also discussed. This review will shed light on the design and fabrication of vdW material-based memory devices with FG engineering, helping to promote the development of practical and promising neuromorphic computing.