2D materials-based 3D integration for neuromorphic hardware

Abstract

Abstract Neuromorphic hardware enables energy-efficient computing, which is essential for a sustainable system. Recently, significant progress has been reported in neuromorphic hardware based on two-dimensional materials. However, traditional planar-integrated architectures still suffer from high energy consumption. This review systematically explores recent advances in the three-dimensional integration of two-dimensional material-based neuromorphic hardware to address these challenges. The materials, process, device physics, array, and integration levels are discussed, highlighting challenges and perspectives.