Two-Terminal MoS2 Memristor and the Homogeneous Integration with a MoS2 Transistor for Neural Networks

Memristors are promising candidates for constructingneural networks.However, their dissimilar working mechanism to that of the addressingtransistors can result in a scaling mismatch, which may hinder efficientintegration. Here, we demonstrate two-terminal MoS2 memristorsthat work with a charge-based mechanism similar to that in transistors,which enables the homogeneous integration with MoS2 transistorsto realize one-transistor-one-memristor addressable cells forassembling programmable networks. The homogenously integrated cellsare implemented in a 2 x 2 network array to demonstrate the enabledaddressability and programmability. The potential for assembling ascalable network is evaluated in a simulated neural network usingobtained realistic device parameters, which achieves over 91% patternrecognition accuracy. This study also reveals a generic mechanismand strategy that can be applied to other semiconducting devices forthe engineering and homogeneous integration of memristive systems.

Automated summary

Research demonstrates the construction of programmable networks using two-terminal MoS2 memristors. These memristors work with a charge-based mechanism similar to transistors, allowing for homogeneous integration with MoS2 transistors to realize one-transistor-one-memristor addressable cells.