MoS2Memristors Exhibiting Variable Switching Characteristics toward Biorealistic Synaptic Emulation

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Abstract
Memristors based on 2D layered materials could provide biorealistic ionic interactions and potentially enable construction of energy-efficient artificial neural networks capable of faithfully emulating neuronal interconnections in human brains. To build reliable 2D-material-based memristors suitable for constructing working neural networks, the memristive switching mechanisms in such memristors need to be systematically analyzed. Here, we present a study on the switching characteristics of the few-layer MoS2 memristors made by mechanical printing. First, two types of dc-programmed switching characteristics, termed rectification-mediated and conductance-mediated behaviors, are observed among different MoS2 memristors, which are attributed to the modulation of MoS2/metal Schottky barriers and redistribution of vacancies, respectively. We also found that an as-fabricated MoS2 memristor initially exhibits an analog pulse-programmed switching behavior, but it can be converted to a quasi-binary memristor with an abrupt switching behavior through an electrical stress process. Such a transition of switching characteristics is attributed to field-induced agglomeration of vacancies at MoS2/metal interfaces. The additional Kelvin probe force microscopy, Auger electron spectroscopy analysis, and electronic characterization results support this hypothesis. Finally, we fabricated a testing device consisting of two adjacent MoS2 memristors and demonstrated that these two memristors can be ionically coupled to each other. This device interconnection scheme could be exploited to build neural networks for emulating ionic interactions among neurons. This work advances the device physics for understanding the memristive properties of 2D-material-based memristors and serves as a critical foundation for building biorealistic neuromorphic computing systems based on such memristors.
Funding Information
  • Division of Electrical, Communications and Cyber Systems (ECCS-1452916)

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