Thermally Driven Multilevel Non-Volatile Memory with Monolayer MoS2 for Brain-Inspired Artificial Learning

Thedemands of modern electronic components require advanced computingplatforms for efficient information processing to realize in-memoryoperations with a high density of data storage capabilities towarddeveloping alternatives to von Neumann architectures. Herein, we demonstratethe multifunctionality of monolayer MoS2 memtransistors,which can be used as a high-geared intrinsic transistor at room temperature;however, at a high temperature (>350 K), they exhibit synapticmultilevelmemory operations. The temperature-dependent memory mechanism is governedby interfacial physics, which solely depends on the gate field modulatedion dynamics and charge transfer at the MoS2/dielectricinterface. We have proposed a non-volatile memory application usinga single Field Effect Transistor (FET) device where thermal energycan be ventured to aid the memory functions with multilevel (3-bit)storage capabilities. Furthermore, our devices exhibit linear andsymmetry in conductance weight updates when subjected to electricalpotentiation and depression. This feature has enabled us to attaina high classification accuracy while training and testing the ModifiedNational Institute of Standards and Technology datasets through artificialneural network simulation. This work paves the way toward reliabledata processing and storage using 2D semiconductors with high-packingdensity arrays for brain-inspired artificial learning.