  The demands of modern electronic components require advanced computing
platforms for efficient information processing to realize in-memory operations
with a high density of data storage capabilities towards developing
alternatives to von Neumann architectures. Herein, we demonstrate the
multifunctionality of monolayer MoS2 mem-transistors which can be used as a
high-geared intrinsic transistor at room temperature; however, at a high
temperature (>350 K), they exhibit synaptic multi-level memory operations. The
temperature-dependent memory mechanism is governed by interfacial physics,
which solely depends on the gate field modulated ion dynamics and charge
transfer at the MoS2/dielectric interface. We have proposed a non-volatile
memory application using a single FET device where thermal energy can be
ventured to aid the memory functions with multi-level (3-bit) storage
capabilities. Furthermore, our devices exhibit linear and symmetry in
conductance weight updates when subjected to electrical potentiation and
depression. This feature has enabled us to attain a high classification
accuracy while training and testing the Modified National Institute of
Standards and Technology datasets through artificial neural network simulation.
This work paves the way for new avenues in 2D semiconductors toward reliable
data processing and storage with high-packing density arrays for brain-inspired
artificial learning.
