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

Thermally-driven Multilevel Non-volatile Memory with Monolayer MoS2 for Neuro-inspired Artificial Learning