High-Accuracy Deep Neural Networks Using a Contralateral-Gated Analog Synapse Composed of Ultrathin MoS₂ nFET and Nonvolatile Charge-Trap Memory

The development of high-accuracy analog synapse deep neural networks entails devising novel materials and innovative memory structures. We demonstrated an analog synapse with contralateral gates based on a two-dimensional (2D) field-effect transistor and nonvolatile charge-trap memory. Vertical integration of a MoS
₂
-channel FET with a charge-trapping layer provided excellent charge controllability and gate-tunable nonvolatile storage. In the proposed contralateral-gate design, the read and write operations were separated to mitigate read disturb degradation. Reducing the MoS
₂
-channel thickness to the ultrathin scale allowed large threshold voltage shifts and on-resistance (R
_ON
) modulations. This vertically integrated MoS
₂
-synapse device exhibited 55 conductance states, high conductance max-min ratio (G
_MAX
/G
_MIN
; ~50), low nonlinearity of α
_p
= -0.81 and α
_d
= -0.31, near ideal asymmetry of 0.5, and free of read disturb degradation. High neural network accuracy (>87%) is also obtained.