Reservoir Computing with Charge‐Trap Memory Based on a MoS₂ Channel for Neuromorphic Engineering

Abstract Novel memory devices are essential for developing low power, fast, and accurate in‐memory computing and neuromorphic engineering concepts that can compete with the conventional complementary metal−oxide−semiconductor (CMOS) digital processors. 2D semiconductors provide a novel platform for advanced semiconductors with atomic thickness, low‐current operation, and capability of 3D integration. This work presents a charge‐trap memory (CTM) device with a MoS 2 channel where memory operation arises, thanks to electron trapping/detrapping at interface states. Transistor operation, memory characteristics, and synaptic potentiation/depression for neuromorphic applications are demonstrated. The CTM device shows outstanding linearity of the potentiation by applied drain pulses of equal amplitude. Finally, pattern recognition is demonstrated by reservoir computing where the input pattern is applied as a stimulation of the MoS 2 ‐based CTMs, while the output current after stimulation is processed by a feedforward readout network. The good accuracy, the low current operation, and the robustness to input random bit flip makes the CTM device a promising technology for future high‐density neuromorphic computing concepts.

Authors

Matteo Farronato; Piergiulio Mannocci; Margherita Melegari; Saverio Ricci; Christian Monzio Compagnoni; Daniele Ielmini

Published

Oct 12, 2022

Journal or venue

Advanced Materials

DOI

10.1002/adma.202205381

Paper type

journal article

Source

Openalex