Defect generation in a data-storage layer by strong ion bombardment for multilevel non-volatile memory applications

Highly Linear and Symmetric Analog Neuromorphic Synapse Based on Metal Oxide Semiconductor Transistors with Self‐Assembled Monolayer for High‐Precision Neural Network Computation

“…[ 12 ] Flash memory and ferroelectric field‐effect transistor (FeFET) exhibit outstanding CMOS compatibility and a wide conductance range; however, flash memory requires high operation voltage, and FeFET has poor fatigue characteristics, which results in cycle‐to‐cycle variation. [ 13–15 ] To overcome the limitations of non‐volatile‐memory‐based synapse devices, metal–oxide–semiconductor field‐effect transistors (MOSFETs) were proposed as an alternative approach. [ 16 ] MOSFET synapse devices showed excellent linearity, but they required continuous refresh operations due to the high off current, resulting in high power consumption.…”

“…[12] Flash memory and ferroelectric field-effect transistor (FeFET) exhibit outstanding CMOS compatibility and a wide conductance range; however, flash memory requires high operation voltage, and FeFET has poor fatigue characteristics, which results in cycle-tocycle variation. [13][14][15] To overcome the limitations of non-volatilememory-based synapse devices, metal-oxide-semiconductor This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor transistors for high-precision neural networks. One of the two transistors controls the synaptic weight by charging or discharging the storage node, which leads to a conductance change in the other transistor.…”