In this study, we investigated the effect of an Al2O3 barrier layer in an all-solid-state inorganic Li-based nano-ionic synaptic transistor (LST) with Li3PO4 electrolyte/WO
x
channel structure. Near-ideal synaptic behavior in the ultralow conductance range (∼50 nS) was obtained by controlling the abrupt ion migration through the introduction of a sputter-deposited thin (∼3 nm) Al2O3 interfacial layer. A trade-off relationship between the weight update linearity and on/off ratio with varying Al2O3 layer thickness was also observed. To determine the origin of the Al2O3 barrier layer effects, cyclic voltammetry analysis was conducted, and the optimal ionic diffusivity and mobility were found to be key parameters in achieving ideal synaptic behavior. Owing to the controlled ion migration, the retention characteristics were considerably improved by the Al2O3 barrier. Finally, a highly improved pattern recognition accuracy (83.13%) was achieved using the LST with an Al2O3 barrier of optimal thickness.
In this paper, we propose a one transistor-two resistive RAM (RRAM) (1T2R) device to overcome the non-ideal switching behavior of artificial synapse devices, such as the unidirectional and abrupt change in the conductance. Our findings reveal that the 1T2R device can exhibit bidirectional conductance changes using unidirectional switching RRAMs. Thus, we introduce a unidirectional but analog switching Cu-based RRAM device (Cu/Cu2-X S/WO3-X/W) having an internal voltage suppressor (Cu2-XS) to realize a bidirectional and analog 1T2R synapse device. The synaptic behaviors of the 1T2R device are calculated using the subthreshold region of an NMOSFET. In addition, we improve the on/off conductance ratio and conductance change linearity owing to the nonlinear current transition characteristics of the subthreshold region. Finally, we demonstrate that an ideal synaptic behavior can be achieved through the 1T2R device even when non-ideal switching RRAM elements are used.
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