RESUMO
The first report of a quantized conductance atomic threshold switch (QCATS) using an atomically-thin hexagonal boron nitride (hBN) layer is provided. This QCATS has applications in memory and logic devices. The QCATS device shows a stable and reproducible conductance quantization state at 1·G0 by forming single-atom point contact through a monoatomic boron defect in an hBN layer. An atomistic switching mechanism in hBN-QCATS is confirmed by in situ visualization of mono-atomic conductive filaments. Atomic defects in hBN are the key factor that affects the switching characteristic. The hBN-QCATS has excellent switching characteristics such as low operation voltage of 0.3 V, low "off" current of 1 pA, fast switching of 50 ns, and high endurance > 107 cycles. The variability of switching characteristics, which are the major problems of switching device, can be solved by reducing the area and thickness of the switching region to form single-atom point contact. The switching layer thickness is scaled down to the single-atom (≈0.33 nm) h-BN layer, and the switching area is limited to single-atom defects. By implementing excellent switching characteristics using single-layer hBN, the possibility of implementing stable and uniform atomic-switching devices for future memory and logic applications is confirmed.
RESUMO
All solid-state lithium-ion transistors are considered as promising synaptic devices for building artificial neural networks for neuromorphic computing. However, the slow ionic conduction in existing electrolytes hinders the performance of lithium-ion-based synaptic transistors. In this study, we systematically explore the influence of ionic conductivity of electrolytes on the synaptic performance of ionic transistors. Isovalent chalcogenide substitution such as Se in Li3PO4 significantly reduces the activation energy for Li ion migration from 0.35 to 0.253 eV, leading to a fast ionic conduction. This high ionic conductivity allows linear conductance switching in the LiCoO2 channel with several discrete nonvolatile states and good retention for both potentiation and depression steps. Consequently, optimized devices demonstrate the smallest nonlinearity ratio of 0.12 and high on/off ratio of 19. However, Li3PO4 electrolyte (with lower ionic conductivity) shows asymmetric and nonlinear weight-update characteristics. Our findings show that the facilitation of Li ionic conduction in solid-state electrolyte suggests potential application in artificial synapse device development.