Off-State Operation of a Three Terminal Ionic FET for Logic-in-Memory

Abstract

We demonstrate a novel concept for low power compute-in-memory applications in a room temperature fabricated ZnO/Ta 2 O 5 thin film transistor. By writing during the off-state, the device power consumption is reduced to nW despite a large L/W ratio. A thinner gate insulator thickness gives higher on/off ratio, nevertheless this reduces the retention time. The on/off ratio in the thicker oxide can be improved by asymmetric voltage pulses of higher magnitude in the off state without affecting power consumption. Benchmarked against other ReRAM devices, the device shows a competitive 8 nJ per transition, which allows a reduction in power consumption compared to a filamentary device. Such non-filamentary devices have closer similarity to biological synapses on account of slow operating speed.INDEX TERMS Tantalum oxide, zinc oxide, oxygen vacancies, memory TFTs and compute-in-memory.

A Solid Electrolyte ZnO Thin Film Transistor for classification of spoken digits using Reservoir Computing

“…2. The movement of oxygen vacancies (V 2+ ) in the gate insulator Ta2O5 caused by an electric field, drives the operation of this device [8]- [9]. The measured conductance values of the SE-FET with a pulse train of ±1 V/ 60 ms applied at the gate terminal shows the gradual change in conductance which results in multiple conductance values as shown in Fig.…”

“…The conductance was measured in the off state [8] i.e. when no gate pulse is applied, as shown in the inset of Fig.…”

Reservoir Computing for Temporal Data Classification Using a Dynamic Solid Electrolyte ZnO Thin Film Transistor

“…In this paper, we experimentally demonstrate our new approach to generate high dimensionality by reading the response of the SE-FET after each pulse. The gate terminal is used for the write operation, whereas the drain terminal is used to perform read operations independently when the device is off, further reducing power consumption (Song et al, 2019). The use of the separate control terminal makes the RC system efficient and straightforward compared to any two-terminal-based artificial neural network.…”