Resistive switching and synaptic properties of fully atomic layer deposition grown TiN/HfO2/TiN devices

Abstract

Recently proposed novel neural network hardware designs imply the use of memristors as electronic synapses in 3D cross-bar architecture. Atomic layer deposition (ALD) is the most feasible technique to fabricate such arrays. In this work, we present the results of the detailed investigation of the gradual resistive switching (memristive) effect in nanometer thick fully ALD grown TiN/HfO2/TiN stacks. The modelling of the I-V curves confirms interface limited trap-assisted-tunneling mechanism along the oxygen vacancies in HfO2 in all conduction states. The resistivity of the stack is found to critically depend upon the distance from the interface to the first trap in HfO2. The memristive properties of ALD grown TiN/HfO2/TiN devices are correlated with the demonstrated neuromorphic functionalities, such as long-term potentiation/depression and spike-timing dependent plasticity, thus indicating their potential as electronic synapses in neuromorphic hardware.

Analog Memristive Synapse in Spiking Networks Implementing Unsupervised Learning

“…To switch the device from LRS to HRS, and vice versa, DC sweeps from 0 V to 1 V (LRS to HRS) and from 0 V to −0.7 V (HRS to LRS) are applied. The device maximum resistance (read at 100 mV) ratio obtainable in DC is about one order of magnitude, which is in agreement with the literature (Garbin et al, 2015; Matveyev et al, 2015; Wang et al, 2015). …”

“…The human brain is a massively parallel, fault-tolerant, adaptive system integrating storage and computation (Kuzum et al, 2013; Matveyev et al, 2015). Moreover, it is able to visually recognize a large amount of living beings and objects and to process huge volumes of data in real-time (Kuzum et al, 2013; Yu et al, 2013a; Wang et al, 2015).…”

“…A second proposed approach is to consider multi-memristor synapses (compound synapse with stochastic programming) (Bill and Legenstein, 2014; Burr et al, 2015; Garbin et al, 2015; Prezioso et al, 2015) at the expense of increased area consumption. Only recently some works demonstrated analog behavior in both potentiation and depression without current or voltage control (Park et al, 2013; Covi et al, 2015, 2016; Matveyev et al, 2015; Brivio et al, 2016; Serb et al, 2016). …”

Имитация Синаптической Связи Нейроноподобных Генераторов С Помощью Мемристивного Устройства

“…Зависимость эф-фективности синаптической связи (усиление связи -потенциация, спад -депрессия) от соотношения времен прихода импульса на синапс (механизм spike timing dependent plasticity -STDP) была продемонстрирована в мемристивных системах (см., например, обзоры [2,3]). Для демонстрации различных форм STDP-механизма используют непрерывный (аналоговый) характер изме-нения сопротивления в мемристивных структурах под действием пре-и постсинаптических сигналов с формой, подобной биологическим импульсам -спайкам [4]. Для генерации таких сигналов используются специальные электрические схемы на основе стандартных цифровых элементов.…”

Multistate Resistive Switching Memory for Synaptic Memory Applications

“…Moreover, it would combine memory and computation in a single electronics element. [7] On the other hand, to increase the bit density and to reduce the cost per bit, memory devices with multilevel characteristics are required. [8] Over the last decade, several attempts were made to demonstrate the multi-bit memory performance in different device architectures.…”