Demonstration of Synaptic Characteristics in VRRAM with TiN Nanocrystals for Neuromorphic System

Abstract

To efficiently develop an extremely intensive storage memory, the resistive random‐access memory (RRAM), which operates by producing and rupturing conductive filaments, is essential. However, due to the stochastic nature of filament production, this filamentary type resistive switching has an inherent limitation, which entails the unpredictability of the driving voltage and resistance states. Several strategies such as doping, research into multilayer stacks, and interface engineering, are suggested to tackle this challenge. This work fabricates a CMOS‐compatible TiN/HfOx/TiN‐NCs (nanocrystals)/HfOx/TiN RRAM to implement analog resistive switching and advance the development of the synaptic device. Specifically, atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) are utilized to observe the formation of TiN nanocrystals, which play a crucial role in the enhancement of resistive switching. By comparing HfOx–based RRAM devices with and without NCs, the DC I–V curves, retention, endurance, and switching speed are properly examined. Interestingly, it is found that the TiN/HfOx/TiN‐NCs/HfOx/TiN device is more appropriately utilized as an artificial synapse in neuromorphic systems mainly due to its stable and reliable resistive switching properties. Finally, this work demonstrates well‐controlled resistive switching 3D vertical RRAM with TiN‐NCs, which is particularly suitable for high‐density memory.

Synaptic Properties and Short‐Term Memory Dynamics of TiO2/WOx Heterojunction Memristor for Reservoir Computing

“…[8] Based on the efficient structure of the human brain, next-generation memory devices, such as ferroelectric random-access memory, [9] phase-change random-access memory, [10] magnetic random-access memory, [11] and resistive random-access memory (RRAM) [12] have been developed as neuromorphic and neuro-hybrid devices. Specifically, two-terminal memristors have gained significant interest from both industry and academia owing to their ease of fabrication, high durability, low-power consumption, [13][14][15] high-switching speed, [16,17] long data retention, [18,19] and excellent compatibility characteristics with current complementary metal-oxide-semiconductor technology. [20,21] Memristors have been actively researched for various synaptic properties, including nonlinear transmission properties, excitatory postsynaptic currents (EPSC), the conversion of short-term plasticity (STP) to long-term plasticity (LTP), spikerate-dependent plasticity (SRDP), and spike-timing-dependent plasticity (STDP).…”

Programmable Retention Characteristics in MoS2-Based Atomristors for Neuromorphic and Reservoir Computing Systems

“…Present artificial intelligence and big data applications require substantial computational power, thus leading to the need for high efficiencies and high-performance processing abilities. − The traditional complementary metal-oxide semiconductor (CMOS)-based von Neumann architecture has reached the limit of data-processing speed between the central processing unit and the memory; further advances are required to improve the fundamental computing structure to overcome this challenge. Neuromorphic computing, which emulates neuronal and synaptic functions in the brain, is currently gaining attention owing to its efficient data-processing capabilities and mechanisms.…”

Synaptic Characteristics of Fully Depleted Silicon‐on‐Insulator Metal‐Oxide‐Semiconductor Field‐Effect Transistors and Synapse‐Neuron Arrayed Neuromorphic Hardware System

“…The result of much research on the neuromorphic mimicking of memory and learning behaviors has rapidly developed through various nanoscale devices. [ 1 ] For example, devices emulating the function of biological synapses have been investigated through work in resistance random access memory (RRAM), [ 2 ] conductive bridge random access memory (CBRAM), [ 3 ] phase‐change memory (PCM), [ 4 ] spin‐torque transfer magnetic random access memory (STT‐MRAM), [ 5 ] flash memory, [ 6 ] and field‐effect transistors (FETs) to overcome limitations of conventional computing systems. [ 7 ] As the most crucial property for these devices, synapse plasticity is the ability to strengthen or weaken over time in response to the frequency and strength of stimulations.…”