Recent advances and future prospects for memristive materials, devices, and systems

MK Song, JH Kang, X Zhang, W Ji, A Ascoli… - ACS …, 2023 - ACS Publications
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Neuromorphic computing using non-volatile memory

GW Burr, RM Shelby, A Sebastian, S Kim… - … in Physics: X, 2017 - Taylor & Francis
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

Memory materials and devices: From concept to application

Z Zhang, Z Wang, T Shi, C Bi, F Rao, Y Cai, Q Liu… - InfoMat, 2020 - Wiley Online Library
Memory cells have always been an important element of information technology. With
emerging technologies like big data and cloud computing, the scale and complexity of data …

Synaptic electronics: materials, devices and applications

D Kuzum, S Yu, HSP Wong - Nanotechnology, 2013 - iopscience.iop.org
In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological
synaptic plasticity and learning are described. The material properties and electrical …

Oxide-based RRAM materials for neuromorphic computing

XL Hong, DJJ Loy, PA Dananjaya, F Tan… - Journal of materials …, 2018 - Springer
In this review, a comprehensive survey of different oxide-based resistive random-access
memories (RRAMs) for neuromorphic computing is provided. We begin with the history of …

In-memory learning with analog resistive switching memory: A review and perspective

Y Xi, B Gao, J Tang, A Chen, MF Chang… - Proceedings of the …, 2020 - ieeexplore.ieee.org
In this article, we review the existing analog resistive switching memory (RSM) devices and
their hardware technologies for in-memory learning, as well as their challenges and …

TiOx-Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic …

J Park, M Kwak, K Moon, J Woo, D Lee… - IEEE Electron Device …, 2016 - ieeexplore.ieee.org
We propose TiO x-based resistive switching device for neuromorphic synapse applications.
This device is capable of 64-levels conductance states because of their optimized interface …

Aligned carbon nanotube synaptic transistors for large-scale neuromorphic computing

I Sanchez Esqueda, X Yan, C Rutherglen, A Kane… - ACS …, 2018 - ACS Publications
This paper presents aligned carbon nanotube (CNT) synaptic transistors for large-scale
neuromorphic computing systems. The synaptic behavior of these devices is achieved via …

Unraveling the Effect of the Water Content in the Electrolyte on the Resistive Switching Properties of Self-Assembled One-Dimensional Anodized TiO2 Nanotubes

KA Nirmal, GS Nhivekar, AC Khot… - The Journal of …, 2022 - ACS Publications
The applied potential, time, and water content are crucial factors in the electrochemical
anodization process because the growth of one-dimensional nanotubes can be accelerated …

Memristor devices for neural networks

H Jeong, L Shi - Journal of Physics D: Applied Physics, 2018 - iopscience.iop.org
Neural network technologies have taken center stage owing to their powerful computing
capability for supporting deep learning in artificial intelligence. However, conventional …