An overview of phase-change memory device physics

M Le Gallo, A Sebastian - Journal of Physics D: Applied Physics, 2020 - iopscience.iop.org
Phase-change memory (PCM) is an emerging non-volatile memory technology that has
recently been commercialized as storage-class memory in a computer system. PCM is also …

Towards oxide electronics: a roadmap

M Coll, J Fontcuberta, M Althammer, M Bibes… - Applied surface …, 2019 - orbit.dtu.dk
At the end of a rush lasting over half a century, in which CMOS technology has been
experiencing a constant and breathtaking increase of device speed and density, Moore's …

2022 roadmap on neuromorphic computing and engineering

DV Christensen, R Dittmann… - Neuromorphic …, 2022 - iopscience.iop.org
Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging

Y Zhang, GQ Mao, X Zhao, Y Li, M Zhang, Z Wu… - Nature …, 2021 - nature.com
The resistive switching effect in memristors typically stems from the formation and rupture of
localized conductive filament paths, and HfO2 has been accepted as one of the most …

Nanosecond protonic programmable resistors for analog deep learning

M Onen, N Emond, B Wang, D Zhang, FM Ross, J Li… - Science, 2022 - science.org
Nanoscale ionic programmable resistors for analog deep learning are 1000 times smaller
than biological cells, but it is not yet clear how much faster they can be relative to neurons …

Nanoionic memristive phenomena in metal oxides: the valence change mechanism

R Dittmann, S Menzel, R Waser - Advances in Physics, 2021 - Taylor & Francis
This review addresses resistive switching devices operating according to the bipolar
valence change mechanism (VCM), which has become a major trend in electronic materials …

Nonvolatile memory materials for neuromorphic intelligent machines

DS Jeong, CS Hwang - Advanced Materials, 2018 - Wiley Online Library
Recent progress in deep learning extends the capability of artificial intelligence to various
practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis …

Deep machine learning unravels the structural origin of mid‐gap states in chalcogenide glass for high‐density memory integration

M Xu, M Xu, X Miao - InfoMat, 2022 - Wiley Online Library
The recent development of three‐dimensional semiconductor integration technology
demands a key component—the ovonic threshold switching (OTS) selector to suppress the …

Effect of the threshold kinetics on the filament relaxation behavior of Ag‐based diffusive memristors

SA Chekol, S Menzel, RW Ahmad… - Advanced functional …, 2022 - Wiley Online Library
Owing to their unique features such as thresholding and self‐relaxation behavior diffusive
memristors built from volatile electrochemical metallization (v‐ECM) devices are drawing …

Tailoring Mid‐Gap States of Chalcogenide Glass by Pressure‐Induced Hypervalent Bonding Towards the Design of Electrical Switching Materials

M Xu, Q Xu, R Gu, S Wang, CZ Wang… - Advanced Functional …, 2023 - Wiley Online Library
Phase change memory (PCM) and ovonic threshold switching (OTS) materials using
chalcogenide glass are essential elements in advanced 3D memory chips. The mid‐gap …