Standards for the characterization of endurance in resistive switching devices
Resistive switching (RS) devices are emerging electronic components that could have
applications in multiple types of integrated circuits, including electronic memories, true …
applications in multiple types of integrated circuits, including electronic memories, true …
Volatile and nonvolatile memristive devices for neuromorphic computing
Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …
endow memristors with a physically tunable conductance to resemble synapses, neurons …
Thousands of conductance levels in memristors integrated on CMOS
Neural networks based on memristive devices,–have the ability to improve throughput and
energy efficiency for machine learning, and artificial intelligence, especially in edge …
energy efficiency for machine learning, and artificial intelligence, especially in edge …
Wafer-scale integration of two-dimensional materials in high-density memristive crossbar arrays for artificial neural networks
Two-dimensional materials could play an important role in beyond-CMOS (complementary
metal–oxide–semiconductor) electronics, and the development of memristors for information …
metal–oxide–semiconductor) electronics, and the development of memristors for information …
Hafnium Oxide (HfO2) – A Multifunctional Oxide: A Review on the Prospect and Challenges of Hafnium Oxide in Resistive Switching and Ferroelectric Memories
Hafnium oxide (HfO2) is one of the mature high‐k dielectrics that has been standing strong
in the memory arena over the last two decades. Its dielectric properties have been …
in the memory arena over the last two decades. Its dielectric properties have been …
Memristor modeling: challenges in theories, simulations, and device variability
This article presents a review of the current development and challenges in memristor
modeling. We review the mechanisms of memristive devices based on various …
modeling. We review the mechanisms of memristive devices based on various …
Hardware implementation of memristor-based artificial neural networks
Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …
techniques, which rely on networks of connected simple computing units operating in …
[HTML][HTML] Reliability of analog resistive switching memory for neuromorphic computing
As artificial intelligence calls for novel energy-efficient hardware, neuromorphic computing
systems based on analog resistive switching memory (RSM) devices have drawn great …
systems based on analog resistive switching memory (RSM) devices have drawn great …
Nanoionic memristive phenomena in metal oxides: the valence change mechanism
This review addresses resistive switching devices operating according to the bipolar
valence change mechanism (VCM), which has become a major trend in electronic materials …
valence change mechanism (VCM), which has become a major trend in electronic materials …
Graphene memristive synapses for high precision neuromorphic computing
Memristive crossbar architectures are evolving as powerful in-memory computing engines
for artificial neural networks. However, the limited number of non-volatile conductance states …
for artificial neural networks. However, the limited number of non-volatile conductance states …