Resistive switching materials for information processing
The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
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 …
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 …
Electrochemical‐Memristor‐Based Artificial Neurons and Synapses—Fundamentals, Applications, and Challenges
Artificial neurons and synapses are considered essential for the progress of the future brain‐
inspired computing, based on beyond von Neumann architectures. Here, a discussion on …
inspired computing, based on beyond von Neumann architectures. Here, a discussion on …
Bridging biological and artificial neural networks with emerging neuromorphic devices: fundamentals, progress, and challenges
As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …
computing using novel neuromorphic devices. The potential of various emerging materials …
A review of artificial spiking neuron devices for neural processing and sensing
A spiking neural network (SNN) inspired by the structure and principles of the human brain
can significantly enhance the energy efficiency of artificial intelligence computing by …
can significantly enhance the energy efficiency of artificial intelligence computing by …
Semiconductor quantum dots for memories and neuromorphic computing systems
The continued growth in the demand of data storage and processing has spurred the
development of high-performance storage technologies and brain-inspired neuromorphic …
development of high-performance storage technologies and brain-inspired neuromorphic …
Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse
Neuromorphic computing targets the hardware embodiment of neural network, and device
implementation of individual neuron and synapse has attracted considerable attention. The …
implementation of individual neuron and synapse has attracted considerable attention. The …
Artificial neuronal devices based on emerging materials: neuronal dynamics and applications
Artificial neuronal devices are critical building blocks of neuromorphic computing systems
and currently the subject of intense research motivated by application needs from new …
and currently the subject of intense research motivated by application needs from new …
Leaky integrate-and-fire neurons based on perovskite memristor for spiking neural networks
JQ Yang, R Wang, ZP Wang, QY Ma, JY Mao, Y Ren… - Nano Energy, 2020 - Elsevier
Artificial neuron is an important part of constructing neuromorphic network in which
information can be computed with high parallelism and efficiency like in the human brain …
information can be computed with high parallelism and efficiency like in the human brain …